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Assessment of Eco-innovative Technologies - Final Report

Report to European Commission ED45757

Issue Number 3

March 2010

Draft Report Assessment of eco-innovation AEA/ED45757/Issue 3 Ref: ENV/C.5/FRA/2006/0071

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Report Assessment of eco-innovation AEA/ED45757/Issue 3 Ref: ENV/C.5/FRA/2006/0071

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Title

Assessment of eco-innovative technologies

Final - Report

Customer European Commission Customer reference Framework contract no.: DG ENV/C.5/FRA/2006/0071

Confidentiality, copyright and reproduction

Unrestricted

File reference ED45757 AEA Gemini Building Harwell IBC Didcot OX110QR UK t: +44 (0)870 190 6604 AEA is a business name of AEA Technology plc AEA Technology is certificated to ISO9001 and ISO14001 Authors Name Florian Hacker (OEKO)

Dr. Wiebke Zimmer (OEKO) Willar Vonk (TNO) Sebastiaan Bleuanus (TNO)

Approved by Name M Woodfield Signature

Date 18 May 2010


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Table of contents

1 Motivation and introduction ........................................................................ 6

2 How to determine the standard assumptions to enable the assessment

of CO2 reduction potential of eco-innovations .................................................. 6

2.1 Case studies ................................................................................................................. 6

2.1.1 Efficient vehicle lighting ................................................................................................ 7

2.1.2 Solar roofs .................................................................................................................. 22

2.1.3 Exhaust heat recovery ................................................................................................ 33

2.2 Issues regarding variations in the effectiveness of the eco innovations .................... 51

2.2.1 Efficient vehicle lighting .............................................................................................. 52

2.2.2 Solar roofs .................................................................................................................. 53

2.2.3 Exhaust heat recovery ................................................................................................ 53

2.2.4 Overview of main factors determining CO2 reduction potential of eco-innovations,

further need of data and standard assumptions ........................................................................ 54


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1 Motivation and introduction The consultants were asked by DG ENV (Guenter Hoermandinger, Malgorzata Golebiewska and

Fabio Dalan) to start preparatory work with respect to methods for assessment of a limited

number of eco-innovations. Standard assumptions for assessing the effectiveness of eco

innovations will be drafted. These assumptions will be made to enable the assessment of the

effectiveness of three relevant eco innovations. These three Eco-innovations are:

• exhaust heat recovery

• solar roofs

• efficient lighting (e.g. LED's)

For each of these, standard assumptions should be derived to enable the quantification of the

possible CO2 reduction and the total contribution of such technologies that would be fair to count

towards an individual manufacturer's average specific emission target

2 How to determine the standard assumptions to enable the assessment of CO2 reduction potential of eco-innovations

2.1 Case studies

Several technologies are under discussion as potential eco-innovations according to the EU regulation that has been implemented recently. Within the scope of this study, three example technologies have been selected in order to discuss their potential to reduce the average CO2 emissions of cars: efficient vehicle lighting, solar roofs and exhaust heat recovery. The objective of this report is to identify the main influencing factors, provide an overview on the availability of corresponding data and suggest possible standard assumptions that could be applied in order to quantify the CO2 benefit of the regarded technologies on a vehicle level. Therefore, within the following sections the example technologies are discussed in the following order: • Firstly, the aspect of eligibility is briefly discussed for every technology in the context of the

eco-innovation regulation; fulfilment of eligibility is a precondition under the EU regulation. • In order to define possible baseline and innovative configurations of the selected technology,

an overview of the current state-of-the-art and future perspectives of the technology and its automotive application is provided.

• Based on these findings on technological features, further factors – including the use of the technology and its application to different vehicle types – which are relevant in order to determine the effective CO2 reduction potential of different technological configurations is discussed.

• Referring to the above-mentioned determining factors, the availability of relevant data and the related uncertainty is discussed. As far as possible, suggestions of standard assumptions to be derived from this data are made and major gaps of data are highlighted.

• In a last step, an approach for determining the CO2 reduction potential of the regarded technologies is presented and first assessment results are presented. The potential for further improvement is discussed with regard to the elaboration of standard assumptions and the development of a robust assessment approach in order to quantify the CO2 reduction potential of eco-innovative technologies.


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2.1.1 Efficient vehicle lighting According to IEA (2006a), each year 55 billion litres of gasoline and diesel are used to operate vehicle lights, representing 3.2 % of total fuel use and equivalent to the consumption of 1.05 million barrels of oil daily. Depending on the vehicle lighting mode, fuel consumption increases in the range of 0.1 to 0.25 l/100 km (WALL 2006). Under standard test-driving cycles, this fuel consumption is not considered because auxiliary devices such as lighting are not activated during testing and are consequently not reflected in the fuel performance figures. Therefore this aspect of vehicle energy performance is currently invisible to end-users and no incentive for manufacturers is given to provide more efficient lights in order to record better fuel-economy test results. However, vehicle lighting has the potential to improve energy efficiency by the use of innovative lighting systems which would consequently reduce the emission level of vehicles that are equipped with corresponding technology.

2.1.1.1 Eligibility of efficient vehicle lighting with regard to Art. 12 on eco-innovations

In order to be considered within EU regulation on passenger cars, eco-innovations have to be checked with respect to several exclusion criteria. In the following the eligibility of efficient vehicle lighting is discussed referring to the main exclusion criteria and major sources of uncertainty in terms of eligibility are highlighted.

Non-coverage by standard test cycle or mandatory provisions

Vehicle lighting is neither covered by the standard test cycle nor by mandatory provisions on a European level and therefore fulfils fundamental prerequisites to be considered as eco-innovative technology. Currently, an improvement of vehicle lighting is not rewarded within the regulation on the emission standards of passenger cars. However, new efficient lighting systems are likely to improve energy efficiency and lower the CO2 emission level of passenger cars substantially, representing a major eligibility criterion for eco-innovations.

Verifiability

To determine the CO2 reduction potential it is assumed that standard assumptions are likely to be used since the efficiency of different lighting systems is well known. In contrast, general assumptions on the operating hours of different types of vehicle lighting have to be made and based on empirical data on vehicle use (see section 2.1.1.4). Spatial and seasonal variations are assumed to be of minor importance since they are likely to be covered by the assumption of average annual use of vehicle lighting. Assuming that the use of vehicle lighting is not dependent on the efficiency of the applied lighting system, the CO2 reduction potential of efficient vehicle lighting is mainly based on technical characteristics and fulfils therefore the verifiability criterion. Efficiency gains are likely to be determined by measurements or calculation, comparing innovative lighting systems with a standard technology.

Baseline configuration

A major challenge in the context of vehicle lighting technology is the definition of the baseline configuration. In the narrow sense, the baseline configuration represents the current standard application of vehicle lighting technology. Innovative technologies are – strictly speaking – more efficient lighting technologies that have not yet been introduced to the market. With regard to vehicle lighting, the current market is characterised by a wide range of different technological concepts depending on the manufacturer, vehicle class and model. Therefore, a general baseline configuration can barely be defined for the entity of passenger cars. On the other hand, automotive lighting technology evolves gradually and the market penetration of innovative technologies correspondingly increases over time. As a result, innovative systems are already being applied to certain vehicles and applications, but have not achieved a considerable overall market share yet (see section 2.1.1.2). A feasible procedure could differentiate between different vehicle classes which require a definition of classes that is stable enough for regulatory purposes. Alternatively, it could define


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threshold values of a maximum market penetration that is allowed before a new technology is no longer considered to be innovative in the context of a certain application.

2.1.1.2 Definition of baseline and innovative configuration of vehicle lighting

Once the general eligibility of efficient vehicle lighting within the implementing regulation on eco-innovative technologies has been determined, an in-depth analysis of available technological concepts and possible lighting configurations is needed in order to quantify potential efficiency gains. Therefore, within the following sections different types of vehicle lighting are presented and standard and innovative lighting technologies are discussed in order to define potential baseline and innovative lighting configurations and quantify the potential technical improvement of efficiency. A baseline configuration of vehicle lighting has to be defined in order to quantify possible emission reduction potentials of different efficient lighting configurations. In the case of vehicle lighting, a distinct lighting technology would have to be assigned to every lighting function (e.g. forward lighting). Depending on the general definition of “baseline”, the baseline configuration could be represented by the most common configuration available or the best technology offered within a vehicle class. Therefore, in this section an overview of types of vehicle lighting is given and possible current and future technological configurations are discussed.

Types of vehicle lighting and applied technologies

The exterior lighting of vehicles can be conveniently divided into two types: forward lighting and signal lighting. Forward lighting is lighting designed to enable the driver to see after dark. Signal lighting is lighting designed to indicate the presence of or give information about the movement of a vehicle, by night and day.

Vehicle forward lighting

Forward lighting includes headlamps and fog lamps, which are characterised by a high luminous intensity. According to IEA (2006a) the use of headlamps in the US accounts for about 43 % of the lighting energy use. Light sources for vehicle forward lighting have to provide sufficient light output to meet the legal requirements that specify the minimum luminous intensities of headlamps. Further, the required amount of light has to be available immediately after switch-on and the lighting technology has to cope with surrounding conditions, such as reliable operation in a wide range of climates, withstand frequent vibration and guarantee a long lifetime. Today, headlamps of modern vehicles are mainly based on either tungsten halogen or xenon discharge (HID) light sources. It is assumed that innovative light emitting diode (LED) headlamps will become of major importance in the coming decades (BOY 2009). Headlamp luminous intensities, light distribution and placement on the vehicle are closely regulated. A main aspect of regulation is that headlamps have to produce two different luminous intensity distributions, so-called high and low beam (BOY 2009).

Vehicle signal lighting

Signal lighting includes front, side, rear position, and turn lamps; stop lamps; rear fog lamps; reversing lamps; daytime running lamps; hazard flashers; and license plate lamps. In contrast to forward lighting, these lamps are usually of smaller size and have a lower luminous intensity. Some signal lamps are used only at night or in conditions of poor daytime visibility (e.g. front and rear position lamps), while others have to be visible at all times (e.g. turn and stop lamps). For many years the technology of vehicle signal lighting hardly changed and was mainly dominated by incandescent light sources covered by clear or coloured lenses. This situation has transformed over the last two decades. Today, signal lighting uses a variety of light sources and methods of optical control and is an integral part of the styling of the vehicle (WOER 2007). The most widely applied light source remains the conventional incandescent one that is characterized by low costs, but also has the disadvantage of relatively short-life time and low-energy efficiency. Due to longer lives, smaller size and smaller power demands, LEDs are already applied to


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vehicles and are expected to become rapidly the light source of choice for vehicle signal lighting (BOY 2009).

A special case of vehicle signal lighting: daytime running lights

Daytime running lamps are pairs of lamps positioned at the front of the vehicle, used during the day to increase the conspicuity of the vehicle. Some countries require their use, some allow their use, and some prohibit their use. Daytime running lamps may be provided by dedicated lamps or by the use of low beam headlamps (BOY 2009). Besides the positive effect of increased road safety due to the use of daytime running lights, the permanent use of forward vehicle lights results in an additional power demand and consequently increasing fuel consumption – in particular when conventional low beam headlamps are used for vehicle lighting. Based on conventional lighting technology various studies (ADAC (2009), HELA (2009)) specify an additional fuel consumption of 0.1 to 0.15 l/100 km, whereas the use of efficient day time running light is likely to generate a significant reduction of fuel consumption due to lower power requirements (BAST (2005): 0.01 to 0.02 l/100 km). As a consequence, national legislation partly requires vehicle manufacturers to equip new passenger cars with dedicated daytime running lights that are optimised for daytime use and dispose of low power lighting sources. On the European level vehicle manufacturers are committed to introducing dedicated daytime running lights on all new types of motor vehicles by 2011. Reversing lamps represent an exception that does not fit into the mentioned classification of forward and signal lighting, since they provide visibility to the rear and a signal to other vehicles.

Innovative vehicle lighting technologies and possible technological configurations

High intensity discharge (HID) lights (e.g. Bi-Xenon)

Xenon front lights continue to increase their share of vehicle lighting. Xenon headlamps were introduced in 1991 as an option in the BMW 7-series and went into series production in 1999. In 2005, already about 25 % of new cars bought in Germany were equipped with Xenon front lights (WOER 2007). Today, due to a considerable price premium, xenon headlights are mainly used on premium products (IEA 2006a). The high-intensity discharge (HID) stands for the electric arc that produces the light. The high intensity of the arc comes from metallic salts that are vaporised within the arc chamber. These lamps are formally known as gas-discharge burners, and produce more light for a given level of power consumption than ordinary tungsten and tungsten-halogen bulbs. Automotive HID lamps are commonly called 'xenon headlamps'. Xenon discharge light sources differ from conventional halogen headlamps in several respects. The most important are the higher amount of light produced, the luminous intensity distribution, and the spectral power distribution of the light emitted. In general, xenon headlamps produce two to three times more luminous flux than conventional halogen headlamps (BOY 2009). Although HID lamps show an efficacy level that is four times greater than halogen headlamps, much of this improvement is currently used to provide more light rather than draw less power. For low and high beam, an energy-efficient use of xenon lamps could lower the power demand by 20 - 45 % (HELA 2009, IEA 2006a).

LED

One light source from which much is expected is the light emitting diode (LED). As a result of technological progress, the construction of headlamps with high power LEDs became feasible and it is expected that vehicle lighting will represent one of the largest near-term opportunities for LED application (IEA 2006a). Present designs give performance between halogen and HID headlamps, with system power consumption slightly lower than other headlamps. Today, LED light sources are mainly applied for signal lighting rather than for forward lighting due to the remaining limitations of LED performance.


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Characteristics of LED

“Electric energy is directly used with semiconductor light diodes to excite electrons, which will then revert to their basic state, emitting light at the same time. A light diode is a classical electrical diode which is operated in the pass direction. In the area of the boundary layer, high-energy electrons can recombine and emit light. LEDs are very small and are operated using low voltages. In the radiated spectrum only light of one wavelength appears” (WOER 2007). With regard to red and amber signal lamps, light diodes are particularly efficient since they radiate the prescribed colour directly. In contrast, conventional incandescent lamps need a red colour filter which absorbs about 75 % of the original luminous flux. Today, as a result of the development of blue and ultra-violet LEDs and due to additive colour mixing, LEDs emitting white coloured light are available. Based on first high performance white LEDs, it is now possible to create headlamps with relatively few LEDs, guaranteeing sufficient performance (WOER 2007). Depending on the kind of application, LED lights could lower the energy demand compared to conventional vehicle lighting in the range of 40 and up to 85 % (HELA 2009, VISTE 2009a, OSRA 2008). Main advantages of LEDs:

� high energy efficiency (2 to 3 times higher than incandescent lamp) – lower power

consumption with higher efficiency (lumens/Watt)

� greater durability and longer life (about 10.000 to 20.000 working hours)

� operation at lower temperatures and no emission of heat radiation

� faster onset or “rise time”, especially relevant for signalling applications

� high efficiency at partial load

Main disadvantages of LEDs: � high costs, in particular for high performance LEDs

� high performance LEDs are sensitive with regard to high temperature and need active

cooling systems

� performance of current LED technology is limited to about 100 W

History and status of technology

When the LED technology emerged, it was first applied to centre high mount stop lamps (CHMSL). In the following years, besides coloured LEDs for signal lighting, new higher output, white colour LEDs were developed which were suitable for automotive forward lighting. Today, all rear signalling functions can be realised, using LED technology. Starting in 2001, first demonstration prototypes with LED headlights were presented by several manufacturers. Due to the high costs of LED technology, their application for forward vehicle lighting however still concentrates on vehicles of the luxury class. For other lighting applications, LED technology is already widely used.

Current application of LED vehicle lighting technology

According to a survey carried out for the light-duty vehicle market in the US (UMTRI 2008b) in 2008, the market penetration of LED varied considerably, depending on the exterior lighting function. In 2008, LED light sources in the US achieved a market share of passenger car sales of less than 1 % for low-beam headlamps, fog lamps, front signalling and marking functions and reverse and license plate lamps. A considerable greater share of LED technology has already been realised for rear turn signal lamps (2.6 %), stop lamps (11.1 %) and in particular for rear signal and marking functions (CHMSL) with a share of 51.2 %.

Future perspectives and limitations

Automotive experts assume that the attractiveness of LEDs for automotive lighting use will further increase in the future. Limitations that once plagued the implementation of LEDs in a headlamp


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have largely receded: output has increased, LED packages have become more suitable, brightness has risen and there are many options for optical coupling. It is expected that remaining hurdles will shrink over time due to a continuous technological improvement (WOER 2007). However, it is expected that LED-technology will mainly increase its market share within the premium segment. Due to the remaining cost advantages of gas discharge light source for head lamp applications, according to expert opinion it is very unlikely that the LED technology will be come the dominating technology (HELLA 2008).

2.1.1.3 Factors determining CO2 reduction potential of vehicle lighting

As illustrated in the previous sections, innovative technologies for different types of vehicle lighting are likely to improve efficiency compared to current standard technologies. In order to quantify the overall potential of CO2 reduction the following factors have to be considered:

- technical configuration and efficiency of vehicle lighting, - average use of vehicle lighting, - further technical specifications of vehicle and on vehicle use.

Technical configuration and efficiency of vehicle lighting

The determination of the power demand of vehicle lighting is a prerequisite for the quantification of the related CO2 emissions. The comparison of different lighting configurations requires the consideration of all types of vehicle lighting and an assignment of specific lighting technologies and related specific power.

Average use of vehicle lighting

Information on the average use of vehicle lighting is crucial in order to combine the power of specific lighting functions with average operation time which allows quantifying the overall energy demand of different lighting configurations. In order to achieve detailed results considering all types of vehicle lighting adequately, information on the average use of every single light source is needed. It is obvious that the average use of lighting may vary considerably depending on the type of vehicle lighting. For example, forward lighting can be generally assumed to be switched on for longer than reverse lighting. With regard to the deduction of average usage times of vehicle lighting it has to be further considered that vehicle lighting is likely to vary among different users and countries due to varying driver behaviour and preferences in terms of lighting usage, national legislation (in particular with regard to mandatory use of daytime running lights), hours and time of daylight (seasonal and geographical variation) and weather conditions. For instance, it can be assumed that the use of vehicle lighting is more frequent in Northern Europe than in Southern Europe and in regions with more frequent bad weather conditions than in regions with more favourable average weather conditions.

Further technical specifications of vehicle and on vehicle use

The quantification of the fuel consumption and related CO2 emissions that are assigned to vehicle lighting requires further information on the average efficiency of the vehicle’s engine and alternator. In particular a differentiation between petrol and diesel passenger cars is suggested as engine efficiency varies considerably among those vehicle types. The average annual mileage is assumed to correlate with the average use of vehicle lighting, but varies considerably among vehicle size classes. Therefore, when quantifying the impact of vehicle lighting on energy consumption and emissions, the average use of vehicle lighting should be adjusted to the average annual mileage of the corresponding vehicle class in a specific country.


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2.1.1.4 Availability of data and deduction of standard assumptions

A reliable assessment of the CO2 reduction potential of efficient lighting requires reliable data on the above-mentioned main determining parameters. In the following a general overview on the availability (and lack) of corresponding data is provided and the possibility of deriving standard assumptions from this data is discussed.


Various technological configurations of lighting can be applied to vehicles. The application of different vehicle lighting technologies is mainly determined by costs and the functionality of the specific technology. In general, more efficient, but also more costly, lighting systems (e.g. LED technology) are mainly applied to higher-class vehicles whereas low-cost lighting technologies with lower efficiency are mainly used within the segment of lower priced vehicles. Often, particularly efficient lighting systems are not part of the standard vehicle equipment, but can be purchased as supplementary equipment. As illustrated above, detailed information on different vehicle lighting technologies for various applications is publicly available and allows the comparison of different configurations in terms of power demand and efficiency. Information on the current standard application of vehicle lighting can be derived from either vehicle or lighting equipment manufacturers (see e.g. OSRA 2008, PHIL 2009). Future perspectives of lighting configuration can be either derived from alternative technologies that are already applied to high-end vehicles or offered as supplementary equipment. Further technical specifications are again provided by the mentioned publications of lighting equipment manufacturers.


Today, little and only non-representative empirical data on the real-world use of vehicle lighting is available. Few studies give detailed information on the average usage of all relevant types of vehicle lighting. In some publications relevant data is limited to the main lighting functions.

Main sources of data

The German Federal Highway Research Institute (BAST) estimates that about 20 % of the total mileage can be assigned to night driving (BAST 2008). On the national level, a systematic survey of the use of vehicle lighting has not however been carried out yet and corresponding data of higher resolution is therefore still missing (BAST 2005). According to WOER (2007) the duty cycle predicts about 1,500 hours of usage for the dipped beam, about 100 hrs for the turn indicator, an average of 600 hrs for the brake light and a maximum of 30 hrs for reverse lights in the context of a vehicle life of 150,000 km. WALL (2006) assumes that in Germany high-beam headlamps are only used in 5 % of driving situations whereas low-beam headlamps with an average use of 95 % represent the most frequently used vehicle light. More detailed information is given in PHOT (2006a), IEA (2006a) and OSRA (2008a) which include detailed information on working hours per year for every type of lighting function; however, the origin of the data and methodology of data collection is not further specified or is only partly traceable. As part of a first approach, IEA (2006a) transposed US figures on the configuration and use of vehicle lighting to other countries and regions, splitting the world into four major regions. According to IEA (2006a), further work is needed to improve the reliability of these estimates, but it is assumed that this first assessment is sufficient to provide a first order of magnitude. A further empirical study of the University of Michigan Transportation Research Institute (UMTRI 2008a) examined the real-world use of automotive lighting equipment in the United States. During the test procedure more than 80 persons were randomly selected from a pool of 6,000 drivers. The driving behaviour was registered over several weeks, covering one year in total. The available data set provides information on daytime and night-time driving hours, the average use of every kind of lighting equipment per year and kilometre and differentiates between different user groups. With regard to the collected data, the generality of the results is limited due to a reported higher annual distance driven than national averages, the non-representativeness of the participants in terms of age group and gender and differences in


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daylight hour distribution due to geographical variations (different time zones) that have not been further examined.

Impact of daylight on headlamp use

Empirical data from a US field operational test (FOT) shows that about 21 % of total mileage is driven by night. But high beam is only used for 3.1 % of the distance driven by night. In general, the use of headlamps increases, the lower the sun position (see Figure 2.1).

Figure 2.1: Use of headlamps (low & high beam) depending on sun position (Source: UMTRI 2006)

Impact of driving situation on headlamp use

The use of forward lighting is mainly determined by the amount of vehicle operation hours during night time or bad weather conditions. Its use is however also likely to vary depending on the driving patterns. For example, in the case of a high share of urban driving, high beam use can be assumed to be rather low. Figure 2.2 shows the share of forward lighting use under different external lighting and driving conditions for a non-representative sample of vehicle users. It illustrates that the use of lighting equipment varies greatly, depending on external conditions and driving situations. Besides an evident relationship between the intensity of daylight and use of lighting equipment, it is further shown that vehicle lighting is more frequently used during highway and interurban driving compared to urban driving situations.


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urbanurbanurban interurbaninterurban interurbanmotorway motorway motorway

< 5,000 lux > 30,000 lux5,000 – 30,000 lux

urbanurbanurban interurbaninterurban interurbanmotorway motorway motorway

< 5,000 lux > 30,000 lux5,000 – 30,000 lux

Figure 2.2: Use of vehicle lights under different driving conditions and depending on light intensity (daylight). Minimum, median and maximum of a sample from 1998-2002 (Source: BAST 2005)

Impact of individual preferences on use of vehicle lighting

Besides external conditions, the use of vehicle lights is likely to be further influenced by individual driver’s preferences. Taking high beam as an example, data from a field observation test (UMTRI 2006) illustrates that its use varies greatly among users depending on their age – older drivers used high beams three times more frequently than younger drivers did – see Figure 2.3. Further analyses of different user groups (UMTRI 2008a) also show differences in the use of signal lighting.

Figure 2.3: Use of high beam by driver age group (Source: UMTRI 2006)


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Use of daytime running light

In Scandinavia, the use of daytime running lights has been mandatory for many years and the use of vehicle lights during the daytime has become general practice. Today, a large number of EU Member States have established national regulations that require the use of daytime running lights (see also Figure 2.4). In some countries, this obligation is limited to the winter season and/or extra urban driving. Assuming that vehicle lighting is performed by conventional low beam, considerable additional fuel consumption is generated and major differences in fuel consumption could be attained between countries with mandatory lighting and other countries. On the other hand, since special daytime running lights will be mandatory within the EU by 2011 the additional fuel consumption will be reduced to a lower amount, but is likely to remain important (see calculation results shown in Figure 2.6) with regard to different legislation in EU Member States on vehicle lighting during the daytime.

Figure 2.4: Overview of regulation on daytime running lights in Europe (Source: Öko-Institut e.V.)

In summary, the available data can provide a basis for a first assessment of vehicle-lighting use that differentiates between different types of vehicle lighting. However, this data does not fulfil the criteria of representativeness in terms of different user groups and individual preferences. Further it neglects the impact of a variable share of driving situations on the use of vehicle lighting and spatial variations due to different national legislation and natural conditions (e.g. weather, daylight distribution). Therefore, the available data on vehicle lighting varies considerably among different sources in terms of total operating hours and the relative distribution between different types of vehicle lighting.


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A more detailed approach considering variations in the use of vehicle lighting for different EU Member States would require consistent empirical data for different regions which is currently not available.


The efficiency of engine and alternator is likely to vary greatly among different passenger cars. Available data and similar approaches determining the lighting-related fuel consumption usually rely only on average engine efficiency. This assumption does however not reflect the fact, that the additional power demand of vehicle lighting is generally related to lower incremental fuel consumption (see KESS 2007) and higher engine efficiency. Due to the considerable difference between average and incremental engine efficiency, it is suggested to consider estimates on the marginal fuel consumption of petrol and diesel engines in order to generate more reliable assessment results of additional fuel consumption caused by vehicle lighting. The average vehicle use per year, represented by the annual mileage, varies depending on vehicle type and size as well as between countries. In general, country-specific data on average annual driving distance is widely available. Therefore, average lighting use can be adapted according to variations of vehicle mileage between countries and vehicle types.

2.1.1.5 Approach for determining the CO2 reduction potential of efficient vehicle lighting

The following discussion illustrates a potential approach for determining the fuel consumption that is related to vehicle lighting and assessing the CO2 reduction potential of efficient vehicle lighting compared to current standard technology. The calculation is based on available data that has been presented in the previous sections and is complemented by additional assumptions. This approach does not differentiate between different countries and should not be understood as representing a standard method for determining the CO2 reduction potential of innovative vehicle lighting. However, it can serve as a first suggestion for the development of a consistent approach and provide a first review of possible impacts and remaining uncertainties.

Description of calculation procedure

In order to quantify the energy consumption and related CO2 emissions of vehicle lighting, Öko-Institut developed a calculation procedure that considers all relevant influencing parameters and enables determination of the greenhouse gas emission levels for different vehicle lighting configurations and vehicle size classes.


The assessment of the CO2 reduction potential due to improved vehicle lighting is carried out for three size classes (small, medium, large) and two types of fuel (petrol and diesel). In order to determine the maximum CO2 benefit achievable, the current standard configuration of vehicle lighting is compared for every vehicle type to an improved configuration that represents the best vehicle lighting technology which could be implemented alternatively. Therefore, every vehicle class is represented by a distinct passenger car model currently on the market. For three car models (VW Polo, VW Golf, Mercedes E-class) that were selected, the current vehicle lighting configuration (standard case) was requested from manufacturers in order to represent every type of vehicle lighting adequately and in as much detail as possible in the computation tool. The current standard lighting configuration varies only slightly between vehicle size classes and conventional lighting technology features heavily. More advanced systems, such as Xenon or even LED are only available as supplementary equipment for most applications. In contrast to these baseline configurations, a second configuration (best case) is elaborated for every vehicle category, comprising the most efficient technology that could be applied for a distinct type of lighting and with currently available lighting technology. The best case configuration is mainly based on energy-efficient LED technology that lowers the energy demand of vehicle lighting by nearly 60 % on average. The following table provides a detailed overview of the lighting technology that is applied for the standard and best case configuration in the calculation procedure.


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Table 2.1: Composition of standard and best case vehicle lighting configuration (for a medium-size car); applied technology and power of applied lighting system

Standard case Best case Technology Conventional lighting LED-based lighting Forward Lighting Low beam H7 (2 x 55 W) JFL2 (4 x 15 W) High beam H15 (2 x 60 W) JFL2 (2 x 15 W) Fog HB4 (2 x 55 W) JFL2 (2 x 15 W) DRL Function H15 (2 x 19 W) JFL2 (2 x 15 W) Front Parking W5W (2 x 5 W) L2W low output (2 x 0.8 W) Front Turn Signal PFY (2 x 24 W) L2W high output (2 x 7.5 W) Rear Lighting Stop W16W(2 x 16 W) L1224R Brake & Turn (2 x 3.5 W) Tail W16W(2 x 16 W) L1224R Tail (2 x 0.75 W) Backup W21W (2 x 21 W) JFL2 (2 x 15 W) CHMSL No standard equipment No standard equipment Side Marker W5W (2 x 5 W) Side Marker Module (2 x 3.5 W) License plate W5W (2 x 5 W) White LEDs (2 x 5 W) Rear Fog W21W (1 x 21 W) L3230R Brake & Turn (1 x 5.3 W) Rear Turn Signal WY21W (2 x 21 W) L1224R Brake & Turn (2 x 3.5 W)


In order to determine the total yearly energy demand of the selected lighting configurations, every single type of vehicle lighting has to be combined with its average annual usage time. Corresponding assumptions on average vehicle operation time have been derived from the empirical data that is discussed in section 2.1.1.4. The following table provides an overview of the main sources of data and the assumptions on lighting operation that have been applied in the scope of this assessment approach. Due to the large variation of the available data on lighting use and its considerable impact on the resulting energy demand and GHG emissions, in the scope of the assessment approach two different assumptions are applied in order to illustrate the range of uncertainty. The first (Case A) mainly relies on data of OSRA (2008) and PHOT (2006) with higher average lighting usage, whereas the second (Case B) is characterized by 40 % lower lighting operation (only DRL remains at the level of case A) which is closer to the data given in UMTRI (2008), WALL (2006) and IEA (2006a).


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Table 2.2: Lighting types and usage [h/year] – available data and assumptions for assessment of vehicle lighting. Definition of two cases

Source OSRA 2008a

PHOT 2006aa

UMTRI 2008

WALL 2006a

IEA 2006a

Assumption for assessment a

Case A: high

operating time

Case B: low

operating time

Forward Lighting

Low beam 200 200 97 189 115 200 120

High beam 30 30 10 10 24 20 12

Fog 75 - - - 120b 75 45

DRL Function

280 280 382 - 341 280 280

Front Parking

220 - 107 199c 115 220 132

Front Turn Signal

75 75 44 13 30 75 45

Rear Lighting

Stop 200 200 81 76 61 200 120

Tail 220 220 107 199c 115 220 132

Backup 25 25 4 4 12 25 15

CHMSL 200 200 81 76c 61 200 120

Side Marker 25 220 107 199c - 25 15

License plate

220 220 107 199c 115 220 132

Rear Fog 20 - - - - 20 12

Rear Turn Signal

75 75 44 13 30 75 45


Depending on the vehicle size, the use of vehicle lighting is adapted to the average annual vehicle kilometres travelled. Finally, in order to determine the additional fuel demand and related greenhouse gas emissions from energy consumption, assumptions on the efficiency of the vehicle’s alternator and engine have to be made (see Table 2.3). The assumed efficiency of alternator as well as the values for energy content and CO2 intensity of different fuels represent standard assumptions that are widely applied in corresponding analyses (e.g. in OSRA (2008), IEA (2006a), BAST (2005)). A major difference of this approach is the assumption on marginal engine efficiency that is related to the additional power demand of vehicle lighting. According to KESS (2007) & KESS (2009) the best-point fuel efficiency of petrol and diesel engines is a good assumption in order to reflect the marginal fuel consumption of additional power demand. The assumption of 195 g diesel per kWh and 200 g petrol fuel per kWh energy output (KESS 2009) implies a marginal engine efficiency of about 43 % for diesel and 41 % for petrol engines which is considerably higher than the average engine efficiency. Data on average European vehicle kilometresd travelled are considered for calculating the fuel demand and greenhouse gas emissions on a kilometre basis [g CO2/km].

a Assumption: average annual mileage of 19,000 km b Including rear fog lamps c Estimation d Source of data: TREMOVE-database (2005)


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Table 2.3: Energy efficiency, fuel consumption and GHG emissions of on-board electricity production (Source of data: KFZT 2009, OSRA 2008, IFEU 2005)

Fuel Alternator efficiency

Marginal engine efficiencye

Energy content of fuel

Energy output of engine

CO2 intensity of fuel

Petrol 59 % 41 % 8.975 kWh/l 1.324 kWh/l 2.326 kg/l Diesel 59 % 43 % 9.929 kWh/l 2.050 kWh/l 2.645 kg/l

2.1.1.6 Results

According to the procedure and assumptions described above, CO2 emissions that are related to vehicle lighting vary in the range of 4.2 to 1.7 g CO2/km under the assumption of high operating time of vehicle lighting (Case A) and 2.8 to 1.2 g CO2/km for lower lighting operation time (Case B). The overall CO2 reduction potential of the best case compared to the standard lighting configuration is in the range of 2.2 to 2.5 gram CO2 per kilometre (Case A) and 1.6 to 1.2 g CO2/km (Case B), depending on the type of engine (due to the different efficiency of petrol and diesel powered engines) and vehicle size. The main results of the calculation procedure are summarised in Table 2.4.

Table 2.4: Energy / fuel consumption and GHG emissions for different lighting configurations and vehicle classes (Results of assessment approach: case A without brackets, case B in brackets)

Fuel Petrol Diesel

Size small medium large small medium large

Example VW Polo VW Golf Mercedes E-

class VW Polo VW Golf

Mercedes E-class

Annual mileage [km]

10,300 12,900 16,500 11,200 16,600 17,400

Lighting efficiency

sta

ndar

d

best

sta

ndar

d

best

sta

ndar

d

best

sta

ndar

d

best

sta

ndar

d

best

sta

ndar

d

best

Energy consumption [kWh/year]

38 (25)

16 (12)

47 (31)

21 (15)

65 (44)

26 (19)

41 (27)

18 (13)

61 (40)

27 (19)

68 (47)

28 (20)

Fuel consumption [l/year]

17 (11)

8 (5)

22 (14)

9 (7)

29 (20)

12 (9)

16 (11)

7 (5)

24 (16)

11 (7)

27 (19)

11 (8)

Emissions [kg/year]

40 (27)

17 (12)

50 (33)

22 (16)

69 (47)

28 (20)

43 (29)

19 (13)

64 (42)

28 (20)

72 (49)

29 (21)

Emissions [g/km]

3.9 (2.6)

1.7 (1.2)

3.9 (2.6)

1.7 (1.2)

4.2 (2.8)

1.7 (1.2)

3.8 (2.6)

1.7 (1.2)

3.9 (2.6)

1.7 (1.2)

4.1 (2.8)

1.7 (1.2)

Emission reduction [g/km]

2.2

(1.4)

2.2 (1.4)

2.5

(1.6)

2.2 (1.4)

2.2

(1.4)

2.4 (1.6)

e Based on the assumption of a marginal fuel consumption of 195 g diesel and 200 g petrol fuel per kWh energy output, respectively


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A slightly higher energy improvement potential can be stated for petrol passenger cars (see Figure 2.5) which is caused by the assumption of lower engine efficiency compared to diesel-fuelled cars.

smal

l, s

tan

dar

d

me

diu

m, s

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diu

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larg

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smal

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est

me

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0

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of

veh

icle

lig

hti

ng

[g

CO

2/km

]

low operating time (Case B) high operating time (Case A) low operating time (Case B) high operating time (Case A)

Petrol Diesel

Figure 2.5: CO2 reduction potential due to improved vehicle lighting technology for different vehicle types. Range of reduction depending on operating time of vehicle lighting (Case A & B) (Results of assessment approach)

The analysis of the share of different types of vehicle lighting with regard to the overall energy demand of vehicle lighting (Figure 2.6) shows that the reduction potential between standard and best case varies considerably between those types. In particular the share of daytime running light increases since the efficiency gain between standard and best case is rather low compared to other types of vehicle lighting. With regard to different types of vehicle lighting, the most important contribution to total energy reduction is assigned to efficient low beam technology in the best case configuration, while the highest relative reduction potential is achieved for signal lighting applications (see Figure 2.7) with a lower total contribution based on only a few average operating hours.


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0.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

400.00

450.00

Standard case Best case

En

erg

y co

nsu

mp

tio

n o

f ve

hic

le li

gh

tin

g [

Wh

/100

km

]

Low Beam

High Beam

Fog

DRL Function

Front Parking

Front Turn Signal

Stop

Tail

Backup

Side Marker

License plate

Rear Fog

Rear Turn Signal

Figure 2.6: Energy demand per type of vehicle lighting (Case A – high operating time). Comparison of standard and best case option (medium-size passenger car) (Results of assessment approach)

0.00

1000.00

2000.00

3000.00

4000.00

5000.00

6000.00

7000.00

8000.00

LowBeam

HighBeam

Fog DRLFunction

FrontParking

FrontTurn

Signal

Stop Tail Backup SideMarker

Licenseplate

Rear Fog RearTurn

Signal

To

tal i

mp

rove

me

nt

of

en

erg

y c

on

su

mp

tio

n [

Wh

/a]

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Re

lativ

e im

pro

vem

ent o

f en

erg

y co

ns

um

ptio

n

total [Wh/a]

relative [%]

Figure 2.7: Total and relative improvement of energy consumption per type of vehicle lighting (Case A). Comparison of standard and best case option (medium-size passenger car) (Results of assessment approach)


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2.1.1.7 Discussion of results

The comparison of current standard lighting technology with more advanced lighting systems shows that relevant improvement in greenhouse gas emissions are likely to be achievable in the future. The results can be considered as the product of a first impact assessment; this is due to various uncertain parameters. The calculation is based on two different cases on the usage time of different types of vehicle lighting, reflecting the large variation within available data. Due to the uncertainty on real-world operation time of vehicle lighting and the major impact it has on the results, further examination is needed concerning this matter. The assumed efficiency of engine and alternator has a strong influence on the generated emission level. Here, assumptions have been set for internal combustion engines that are based on the expected marginal fuel consumption of an additional power demand for vehicle lighting. The assumption of the current standard lighting configuration tends to be reliable since it is based on passenger cars that are currently available, whereas the configuration of the best case is more theoretical. Its composition is derived from the best technology that is currently available for corresponding lighting functions, but it has not been analysed in terms of its technical feasibility in practice. An in-depth analysis of the generated results shows that in particular with regard to forward, stop, tail and turn signal lighting major improvements are likely to be achievable through the application of more energy efficient lighting technologies. The improvement of daytime running lights is rather limited and its share increases from standard to best case configuration. This is due to the fact that a rather efficient technology is already applied in the standard case. In the best case configuration, the share of DRL in terms of the total energy demand of vehicle lighting amounts to 25 %. The improvement of CO2 emissions that can be realised is tightly linked to the definition of a baseline configuration. Current standard lighting configurations are defined as baseline configuration although more efficient lighting systems are already available as supplementary equipment for new passenger cars. Correspondingly, if the current best lighting technology available within a specified vehicle class determined the baseline, the potential of further improvements would be reduced considerably.

2.1.2 Solar roofs The automotive application of PV modules is still in its infancy. Currently, solar roofs are applied in different ways to passenger cars and generated electricity is mainly used to support the ventilation system. These current applications are assumed to have only minor impacts on a vehicle’s CO2 emissions, whereas more effective applications can be expected in the future, assuming more powerful PV modules, larger batteries for energy storage and an increasing electrification of the vehicle’s powertrain. The main effect that is assumed for current applications is a lowering of the fuel consumption resulting from a lower operation time of air conditioning due to pre-cooling or lower power demand of the radiator if the generated electricity is used for heating (e.g. seats). A prerequisite of solar roof applications to be considered as eco-innovation is that the applied technology meets defined eligibility criteria. A first discussion of some main criteria is carried out in the following.

2.1.2.1 Eligibility of solar roof applications with regard to Art. 12 on eco-innovations


Current solar roof applications that are under discussion, such as electric devices enabling a pre-cooling of the vehicle interior or providing additional heating functions, are not covered by mandatory provisions under the “integrated approach”, nor are corresponding effects included in the standard test cycle. Therefore a main criterion for eco-innovation is fulfilled. In contrast, the CO2 savings that can be achieved by current solar roof applications are estimated to be of only minor importance. Whether current solar roof applications can fulfil the CO2 reduction criterion will depend on the final procedure set out in the implementing regulation in terms of the minimum CO2 reduction that will be required for a single eco-innovation.

Verifiability


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The assessment of potential CO2 savings resulting from the application of solar roofs and the generation of electricity that can be used for various applications cannot generally be derived from standard assumptions due to a large number of influencing parameters. The main influencing factors are the amount and availability of electricity generation that depends on the size of PV modules, their efficiency and solar irradiation (temporal and spatial variation, local shading); the kind of application (heating, cooling); individual consumer behaviour (use of heating, cooling options, general use of car); external conditions (temperature). With regard to these factors, mean values cannot generally be derived due to a poor availability of empirical data (with regard to consumer behaviour) and due to spatial variations (in particular with regard to electricity generation) that are likely to occur (see section 2.1.2.4). As a consequence of the large number of influencing factors, the verifiability of emission reduction in the real world is likely to be uncertain. Under current conditions, only rough estimates can be carried out based on assumptions on consumer behaviour, external conditions and operation profiles for the devices of concern (see section 2.1.2.5).

Baseline configuration

Currently, solar roofs for automotive use are only applied in niche markets and at small scale. The final implementing legislation will determine whether current solar roof applications can be considered as eco-innovation. It is expected that innovative solar roof applications will be developed in the future. A baseline definition is required in order to estimate the CO2 reduction potential of vehicles with various kinds of solar roof applications within the EU regulation on eco-innovations, regulation (EC) No 443/2009, article 12, “Eco-innovation”. Due to the fact that solar roofs are currently applied to passenger cars only to a very limited extent, vehicles without solar roof application are likely to be considered as baseline configuration. In the future, a larger amount of electricity generation due to improved PV modules and a larger battery system could lead to a considerable lower demand of fossil fuel for propulsion. The additional on-board electricity generation would have to be considered in a new type approval test for vehicles with electric propulsion. This aspect is however beyond the scope of this study and not discussed in greater detail.

2.1.2.2 Definition of baseline and innovative configuration of vehicle lighting

Although current configurations of automotive solar roof technology are possibly not eligible with regard to the regulation on eco-innovative technologies, this could become possible for improved near-term technological concepts. Therefore, starting from today’s technology, future technological concepts and configurations are discussed in the following so as to enable a definition of possible baseline and innovative applications of solar roofs for passenger cars. These findings on technological concepts are a prerequisite for a first assessment and the quantification of possible future improvements of fuel consumption and emission reduction caused by different solar roof applications.

Current solar roof technologies and application

Current application

At present, the application of PV cells to conventional combustion engine passenger cars is mainly limited to so-called “solar tilt/slide sunroofs”. Due to the low performance of small PV modules the generate electricity is only used to power the car’s air ventilation system while the car is parked in order to lower the temperature within the vehicle, especially in summer, and in order to dehumidify the inside of the car. With regard to the increasing use of on-board electronics in cars and related power demand, corresponding solar roof applications are expected to charge the battery automatically in the future in order to improve the availability of starting power. Such small solar panels for automotive use are already offered by several companies and applied to prototype vehicles.

Available vehicles and applied PV technology

In the early 1990s, Mazda already offered its 929 luxury sedan with optional solar cells in the glass sunroof to drive fans that remove hot air from the car (TERE 2008). Today, low


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performance solar roofs are applied to several vehicle models of the luxury class, such as Audi A8 and A6, VW Phaeton, Bentley, Skoda Superb, Maybach (WEBA 2009). The solar cells that are applied consist of monocrystalline silicon and have an efficiency of 16 %, resulting in a peak power output of 36.7 watts (WEBA 2009). Most onboard solar systems to date have cost several thousand Euros while generating less than 100 watts of energy, improving a vehicle’s fuel efficiency to a very limited extent (TERE 2008). Toyota’s third-generation Prius which was launched in 2009 is equipped with an optional solar panel on its roof. The solar panel is composed of a total of 36 cells with a conversion efficiency of 16.5 %, reaching a maximum output of 50 watts (TECH 2009). The generated electricity powers a ventilation system that can cool the car without help from the engine. The driver can start the fan remotely in order to cool the parked car on sunny, hot days. Therefore, once the car is started, less energy is needed by the air conditioning to do the rest of the cooling (CNN 2008). With regard to future applications, PV panels installed on vehicles could not only feed some of the devices listed above, but could also provide the excess energy to the battery preserving its charge level and extending its lifetime. A corresponding concept has already been developed by a small US company offering rooftop solar panel for retrofitting purposes, providing about 24 watts that can be applied to hybrid vehicles. Although the generated electricity does not charge the hybrid-system battery, it is stored in a lead-acid auxiliary battery that drives the air conditioner, radio and other peripherals (TERE 2008).

Innovative solar roof technologies & possible future technological configurations

Future perspectives

The application of solar energy roofs becomes more attractive when the electrification of passenger cars increases and is therefore of particular interest for hybrid and electric vehicles with a large battery system. Today, solar energy roofs are not yet applied to passenger cars in series production, but some conventional hybrid vehicles have already been retrofitted by adding solar roofs that charge an on-board traction battery.

Concept vehicles, PV technology and potential fuel savings

So-called “solar energy roofs” consist of PV cells that are integrated in the entire roof in order to generate power, which continuously charges the battery of a hybrid or electric car. The performance of corresponding systems is likely to achieve about 100 to 200 watts and to outperform solar sunroofs by far, whereas the efficiency remains rather low at about 17 % (WEBA 2009a). A company called ‘Solar Electrical Vehicles’ in the US adds solar roofs of 200 to 300 watts to passenger cars in order to charge a supplementary battery. A Toyota Prius that is equipped with this kind of solar roof can operate up to 20 miles per day (10 additional miles due to solar panel) in electric mode thus improving fuel economy by up to 29 % (depending on driving habits and conditions) (TRHU 2007). Investigations of the US National Renewable Energy Laboratory (NREL) with a modified Toyota Prius with solar roof that is used to run the auxiliary systems resulted in an additional 5 miles of electric range from the panel (CNN 2008, TERE 2008). According to expert opinion, even if solar cells worked far better than they do today, it is highly unlikely that passenger cars could be entirely propelled by electricity derived from solar panels on the vehicle’s roof in the future. The main constraints of vehicle’s solar roofs with regard to power production are the limited surface area of the car roof and the fact that panels can not be tilted perpendicular to the sun for optimal energy capture (TERE 2008). NREL researcher tested the extent of these limitations, applying a crystalline-silicon cell panel capable of generating a total of 215 watts to a Toyota Prius. Under normal use, the output of the roof panel maxed out already at about 165 watt (TERE 2008). Assuming five hours of good sunlight, the panel delivered an electric output of at most 0.825 kilowatt-hours, resulting in a 5 % increase of the electric driving range of the vehicle.

2.1.2.3 Factors determining CO2 reduction potential of solar roof application

Although the currently available solar roof applications are considered to be of only minor impact in terms of emission reduction, the use of solar roofs for passenger cars may reduce the emission level in the long term. General aspects that have to be considered in order to quantify the


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potential impact of solar roof applications are discussed in this section. Main determining factors that have to be considered are:

- technical configuration and efficiency of solar roof technology - average use of solar roof applications and real-world efficiency - further technical specifications of vehicle and vehicle use

Technical configuration and efficiency of solar roof application

The current application of solar roofs to conventional combustion engine passenger cars generates a low amount of on-board electricity that is not stored, but directly consumed by electric fans or other electric devices. Therefore, its potential to lower CO2 emissions is questionable and very difficult to verify. Assuming more powerful and larger solar roofs with higher energy output in the future, the onboard storage of the generated electricity could become an attractive option. The electricity stored in an on-board battery and accumulated over a larger time-span could provide energy for an increasing number of electric devices and reduce fuel consumption since the battery would not have to be charged and electric devices would not be propelled automatically by the operation of the alternator anymore. In the case that electrification of passenger cars increases (e.g. hybridisation) the electricity generated on board could even feed the traction battery and would consequently extend the electric range of the vehicle and / or could reduce the need of battery charging from the electric grid.

Average use of solar roof applications and real-world efficiency

The amount of electricity that can be generated by solar roofs depends on the performance of the assembled PV modules under standard conditions and the time and conditions of real-world operation. While the technical performance characteristics of PV modules can be easily described, the average use and real-world efficiency of the technology is associated with a much greater uncertainty due to a large number of influencing factors (see Table 2.5). ARSI (2006) summarises the main difficulties of automotive applications of PV module, mentioning the main factors that determine the overall performance: “In automotive applications, PV generators often work with fast time-varying solar irradiation levels due to the movement. Moreover, especially if the solar cells are not placed only on the roof of the car, different subsections of the PV generator may receive different sun irradiance levels, not only during gear, but also whenever the vehicle is parked and trees, lattices or structures in the neighbourhood shade a part of the PV generator. Such working conditions make hard the extraction of the maximum power from the PV generator at each time instant. In fact, even under uniform working conditions, typical of many stationary roof mounted PV generator, it is mandatory to match the PV source with the load/battery/grid in order to draw the maximum power at the current solar irradiance level. [Therefore] particular attention has to be paid in maximizing the net power from solar panels, taking into account the effects of mismatching and non uniform irradiation and temperature. Due to vehicle movement and shading effects, these problems are much more severe than in PV stationary applications.”


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Table 2.5: Factors determining real-world efficiency of solar roofs for automotive application

Selection of parameters determining local shading of solar roofs:

- share of driving situations (urban, interurban, motorway)

- choice of parking opportunity (garage, carport, outside)

- degree of urbanisation at specific location (density, average height of buildings)

- height and density of roadside greenery (urban – rural)

- topography

Further factors influencing module efficiency:

- degree of average panel pollution

- temperature (ventilation) of PV module

- degradation of panel over time

- partial shading leading to mismatching-effects (deactivation of an entire series of cells)

Besides the local variation of solar radiation, the real-world performance of PV modules is also heavily dependent on the geographical variation of solar radiation. Solar radiation decreases with increasing geographical latitude and the usable amount of solar energy can be further limited by bad weather conditions. Therefore, the effective performance of solar roofs is expected to be much higher in Southern compared to Northern Europe and further lowered in regions where bad weather conditions are more frequent due to fewer sunshine hours per day.

Further technical specifications of vehicle and vehicle use

In order to determine the amount of conventional fuel that can be substituted by on-board electricity generation, information on the efficiency of conventional on-board electricity production with a traditional alternator and the engine efficiency with respect to marginal power demand has to be considered. Further the breakdown of fuel savings and emission reduction on a kilometre-basis has to rely on data on the average annual mileage of passenger cars. In the context of distance-based fuel savings, vehicle mileage is of considerable importance due to the fact that the amount of solar energy generation is independent of annual mileage; however, total power consumption increases with rising annual mileage. Therefore, the relative contribution of on-board generated energy decreases with increasing vehicle mileage. Further, situations could occur whereby the electricity demand of the vehicle is lower than the amount of on-board generated electricity and the battery has been charged to the maximum degree possible (most likely during non-operation of the vehicle). This means that it would not be possible to store locally further units of on-board generated energy; these units would then be lost. Consequently the theoretical greenhouse gas emission reduction potential that is expected in terms of the total annual on-board electricity generation would be reduced in practice.


In order to quantify the potential reduction of fuel consumption and related emissions, reliable data on the mentioned categories is required. The following sections provide an overview of available data and assess whether it is possible to derive standard assumptions for relevant categories.

Technical configuration and efficiency of solar roof application

As mentioned above, current applications are unlikely to decrease fuel consumption and the related emissions of passenger cars.


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With regard to the future applications of solar roofs, only a range of possible configurations that are likely to be developed in the near future can be regarded. Technical specifications of PV modules for automotive application can be derived from manufacturers of corresponding systems (e.g. WEBA 2009 & WEBA 2009a). The storage and use of on-board generated electricity has to rely on assumptions based on the technological configuration. In contrast to vehicle lighting, more general assumptions on technical configuration and system efficiency have to be made, due to a poor availability of corresponding data.

Average use of solar roof applications and real-world efficiency

Global data on solar radiation and average sunshine hours is widely available and can be applied in order to determine the maximum energy output that can be expected from solar roof applications depending on the geographical situation. In contrast, local effects that are likely to lower the performance of automotive PV panel applications are more difficult to be determined since empirical data on the average vehicle’s exposure to solar radiation and on possible shading effects is not available. In order to quantify the potential real-world performance of solar roofs, assumptions on the average solar irradiation would have to be made for passenger cars. With regard to the quantification of CO2 reduction potentials due to solar roof application and on-board energy generation, no data is available since current configurations are assumed to have only little effect and perspectives of future configurations are not yet assessed in greater detail.

Solar radiation and theoretical energy output

Average solar radiation and sunshine hours determine the average energy output of PV modules. For Europe detailed data with high spatial resolution is available and can be used to determine the average energy output of a given PV module at any location in Europe. The following calculation is carried out with a Photovoltaic Geographical Information System (PVGIS) that allows a geographical assessment of solar resource and performance of photovoltaic technology within the European Union (see Figure 2.8). This tool is provided by JRC (Institute for Energy, Renewable Energy Unit) and publicly available on the internet (JRC 2008).

Figure 2.8: Graphical interface of the JRC Photovoltaic Geographical Information System (Source:


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JRC 2008)

Impact of vehicle use and local shading

While the consideration of average solar radiation allows the determination of a theoretical maximum energy output of a PV module at optimal, undisturbed conditions, the real-world efficiency is highly influenced by vehicle use, local conditions and resulting local shading of the roof-mounted PV panel. Due to the early stage of technological development and the variety of factors that might cause local shading, no data is publicly available. Therefore, the assessment of the CO2 reduction potential of solar roof applications has to rely on rough estimates that are related to great uncertainty. In order to derive reliable standard assumptions, empirical data on the real-world use of vehicles and occurring shading would be required.


According to efficient vehicle lighting, assumptions on the marginal engine efficiency and alternator efficiency influence the generated fuel saving and emission reduction potential. In the context of solar roof applications, variations of average annual mileage are of even greater importance. In order to reflect potential savings properly it is suggested to differentiate at least among petrol and diesel cars and to consider variations of annual mileage among different vehicle classes and countries.

2.1.2.5 Approach to determine the CO2 reduction potential of efficient vehicle lighting

A first assessment approach is presented in order to roughly estimate the CO2 reduction potential of solar roof application to passenger cars. Due to the poor availability of empirical data, simplifying assumptions have to be made with regard to the use (effective solar irradiation) and efficiency of the applied PV technology.


Technical configuration

It is assumed that generated electricity can be stored in an on-board battery and will be used to (partly) satisfy the energy demand of on-board electric devices. The CO2 reduction potential results form fuel economies that can be consequently achieved since electricity generated on-board no longer has to be provided by the conventional fuel-powered alternator. Other applications, such as the direct consumption of generated electricity without energy storage (current application for ventilation system) or the use of energy for electric propulsion are not considered here. The first because only a minimal effect can be expected and this can hardly be quantified. The latter is due to the remaining uncertainty that is related to the configuration of electric propulsion and the determination of CO2 emission allocation when electricity is provided from the electric grid. The assessment of the CO2 reduction potential is carried out for two different automotive PV panels. The first represents current technology with low performance that is already applied to some vehicles on the market. The second is characterised by higher performance, representing future technological concepts that would cover the entire vehicle’s roof.

Solar radiation and theoretical energy output

Depending on the solar radiation and the number of sunshine hours, the maximum energy output per year can be determined for different locations in Europe. It has to be considered that the overall performance is lowered by the non-optimal horizontal exposure of the PV panel and local shading effects, which requires that appropriate assumptions be made. In order to determine the average output of automotive solar roof panels several assumptions on their characteristics and working efficiency have to be made (see Table 2.6). Two panels of a maximum output (Wp) of 50 and 200 W are considered, respectively. Due to the horizontal installation on the vehicle’s roof, the slope of the panel is set to 0°. Electric system losses do not include the efficiency of electricity generation of the PV panel, but represent losses that occur


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within the electric system (cables, inverters, etc.) only. A value of 14 % system losses is here selected, representing a default value according to (JRC 2008). Based on these general assumptions the energy output is calculated for different European locations (see Table 2.7), reflecting variable geographic conditions of solar irradiation.

Impact of vehicle use and local shading

Major sources of uncertainty are further losses that are related to the shading of the solar roof under real-world conditions. According to an informal expert consultation, shading losses of mobile PV panel applications can be expected to be considerable. Compared to other PV panel applications such as the parking meter that are also frequently affected by local shading, mobile applications are likely to be characterised by even greater losses due to the fact that the PV system cannot be optimised to local conditions, but has to cope with highly variable lighting conditions. In order to reflect the uncertainty that is related to shading losses and real-world-efficiency of solar roof applications, here two different assumptions are applied. It is assumed that the efficiency of solar roofs is lowered in the range of 70 % (Case A) and up to 85 % (Case B). These losses are assumed to occur due to shading effects during vehicle operation or outside parking and situations where the vehicle is parked in closed garages or in carports. A further reduction of available electric energy is likely to occur when electricity is stored over a longer time span due to battery self-discharge. It needs to be considered that the assumption on shading losses cannot rely on any measurement data, but is entirely based on own estimates. On the other hand, it is important to note that shading losses determine heavily the overall benefit of solar roof applications. Therefore, the generated results should be considered as only very rough estimations that have to be further evaluated.

Table 2.6: Assumption on solar performance / configuration and losses of the system and due to shading effects (two different assumptions: Case A & B)

Maximum output of current solar roof (Wp)

Maximum output of future solar roof (Wp)

Slope Electric system losses

Estimated range of shading and other (battery discharge ) losses

50 W 200 W 0° 14 % Case A: 70 % / Case B: 85 %


The amount of electricity that is finally derived is assumed to substitute electricity that is generated by an on-board alternator. In order to determine the amount of conventional fuel and related emissions that can be substituted by an on-board electricity generation, information on the efficiency of conventional on-board electricity production with a traditional alternator has to be considered (see efficient vehicle lighting). The breakdown of fuel savings and emission reduction on a kilometre-basis is carried out, based on average European annual mileage of different vehicle types according to the approach for efficient lighting. Further, an additional electric driving range and the substitutable mileage that could be achieved with electricity from the PV module are stated, but are of only theoretical relevance. These values are generated under the assumption that passenger cars of the future are able to drive electric. The electricity that is generated by the on-board PV panel could hence increase the electric driving range or reduce the amount of electricity that would be needed to be provided by the grid.

2.1.2.6 Results

The first assessment results (see Table 2.7 & Figure 2.9) show that higher performing PV panels could achieve up to 6 g CO2/km emission reduction under most favourable geographical conditions and less than 4 g CO2/km under rather unfavourable conditions for medium-size petrol passenger cars. The lower performing PV panel generates GHG emission savings in the range of 1.5 to 0.9 g CO2/km. The considerably lower effect in the case of medium-size diesel cars (maximum of 4.8 (high) and 2.4 g CO2/km (low performance panel)) is determined by the


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difference of engine efficiency between diesel and petrol-fuelled cars, but in particular caused by the assumption of a considerably higher annual mileage for diesel cars (Base: average European vehicle mileage data). The higher efficiency of diesel engines leads to lower savings, since the substituted electricity could otherwise be provided by diesel-powered vehicles more efficiently. Due to a higher annual mileage of diesel cars, the additional electricity that is provided by the solar roof independently of the annual mileage is allocated to a larger total distance and represents therefore a smaller share of the entire fuel consumption and GHG emissions compared to petrol cars. Assuming an average energy consumption of 20 kWh/100 km for the electric driving of future cars with electric driving capability, the on-board generated electricity could extend the electric driving range by up to 366 kilometres per year under most favourable conditions and substitute up to 2.8 % (petrol car) and 2.2 % (diesel car) of the annual total mileage for the high-performance panel and 92 kilometre per year and 0.7 % / 0.6 % of the annual mileage for the lower performing panel. The above-mentioned figures have been generated under the assumption of a 75 % reduction of the theoretical energy output due to local shading and battery discharge losses. Assuming higher overall losses under real-world conditions of 85 %, the amount of energy output and reduction of fuel consumption and GHG emissions is about halved (see also bracketed figures of Table 2.7).

Table 2.7: Energy output, reduction of fuel consumption / GHG emissions and potential electric driving distance for different solar roof applications at different European locations (Results of assessment approach: case A without brackets, case B in brackets)

Location Madrid Helsinki Berlin Munich Paris London Maximum output [Wp]

50 200 50 200 50 200 50 200 50 200 50 200

Annual output [kWh/year]

18 (9)

73 (37)

11 (5)

43 (21)

11 (6)

46 (23)

13 (6)

52 (26)

13 (6)

50 (25)

11 (6)

45 (23)

Petrol (annual mileage: 12,900 km)

Fuel saving [l/year]

8 (4)

33 (17)

5 (2)

20 (10)

5 (3)

21 (10)

6 (3)

24 (12)

6 (3)

23 (12)

5 (3)

21 (10)

Emission reduction [kg/year]

19 (10)

78 (39)

11 (6)

46 (23)

12 (6)

48 (24)

14 (7)

55 (27)

13 (7)

54 (27)

12 (6)

48 (24)


1.5 (0.8)

6.0 (3.0)

0.9 (0.4)

3.5 (1.8)

0.9 (0.5)

3.8 (1.9)

1.1 (0.5)

4.3 (2.1)

1.0 (0.5)

4.2 (2.1)

0.9 (0.5)

3.7 (1.9)

Additional electric driving range [km/a]

92 (46)

366 (183)

54 (27)

214 (107)

57 (29)

228 (114)

65 (32)

259 (129)

63 (32)

252 (126)

56 (28)

226 (113)

Substituted annual mileage [%]

0.7 (0.4)

2.8 (1.4)

0.4 (0.2)

1.7 (0.8)

0.4 (0.2)

1.8 (0.9)

0.5 (0.3)

2.0 (1.0)

0.5 (0.2)

2.0 (1.0)

0.4 (0.2)

1.8 (0.9)

Diesel (annual mileage: 16,600 km)

Fuel saving [l/year]

7 (4)

30 (15)

4 (2)

17 (9)

5 (2)

19 (9)

5 (3)

21 (11)

5 (3)

21 (10)

5 (2)

18 (9)

Emission reduction [kg/year]

20 (10)

79 (39)

12 (6)

46 (23)

12 (6)

49 (25)

14 (7)

56 (28)

14 (7)

54 (27)

12 (6)

49 (24)


1.2 (0.6)

4.8 (2.4)

0.7 (0.3)

2.8 (1.4)

0.7 (0.4)

3.0 (1.5)

0.8 (0.4)

3.4 (1.7)

0.8 (0.4)

3.3 (1.6)

0.7 (0.4)

2.9 (1.5)

Additional electric driving

92 (46)

366 (183)

54 (27)

214 (107)

57 (29)

228 (114)

65 (32)

259 (129)

63 (32)

252 (126)

56 (28)

226 (113)


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range [km/a] Substituted annual mileage [%]

0.6 (0.3)

2.2 (1.1)

0.3 (0.2)

1.3 (0.6)

0.3 (0.2)

1.4 (0.7)

0.4 (0.2)

1.6 (0.8)

0.4 (0.2)

1.5 (0.8)

0.3 (0.2)

1.4 (0.8)

0

10

20

30

40

50

60

70

80

90

Madrid Helsinki Berlin Munich Paris London

An

nu

al e

mm

issi

on

red

uct

ion

[kg

CO

2/a]

0

1

2

3

4

5

6

7

Distan

ce-based

emissio

n red

uctio

n [g

CO

2/km]

0

10

20

30

40

50

60

70

80

90

Madrid Helsinki Berlin Munich Paris London

An

nu

al e

mm

issi

on

red

uct

ion

[kg

CO

2/a]

0

1

2

3

4

5

6

7

Distan

ce-based

emissio

n red

uctio

n [g

CO

2/km]

Case B (85% losses) [kg/a] Case A (70% losses) [kg/a] Case B (85% losses) [g/km] Case A (70% losses) [g/km]

Figure 2.9: Annual and distance-based emission reduction for petrol passenger cars equipped with low (upper figure) and high performing solar roof (lower figure) at different locations; assuming lower (Case A: 70 %) and higher (Case B: 85 %) losses (Results of assessment approach)

Definition of an average CO2 reduction value for EU-27 While the results presented above illustrate the potential of PV energy generation and CO2 reduction for selected locations within EU-27, more aggregated assumptions are needed in order to quantify the mean reduction potential on the European level and to define an average CO2 reduction value for EU-27, paying particular consideration to variable solar radiation.


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Therefore, the mean annual solar radiation for all European Member States (at the location of its capital city) has been derived by means of PVGIS (JRC 2008). In order to consider the different size of national passenger car markets within the EU, a weighted average of solar radiation in Europe is calculated based on national mean solar radiation (at capitals) and the number of new registered passenger cars per year (passenger car registration data for 2008 derived from EC 2008). This calculation results in a mean annual energy output that is very close to the values that were derived for Munich (see Table 2.7). This means that the average CO2 reduction potential of solar roof applications would be in the range of 1.1 to 4.3 g CO2/km for diesel cars and 0.8 to 3.4 g CO2/km for petrol cars under the more favourable conditions (see Table 2.6, Case A). It is important to note that this weighted average is based on the simplifying assumption that solar roof vehicles would enter the European car market in equal shares according to the national proportion of the newly registered passenger cars on the European level.


The assessment of solar roof applications to passenger cars is carried out for potential future technology concepts that are not on the market yet. This is due to the fact that according to expert consultations the current on-board use of electricity (e.g. for fans) that is generated by small PV panels is unlikely to lead to a significant and measurable reduction of fuel consumption and related GHG emissions. With respect to the technological concepts that are evaluated, it should be noted that uncertainties about possible configurations remain (e.g. storage and use of generated electricity). Therefore, with regard to the impact assessment that has been carried out and the results that were generated, it should be taken into account that a wide range of assumptions had to be made and due to a lack of empirical data great uncertainty remains with regard to several influencing factors. The results of this first impact assessment show however that the emission reduction on a kilometre-basis varies significantly among regions and depends on the assumed engine efficiency (petrol – diesel) and annual mileage. Lower annual mileage and lower engine efficiency of a passenger car lead to greater fuel savings and emission reduction per distance when electricity from a PV panel is used. A weighted average of the emission reduction potential for EU-27 has been derived in order to assess the average reduction potential of solar roof applications on the European level. It considers the spatial variation of solar radiation within the EU and the share of national new passenger cars on the total EU market. The greatest uncertainty that remains is related to the usage of a passenger car with solar roof and its shading since it determines the real-world energy output of the PV panel heavily. As shown above, already rather small variations of the real-world efficiency of solar roofs have important impacts on the overall energy output and the related potential to lower GHG emissions. The determination of the shading and efficiency of a solar roof under real-world conditions is however a very complex issue due to a variety of different sources of shading. Shading can vary greatly among locations (urban – rural, topography) and be further determined by individual behaviour (parking at covered or non-covered locations). Even detailed data on mobility pattern would be of only limited value since it could also be assumed that future drivers of vehicles with solar roof would modify their behaviour in order to enable an efficient operation of the PV module. Currently available publications are based on rough assumptions on the average real-world efficiency of solar roofs. A more reliable assessment of the efficiency of solar roof applications would require empirical data on the average shading of the PV module under different conditions. When evaluating these first results, it has to be noted that they are based on rough estimations – in particular with regard to real-world efficiency – and should therefore be interpreted with caution. These first assessment results are not suitable for deriving final conclusions on the CO2 reduction potential of solar roof applications.


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2.1.3 Exhaust heat recovery For modern IC engines, only a small part of the applied fuel energy is transposed to mechanical energy for vehicle propulsion. The rest of the energy is lost due to heat-rejection to coolant/oil, exhaust heat and other remaining heat and energy losses. Heywood (HEY 1988) describes the energy balance within an engine in the Sankey diagram of Figure 2.10. For SI engines 36-50 % and for Diesel engines 23-37 % of the applied fuel energy is transposed to exhaust enthalpy loss (exhaust energy + unburned fuel energy) at maximum engine power. Other sources state comparable numbers like ± 30 % (TENG 2007, FREY2008 and ENDO 2007).

Figure 2.10: Sankey diagram for IC engine. mfQLHV = fuel flow rate x lower heating value, Qw = heat transfer rate to combustion chamber wall, He = exhaust gas enthalpy flux, Pb = brake power, Ptf = total friction power, Pi = indicated power, Ppf = piston friction power, Qcool = heat-rejection rate to coolant, Qc,e = heat-transfer rate to coolant in exhaust ports, He,s,a

= exhaust sensible enthalpy flux entering atmosphere, He,ic = exhaust chemical enthalpy flux due to incomplete combustion, Qe,r = heat flux radiated from exhaust system, Ee,k =exhaust kinetic energy flux, Qmisc = sum of remaining energy fluxes and transfers

The potential for further improvement of engine efficiency by engine internal measures, like advanced injection timing, reduced pumping losses and high boost pressures, as well as improving thermodynamic efficiency and reducing losses, is limited. Therefore new techniques are being explored to further increase further fuel economy. Recovering (a part of) the energy lost through the exhaust is a technology that could contribute to a substantial improvement of overall engine efficiency (HOUN 2007). A number of exhaust heat recovery techniques are described in relevant literature:

- Rankine Cycle - Mechanical Turbo-compounding - Open air Brayton Cycle - Stirling Cycle - Electrical Turbo-Compounding - Thermo Electrical Generator - Compressed air cycle - Hot air engine cycle


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In the case studies feasibility of the techniques (for passenger car application) is important. After studying the mentioned techniques, the case studies are limited to Rankine Cycle, Electrical Turbo-Compounding and Thermo Electrical Generator for the following.

2.1.3.1 Brief description of possible technological configurations of exhaust waste heat

recovery systems

Rankine cycle

In principle with the Rankine (evaporation) cycle, exhaust gas heat is converted to kinetic energy. A schematic reproduction of the Rankine cycle applied to an IC engine is given in Figure 2.11. This cycle is the thermodynamic principle behind today's thermal electricity power plants. Using the exhaust gas heat, a working fluid is heated in a closed circuit until it evaporates. The gaseous working fluid goes to a turbine- or piston-expander that powers an output shaft. The gaseous working fluid is cooled down further and turns into fluid again by a condenser placed after expander. The fluid is then pressurized by a pump and supplied to the evaporator again. This cycle repeats. The rotating output shaft of the expander can be used to power an electric generator or can be coupled to the driveline with an electric-, spring- or hydrokinetic coupling.

Figure 2.11: Plain schematic reproduction of the Rankine cycle applied to an IC engine (ENDO 2007)

When the working fluid is water or engine coolant, the cycle is called the Clausius Rankine Cycle (CRC). When the working fluid is an organic fluid, the cycle is called Organic Rankine Cycle (ORC) (SCHU 2009).

Electrical Turbo-Compounding

An Electrical Turbo-Compound (ETC) system basically converts available waste heat and kinetic energy in the exhaust into electrical power. This case study will describe two possible technologies for Electrical Turbo-Compounding:

- A generator / motor fixed to the turbo shaft (system 1) - A separately mounted turbo-generator (system 2)

A schematic reproduction and system overview of a generator / motor fixed to the turbo shaft is given in Figure 2.12. When the power produced by the turbocharger turbine exceeds the power of the compressor, the surplus power can be converted into electrical power by the use of an electric generator/motor located on the turbocharger shaft (HOPM 2004). The electrical generator in Figure 2.12 is integrated in the turbocharger design, but could also be placed in the area of the turbocharger driven by a system of gears (system 1b). This would make the system more complex and perhaps less efficient, but would give the opportunity to benefit from lower heat load on the generator, as well as lower generator speeds (so less vulnerable to tight tolerances) (BUMB 2006).


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Figure 2.12: generator / motor fixed to the turbo shaft (system 1)

Figure 2.13 shows a schematic reproduction and system overview of a separately mounted turbo/generator. With a turbo / generator, waste heat and kinetic energy available after the after-treatment system can directly be converted into electrical power.

Figure 2.13: separately mounted turbo / generator (system 2)

With both technologies the generated power can be lead to an electric motor / generator mounted on the crankshaft, in order to assist the IC engine. The generated power can also be used to drive other electrical on-board devices, or it can be stored if sufficient storage capacity is available on board the vehicle. The applied motor / generator might replace the alternator and could act as a generator to reload the batteries (HOPM 2004). Alternately, for system 1, power from the batteries can be used, making the generator / motor act as a motor in order to help accelerate the turbo e.g. at cold start or transient conditions. This could boost low engine-speed torque which in turn can have a positive effect on fuel efficiency since higher low-end engine torque enables earlier up-shifts and thus lower overall engine speeds. It should be mentioned that low-speed torque could encourage more dynamic driving and could thus possibly lead to higher fuel consumption.

Thermo Electrical Generator

An automotive application of a thermo electrical generator basically directs waste heat energy in the exhaust through an exhaust heat exchanger. This heat will be pumped as hot coolant through an automotive thermoelectric generator (ATEG), were it is converted into electrical power, see the scheme of Figure 2.14 for further explanation. The generated electrical power can be used to power other electrical on-board devices, to support the alternator or for (in)direct vehicle propulsion support


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Figure 2.14: Plain schematic reproduction of Automotive Thermoelectric Generator technology for exhaust waste heat recovery

Automotive Thermoelectric Generators are devices that utilize the Seebeck effect in order to recover lost heat from an internal combustion engine to electrical energy. The Seebeck effect is the conversion of a temperature difference directly into electrical energy on the interface of two different metal or semi-conductor materials. The Seebeck effect is the reverse of the Peltier-effect, where electrical energy is converted to a temperature difference (WIKIc 2009). A typical ATEG is build up as followed (see Figure 2.15 for a schematic and cross section illustration). The inlet exhaust gas enters the ATEG at the hot side and leaves the ATEG at the cold side of the heat exchanger. A water flow circuit transports excess exhaust heat to the thermoelectric (TE) materials, where it is converted into electrical power (CRA1 2009).

Figure 2.15: top view: schematic reproduction of an Automotive Thermoelectric Generator bottom view: cross section view of an Automotive Thermoelectric Generator

The problem of conventional ATEG’s is that the exhaust temperature is quite variable. As a consequence the TE material either has to be capable of surviving the highest exposure temperature without degradation, or the TE material must be protected against temperatures above its operating temperature limit. Further the TE material is most efficient at a specific small operating temperature range, which also interferes with an effective automotive application. In order to solve these problems and to accommodate the wide range of operating conditions, it is


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proposed to break the ATEG into multiple sections (CRA1 2009). Each section can then be optimized for a much smaller range of operating conditions, controlled by a valve switching system, see Figure 2.16 for an example with 3 sections.

Figure 2.16: Schematic reproduction of a multiple section thermoelectric generator

This case study will be based on the multiple sections ATEG.

2.1.3.2 Eligibility of exhaust heat recovery with regard to regulation on eco-innovations

In order to be considered within EU regulation on passenger cars, eco-innovations have to be checked with respect to several exclusion criteria. In the following the eligibility of exhaust heat recovery is discussed referring to the main exclusion criteria and major sources of uncertainty in terms of eligibility are highlighted.


The effect of exhaust heat recovery, using either one of the three described technologies, is partly measurable by execution of the standard test cycle as described in the regulation on the emission standards for passenger cars. However it is expected that the actual effect of the application of the used technology is not easy to determine for each of the technologies, because possible “shutting off” of the exhaust heat recovery system, in order to determine the baseline, does not remove the possible negative side effects on fuel consumption, for instance caused by an increased exhaust back pressure. Therefore, the baseline vehicle would have to be a vehicle without the system installed, not just with the system switched off. The actual effect of exhaust heat recovery in real world conditions could differ in a positive way from the results obtained on the type approval cycle. It is likely that real world exhaust gas temperatures are higher in comparison with the relatively mild standard test cycle, and therefore more exhaust heat could be converted to usable energy if the system is dimensioned for it. Also the different measures’ savings vary, depending on application and ambient conditions. So while the technologies would reduce real-world fuel consumption, their benefit in the official test cycle’s ambient temperatures could be negligible (AUTO 2009). Further the application of an exhaust heat recovery system is not covered by any mandatory provision as part of the integrated approachf. Therefore exhaust heat recovery systems might be considered as eco-innovative technology depending on the details of the implementing legislation on eco-innovations.

Verifiability

To determine the CO2 reduction potential it is assumed that standard assumptions for each available exhaust heat recovery system are likely to be used since the efficiencies and influencing parameters of the different parts of the exhaust heat recovery systems are becoming to be well known. In contrast spatial and seasonal (temperature and humidity) variations as well as variation in available exhaust heat energy per vehicle type are influencing factors that make deriving mean values for CO2 reduction potential difficult. The verifiability of emission reduction dispersion in the

f Commission Communication COM(2007)19


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real world is possible by mapping the effects of all variation factors. With the currently available information, rough estimates on efficiency gains are likely to be determined by measurements and/or calculation based on assumptions of average European driving with average European vehicles. In these measurements and/or calculation, vehicles with exhaust heat recovery technology should be compared to comparable vehicles with standard technology.

Baseline configuration and definition of innovativeness

Currently, the three described exhaust waste heat recovery technologies are not yet applied in production for automotive energy generation, and could therefore be considered as innovative. However the Rankine Cycle is already a proven method to recover exhaust waste heat for steady-state operation engines and it is expected that exhaust waste heat recovery systems will be developed further in the future, to become ready for application for automotive propulsion (ENDO 2007, MTZ1 2008). Also the other described waste heat recovery technologies are being investigated by OEM’s and suppliers for application for vehicle propulsion (MILL 2006, HOPM 2003, AUTO 2009, CRA1 2009). A baseline definition is required in order to estimate the CO2 reduction potential of vehicles with various kinds of exhaust heat recovery applications within the EU regulation on eco-innovations. Vehicles without exhaust heat recovery application are likely to be considered as the baseline configuration.

2.1.3.3 Definition of baseline and innovative configuration of exhaust heat recovery

In order to define possible baseline and innovative configurations of the selected exhaust heat recovery technologies, an overview of the current state-of-the-art and future perspectives of the technologies and its automotive application is provided for each described exhaust heat technology.

Rankine cycle current state-of-the-art, future perspectives and automotive application

The CRC or ORC concepts are in general used in power plants and industrial applications. Honda, Toyota, BMW, Cummins and CPTI have developed concepts for light and heavy duty drivelines and proven the systems potential. Within these concepts it was demonstrated that packaging of Rankine cycle systems in passenger cars is possible, as shown in Figure 2.17 and Figure 2.18.

Figure 2.17: Packaging of a Rankine cycle based system on a BMW 3-series model (MTZ1 2008)

Figure 2.18: Layout of a Rankine cycle system applied to a Honda Hybrid demonstrator vehicle (ENDO 2007)

Not always fuel savings are published in the literature. For light duty application already engine thermal efficiency increases of 13 % during driving conditions (ENDO 2007) and engine power increases of up to 14 % (FREY 2008) and 20 % (TENG 2007) for engines at steady state partial load conditions, without adding extra fuel were demonstrated. Some study’s show potential fuel


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savings (BSFC) of 7-15 % at different engine loads and speeds. There is quite a lot of work to be done to define the final concept (size, weight, costs and system integration). Examples of future development are:

- Consideration of separate fluid circuits for exhaust, EGR (& cooling?). And condenser position/design plus feed/boost pump type.

- Choice of working fluid (application depending) - Evaluation of design concept of heater and evaporator (chosen material mostly Stainless

Steel despite of the low thermal conductivity, due to corrosion, ballooning and flake/disintegration of aluminum and resp. copper).

- Choice expander principle. Turbines offer higher efficiency, but respond poor in starting torque and velocity changes, and are more expensive. If a turbine is used it is essential to convert energy into electricity before use. (extra costs and complexity) (STOB 2006).

- Development of a controlling concept/strategy for pressures/temperatures, - Choice to be made between electricity capture or coupling to driveline.

Electrical Turbo-Compounding current state-of-the-art, future perspectives and automotive application

The application and potential of the rather new electrical turbo-compounding technology is investigated, in particular by heavy duty engine OEM’s like Caterpillar (HOPM 2003 and HOPM 2004), Iveco (MILL 2006) and John Deere (VUK 2006). Caterpillar has built an ETC system 1 demonstrator that delivered 44kW at 58.600 rpm. With the gained knowledge during investigating this demonstrator, Caterpillar predicts fuel economy improvements of 5 to 10% at steady state engine operation. Their test results also show that other engine performance parameters such as A/F ratio, turbine inlet temperature and exhaust valve temperature are not negatively impacted. (HOPM 2003). John Deere has built an ETC system 2 demonstrator. With this demonstrator 20% maximum engine power increase and 10% fuel economy improvement have been demonstrated at Tier3 conditions [VUK 2006]. Simulations of other parties also demonstrated the systems potential, showing fuel consumption reductions of 1 to 6 %, depending on the driving cycle (MILL 2006) and BSFC improvements of 8 to 9% (HOUN 2007) For ETC technology in the future, the following comments on robustness and complexity can be made:

- The generator / motor fixed to the turbocharger (system 1) might become a robust system in the future, if the heat, the maximum speed and tolerance challenges in the design can be overcome. (HOPM 2004).

- Further benefits of system 1 that can be explored in the future are (HOPM 2003): o Possibilities for omitting the waste gate or VGT (Variable Geometry Turbine) o Turbo assist capability

- The turbo / generator mounted after the after-treatment (system 2) already looks to be fairly robust. Future challenges might lie within packaging and the question if back-pressure after the after-treatment system is enough to have a reasonable output.

Thermo Electrical Generator current state-of-the-art, future perspectives and automotive application

Thermoelectric Generator application for exhaust waste heat recovery is investigated by a number of OEM’s like BMW (LAGR 2005), cluster projects and foundations with participants like Renault Trucks, Renault, Volvo and Valeo (ROWE 2009). BMW has built its first prototype in 2004 as a standalone underfloor unit. BMW has since integrated it into the exhaust gas recirculation (EGR) cooler, see Figure 2.19. It has been demonstrated that this application can reduce fuel consumption by 2% under typical customer driving conditions (AUTO 2009). Other studies and simulations also show typical fuel


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consumption reductions of around 2% to 3% and mention that in the near future ~2013 even 5% to 6% should be achievable by improving the thermoelectric generator efficiency with new thermoelectric materials. (CRA1 2009, SMIT 2009 and WOJC 2006). According to BMW the start of production of the ATEG for passenger cars could already be in model year 2013 (LAGR 2005). For Thermoelectric Generator technology for Automotive exhaust waste heat recovery applications, the following comments on robustness and complexity are made by the studied literature:

- The relative simple system architecture has a limited number of moving parts. Therefore the system can be described as a maintenance free and wear resistant system (WOJC 2006).

- The future thermoelectric materials will significantly increase the ATEG efficiency and the feasibility of the technology (CRA1 2009, SMIT 2009 and WOJC 2006).

- The design challenge lies within optimization of the exhaust heat exchanger without increasing exhaust backpressure.

Figure 2.19: BMW prototype engineering drawings of a thermoelectric generator implemented in the EGR cooler

2.1.3.4 Factors determining CO2 reduction potential of exhaust heat recovery application

Exhaust heat recovery systems have already shown CO2 reduction potential in demonstrator tests and simulations. General aspects that have to be considered in order to quantify the potential real world impact of future production systems are discussed in this section. The main factors that have to be considered for an approximation of CO2 emission reduction potential are:

- The amount of kinetic and heat energy and exergy in the exhaust flux during real world driving. Exergy means energy convertible into usable types such as kinetic or electric energy. The function of heat engine is to transform thermal energy into kinetic energy with higher quality. Therefore, from the perspective of energy quality, a certain amount of heat at high temperature has a higher content of exergy, i.e. useable energy, than the same amount of heat at low temperature, because it can be used more effectively with higher theoretical efficiency in a heat engine (ENDO 2007 and WIKIb 2009).

- The efficiency of exhaust heat recovery (sub)systems for exhaust heat conversion to usable energy. The efficiency of transporting, storing and use of the recovered energy for vehicle propulsion or driving vehicle subsystems, that normally use energy (indirectly) generated by applied fuel energy, also belongs to this determining factor.

- The decrease in engine and driveline efficiency as well as fuel economy decrease due the application of the exhaust heat recovery technology (increased exhaust backpressure etc.).

When the described exhaust heat recovery systems are becoming available on the market, fleet analysis (per member state), and/or a thorough measurement program could be used to determine the actual effect of the used technologies on CO2 and emission reduction.


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In order to quantify the potential reduction of fuel consumption and related emissions, reliable data on the mentioned categories is required. The following sections provide an overview of available data and assess whether it is possible to derive standard assumptions for relevant categories. The type of analysis undertaken here is without prejudice to the actual detailed assessment to be undertaken in any concrete application for an eco-innovation in the future. It serves the purpose of illustration, of highlighting the type of assumptions that need to be made and may be standardised, and to derive an estimate of the order of magnitude of the possible CO2 savings.

Amount of kinetic and heat energy and exergy in the exhaust flux

Amount of heat energy in the exhaust (by the first law of thermodynamics)

Determination of the amount of heat energy in the exhaust can be performed in many ways. For real world driving, there are databases available with emission data of typical European driving with typical European vehicles. Determining the approximate amount of energy in the exhaust can be performed by calculating the applied fuel energy out of online emission data during typical European driving, using the specification of the consumed fuel. With the applied fuel energy and a standard assumption on the amount of fuel energy being transposed to exhaust energy loss, the approximate amount of heat energy in the exhaust can be determined. The standard assumptions on the amount of fuel energy being transposed to exhaust energy loss is based on the available information in the literature (HEY 1988, CRA1 2009, SMIT 2009, TENG 2007, ROWE 2009, FREY2008 and ENDO 2007) and are given in table 2.8a.

Table 2.8a Standard assumptions on the amount of fuel energy being transposed to exhaust energy loss (as a percentage of applied fuel energy)

Exhaust sensible enthalpy flux entering atmosphere

Exhaust total heat energy (pre exhaust ports)

Exhaust total heat energy (post exhaust ports)

SI engines 39 % 47 % 43 % Diesel engines 30 % 36 % 33 % The exhaust energy loss is subdivided in several parts. Depending on exhaust energy recovery system layout and working principle, one of the parts can be chosen. It should be noted that the amount fuel energy being transposed to exhaust energy loss, varies with varying driving conditions, engine load and speed etc. (HEY 1988 and TENG 2007). Therefore, the usage of an assumed fixed percentage only leads to an approximate value of exhaust energy loss. For an exact determination of the exhaust energy loss, the actual exhaust flow and exhaust temperature distribution should be mapped during real world driving with a representation of the European vehicle fleet.

Amount of exergy (available work) in the exhaust

It needs to be pointed out that the first law analysis is sometimes misleading in evaluation of energy available for exhaust heat recovery; because energy per se does not reflect how much mechanical work can be converted. For energy from any source, only part of it is available energy can be converted into useful work, the rest is unavailable energy, i.e. equivalent to energy in the ambient. This available work (exergy) depends largely on exhaust gas temperature (TENG 2007). For this case study, the standard assumptions as given in Table 2.8b are made, because exhaust temperature distribution during the driving cycle was not available for analysis. These assumptions were made based on standard assumptions for exergy/enthalpy ratio’s as a function of exhaust gas temperature (TENG 2007) and assumptions for exhaust temperature distribution (FREY 2008 and LAGR 2005).


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Table 2.8b: Standard assumptions on the amount exhaust heat exergy (as a percentage of applied fuel energy)

Exhaust sensible enthalpy flux entering atmosphere

Exhaust total heat energy (pre exhaust ports)

Exhaust total heat energy (post exhaust ports)

SI engines 10 % 16 % 13 % Diesel engines 6 % 11 % 8 %

Exhaust kinetic energy

Some waste heat recovery systems benefit from kinetic energy in the exhaust. Because kinetic (and electrical) energy can be converted to useful work completely if the conversion processes are reversible or frictionless, their exergy values are equal to their energy values (TENG 2007). The available kinetic energy in the exhaust depends on engine and exhaust specification as well as engine speed and load. Because the non availability of all necessary data, the standard assumptions as given in Table 2.8c are made (HEY 1988).

Table 2.8c: Standard assumptions on the amount of kinetic energy in the exhaust (as a percentage of applied fuel energy)

Exhaust kinetic energy SI engines 4.5 % Diesel engines 3.5 % For Electrical Turbo Compounding technology, the surplus turbine power is also mentioned as a source for waste energy recovery. For application in this case study, surplus turbine power information available in the literature (HOPM 2003) is expressed as a percentage of engine power. The surplus turbine power lies in the range of 10-12 % of engine power. For the case study, the standard assumption for surplus turbine power of 10% of engine power will be made. This assumption is questionable, because it is doubtable if all surplus power can be used for energy recovery. This would mean that the waste gate will not operate anymore and that exhaust backpressure would increase significantly. Because of the complexity and the poor availability of relevant data, this effect is not considered in this exploratory case study. When more profound investigation is performed, it’s recommended to investigate the usable portion of the surplus turbine power, and the exhaust back pressure increase penalty side effect that should be considered.

The efficiency of exhaust heat recovery systems and use of recovered energy

Now that the exergy in the exhaust can be estimated, the efficiencies of the different exhaust heat recovery technologies are important parameters for determining the potential reduction of fuel consumption and related emissions. In this section, for each exhaust heat recovery technology, considered in this case study, standard assumptions will be made for the (sub)systems efficiencies. Also standard assumptions will be made on the efficiencies of transport, storage and consumption of the recovered energy for vehicle propulsion or powering vehicle subsystems.

Rankine cycle efficiencies

Based on the available information in the literature, describing Rankine cycle technology being applied for exhaust waste heat recovery for automotive energy, the standard assumptions as given in Table 2.9a are made for the Rankine cycle efficiency.

Table 2.9a: Standard assumptions on Rankine cycle efficiency

Rankine cycle efficiency for energy conversion (not exergy) (FREY 2008) 0.22 Heat transfer efficiency (FREY 2008) 0.80 Flow and friction efficiency (FREY 2008) 0.90 Expansion efficiency (FREY 2008) 0.70 Approximate total effective Rankine cycle efficiency (FREY 2008 and ENDO 2007) 0.11


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Electrical generator efficiency 0.95 Electrical motor efficiency (HOPM 2003) 0.90 Approximate total system efficiency (of exhaust heat energy recovery) 0.095

Electrical Turbo Compounding efficiencies

Based on the available information in the literature, describing Electrical and mechanical turbo compounding technology being applied for exhaust waste heat recovery for automotive energy, the standard assumptions as given in Table 2.9b are made for the Electrical Turbo Compounding efficiency.

Table 2.9b: Standard assumptions on Electrical Turbo Compounding efficiencies

Approximate turbine efficiency (MILL 2006 and HOPM 2003) 0.80 Electrical generator efficiency (HOPM 2003) 0.92 Electrical motor efficiency (HOPM 2003) 0.90 Approximate total efficiency of a generator / motor fixed to the turbo shaft (system 1)

0.83

Approximate total efficiency of a separately mounted turbo-generator (system 2)

0.66

Thermoelectric Generator efficiencies

The thermoelectric generator efficiency mainly depends on the efficiency of the applied materials and the temperature difference that is obtained in the heat exchanger. The ATEG efficiency ηTE

can be calculated as (SMIT 2009 and CRA1 2009):

hch

ch

TE

TTZT

ZT

T

TT

/1

11

++

−+⋅

−=η

Where Th is the temperature at the hot side of the heat exchanger and Tc is the temperature at the cold side of the heat exchanger. The performance of the device, determined by properties of the thermoelectric materials, is stated as a figure of merit, ZT. At present, typical values for ZT are 0.85 to 1.25, giving the device a maximum efficiency of around 5% at the optimal operating temperature. In the near future, a ZT of 3 might be possible using innovative materials and techniques, increasing the maximum efficiency to 10% to 13%. CRA1 2009 states a relatively steady average ATEG efficiency of around 4.2%, when using a multiple section thermoelectric generator. Based on the available information in the studied literature, the standard assumptions as given in Table 2.10 are made for the present thermoelectric generator efficiencies.

Table 2.10: Standard assumptions on Thermoelectric Generator efficiencies

Multiple section thermoelectric generator efficiency (of exergy) (CRA1 2009) 0.042 Pumping and electrical conversion efficiencies (SMIT 2009 and CRA1 2009) 0.71 Approximate total effective ATEG efficiency (of energy) 0.030 Electrical motor efficiency (HOPM 2003) 0.90 Approximate total system efficiency (of exhaust heat energy recovery) 0.027 The future potential of increasing generator efficiency due to an increased ZT by innovative thermoelectric materials is not considered in the case study and simulations.

The decrease engine and driveline efficiency due to the application of the exhaust heat recovery technology

For an exhaust heat recovery system, a systematic calculation of efficiency must also include the net effect of additional exhaust backpressure caused by the recovery system. Any increase in backpressure, caused by the restriction that the recovery system creates, will increase fuel consumption and reduce the benefits provided by the device (ROSE 2009). The fuel consumption increase ranges around 2% for turbo charged engines and 3.5% for natural aspired engines per


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10kPa increased backpressure for modern engines (JAAS 2007). Each exhaust heat recovery technology has a typical effect on backpressure. The studied literature does not describe exhaust backpressure penalties for the different systems. Based on DPF and muffler pressure drops, the estimations given in Table 2.11 were made for backpressure increases and associated fuel consumption increases. The exhaust backpressure and backpressure penalties increase with increasing engine speed, depending on the application (system and vehicle) (JAAS 2007). The mentioned estimations are assumed average values.

Table 2.11: Standard assumptions for decreases of engine efficiencies due to the application of the exhaust heat recovery technology

Backpr. Increase [kPa]

Fuel consump. Penalty

Rankine cycle for natural aspired engines(integrated in catalyst or muffler) 2-5

< 1 % Rankine cycle for turbocharged engines(integrated in catalyst or muffler) < 1 % Electrical turbo-compounding (system 1) for natural aspired engines

5-10

Electrical turbo-compounding (system 1) for turbocharged engines Electrical turbo-compounding (system 2) for natural aspired engines

5-10

Electrical turbo-compounding (system 2) for turbocharged engines Thermo electric generator for natural aspired engines (integrated in catalyst or muffler)

2-5 < 1 %

Thermo electric generator for turbocharged engines (integrated in catalyst or muffler)

< 1 %

Because of the fact that the studied literature does not provide reliable data on the penalty for the studied exhaust heat recovery systems on increasing backpressure or fuel consumption, and the fact that the effect on fuel consumptions is likely to be < 1 % for most systems, the standard assumptions for the penalties for exhaust waste heat recovery application in this study will all be set to zero. The penalty for the electrical turbo-compounding system 2 is not mentioned in the studied literature, but could be significant. Therefore the fuel consumption reduction potential of this particular electrical turbo-compounding system is not calculated in the simulation.

2.1.3.6 Approach to determine the CO2 reduction potential of exhaust heat recovery

A first assessment approach is presented in order to roughly estimate the CO2 reduction potential of the different exhaust heat recovery technologies. Due to the poor availability of empirical data, simplifying assumptions have been made in the previous section. This section describes the followed calculation procedure and how the assumptions are used for estimating the CO2 reduction potential.


A key assumption in assessing the effectiveness of an exhaust heat recovery system is the drive pattern and other variables (topography, ambient temperature…) which together determine the exhaust temperature. For quantifying the potential reduction of fuel consumption for the case studies, emissions and cycle behaviour of a typical Diesel and petrol vehicle during the CADC cycle (Common Artemis Driving Cycle) are analysed. The CADC cycle represents typical European driving and can be divided into three distinct parts: urban, rural and motorway. It is therefore recommended to use the CADC as the basis for assessing exhaust heat recovery. The influence of factors such as topography, ambient temperature etc can be ignored because the available work in the exhaust gas is largely influenced by the exhaust gas temperature. Since topography and ambient temperature have no significant influence on exhaust gas temperature, their influence on the CO2 emissions reduction potential will be insignificant.]


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With vehicle data, fuel data and the made standard assumptions, the necessary calculations can be made for estimating the potential reduction of fuel consumption of the different exhaust heat recovery technologies. In the illustrative calculation, the following calculation steps are made.

Engine load

With the vehicle road load information, gear switch and acceleration information during the cycle, the actual powertrain load is calculated. Based on road load and vehicle maximum speed and power information, the powertrain efficiency is estimated. The powertrain load is corrected to engine load with the estimated powertrain efficiency. The engine load is calculated as an actual value and as an average for each representative part. Also the total effectively used energy for vehicle propulsion is calculated as a total for each representative part of the CADC.

Applied fuel energy

The applied fuel energy is calculated from the actual emission data during the CADC, based on a carbon balance calculation method for fuel consumption calculation and fuel specifications. The applied fuel energy is calculated as an actual value (actual exposed fuel power; the amount of fuel used multiplied by its lower heating value) and as a total for each representative part of the CADC (total exposed fuel energy).

Engine efficiency

Now that the applied fuel energy is calculated and the engine load is estimated, the engine efficiency can be estimated as an average for each representative part of the CADC cycle. The estimated engine efficiencies are shown in Figure 2.20 and Figure 2.21.

Typical petrol vehicle energy balance over the CADC cycle

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

45.00%

50.00%

Engine efficiency Exh heat energy Exh Kinetic energy

per

cen

tag

e o

f ap

pli

ed f

uel

en

erg

y

CADC TOTAL CADC URBAN CADC RURAL CADC MOTORWAY

Figure 2.20: Typical petrol vehicle engine efficiency, exhaust heat and exhaust kinetic energy expressed as a percentage of applied fuel energy for the different representative parts of the CADC cycle.


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Typical Diesel vehicle energy balance over the CADC cycle

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

Engine efficiency Exh heat energy Exh Kinetic energy

per

cen

tag

e o

f ap

pli

ed f

uel

en

erg

y


Figure 2.21: Typical Diesel vehicle engine efficiency, exhaust heat and exhaust kinetic energy expressed as a percentage of applied fuel energy for the different representative parts of the CADC cycle.

Exhaust energy and exergy

For each part, the amount of different types of available exhaust energy for the different exhaust heat recovery systems is estimated, based on the applied fuel energy calculation and the standard assumptions on the applied fuel energy being transposed to the different exhaust energy types – see Tables 2.8. These assumptions are made as an average for European driving. In order to divide these assumptions to urban, rural and motorway driving, the assumptions are corrected with the engine efficiency proportion (cycle average vs. cycle part average) for the different parts of the cycle. The exhaust energy is calculated as an actual value and as a total for each representative part of the CADC. It can also be expressed as a percentage of the applied fuel energy for each representative part of the CADC, as shown in Figure 2.20 and Figure 2.21 for the studied example vehicles. The actual exhaust heat energy during the CADC cycle is shown in Figure 2.22 for the studied example vehicles.


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Figure 2.22: Actual engine load and exhaust heat energy over the different parts of the CADC cycle for a typical petrol (left) and Diesel (right) vehicle

The exergy could also be calculated, based on the calculated amount of energy. A proper way to do this is to correct the standard assumptions of Table 2.8 with the actual exhaust gas temperature at the entrance of the recovery system. Because this information was not available for the studied vehicle data, an approach could be made with for example a correction as a function of vehicle speed. Because of the fact that the studied literature describes system efficiencies as a ratio of exhaust energy to recovered energy, the exergy determination is not part of the simulation.

Recovered energy and potential fuel saving

Combined with the system efficiency’s and possible increased losses, the exhaust energy estimation leads to an estimation of recoverable energy (as a percentage of applied fuel energy), the results of this analysis are shown in the figures below. The shown results should not be confused with fuel consumption reduction potential, because that depends on internal combustion engine energy that can be replaced by recovered wasted energy.

Typical petrol car | actual energy in exhaust during Urban part of CADC

-20.0

-10.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

128 228 328 428 528 628 728 828 928 1028

time [s]

ener

gy

in e

xhau

st [

kW]

-300

-200

-100

0

100

vehi

cle

spe

ed [k

m/h

]

act heat energy in exhaust average heat energy in exhaustEngine Load ((RL+aL)/eff) average Engine Loadvehicle speed

Typical Diesel car | actual energy in exhaust during Urban part of CADC

-20.0

-10.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

128 228 328 428 528 628 728 828 928 1028

time [s]

ener

gy

in e

xhau

st [

kW]

-300

-200

-100

0

100

veh

icle

sp

eed

[k

m/h

]


Typical petrol car | actual energy in exhaust during Rural part of CADC

-20.0

-10.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

1150 1250 1350 1450 1550 1650 1750 1850 1950 2050

time [s]

ener

gy

in e

xhau

st [

kW]

-300

-200

-100

0

100

ve

hic

le s

pee

d [

km/h

]


Typical Diesel car | actual energy in exhaust during Rural part of CADC

-20.0

-10.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

1150 1250 1350 1450 1550 1650 1750 1850 1950 2050

time [s]

ener

gy

in e

xhau

st [

kW]

-300

-200

-100

0

100

ve

hic

le s

pee

d [

km/h

]


Typical petrol car | actual energy in exhaust during Motorway part of CADC

-20.0

-10.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

2307 2407 2507 2607 2707 2807 2907 3007

time [s]

ener

gy

in e

xhau

st [

kW]

-300

-200

-100

0

100

veh

icle

sp

eed

[km

/h]


Typical Diesel car | actual energy in exhaust during Motorway part of CADC

-20.0

-10.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

2307 2407 2507 2607 2707 2807 2907 3007

time [s]

ener

gy

in e

xhau

st [

kW]

-300

-200

-100

0

100

veh

icle

sp

eed

[km

/h]



48 AEA

potential of exhaust energy recovery of a typical petrol vehicle over the CADC cycle

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

Rankine cycle Electrical Turbo-compounding Thermo Electric Generator

reco

vere

d e

ner

gy

(as

per

cen

tag

e o

f ap

plie

d f

uel

en

erg

y)


potential of exhaust energy recovery of a typical Diesel vehicle over the CADC cycle

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%


reco

vere

d e

ner

gy

(as

per

cen

tag

e o

f ap

plie

d f

uel

en

erg

y)


Figure 2.23 and Figure 2.24: potential of exhaust energy recovery of a typical petrol (top view) and Diesel (bottom view) for the different exhaust heat recovery technologies, expressed as a percentage of applied fuel energy

The amount of engine power that can be replaced by recovered energy, gives an indication of the fuel consumption decrease potential for the example vehicles during typical European driving conditions. Within this indication, the decreasing amount of available exhaust energy for recovery as a direct effect of decreasing required engine energy is ignored for this case study.

2.1.3.7 Results

The first assessment results show that there is a significant fuel consumption and CO2 emission reduction potential for all three investigated exhaust heat recovery technologies. The average engine thermal efficiency increases 2.6% to 14.1%, depending on applied technology and example vehicle (see the tables and pictures below).


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Table 2.12 and Figure 2.25: Average CADC thermal efficiency of a typical petrol vehicle for the different exhaust heat recovery technologies

Average total CADC thermal efficiency Standard engine

25.9%

Rankine cycle

29.6%

Electr. Turbo-Compounding

28.1%

Thermo Electric Generator

27.0%

Table 2.13 and Figure 2.26: Average CADC thermal efficiency of a typical Diesel vehicle for the different exhaust heat recovery technologies

Average total CADC thermal efficiency Standard engine

31.5%

Rankine cycle

34.3%


34.1%


32.3%

Based on these first assessment results, the rough indication can be made that that the fuel consumption and CO2 emission reduction potential equals the engine thermal efficiency increase. The results of this rough indication are shown in the tables and pictures below.

Table 2.14 and Figure 2.27: Average CADC fuel consumption reduction potential of a typical petrol vehicle for the different exhaust heat recovery technologies

Average total CADC CO2 emission reduction potential Rankine cycle

14.1%


8.3%


4.0%

engine thermal efficiency increase of a typical petrol vehicle over the CADC cycle

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

CADC URBAN CADC RURAL CADC MOTORWAY CADC TOTAL

eng

ine

ther

mal

eff

icie

ncy

standard engine Rankine cycleElectrical Turbo-compounding Thermo Electric Generator

engine thermal efficiency increase of a typical Diesel vehicle over the CADC cycle

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

CADC URBAN CADC RURAL CADC MOTORWAY CADC TOTAL

eng

ine

ther

mal

eff

icie

ncy

standard engine Rankine cycleElectrical Turbo-compounding Thermo Electric Generator

fuel consumption reduction potential of a typical petrol vehicle over the CADC cycle

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%


fuel

consu

mption red

uct

ion p

ote

ntial



50 AEA

Table 2.15 and Figure 2.28: Average CADC fuel consumption reduction potential of a typical Diesel vehicle for the different exhaust heat recovery technologies

Average total CADC CO2 emission reduction potential Rankine cycle

9.0%


8.3%


2.6%

The first simple conclusion could be that the exhaust heat recovery technologies applied on petrol fuelled vehicles have the highest CO2 emission reduction potential for average European driving. A simple explanation is that a petrol engine has a lower standard thermal efficiency and therefore a higher exhaust waste heat portion of applied fuel energy is available for recovery, in comparison with a Diesel engine. The first assessment results also show that Rankine cycle recovery technology has the highest CO2 emission reduction potential with 9% for typical Diesel and 14% for a typical petrol fuelled vehicle. Electrical turbo-compounding technology is the second best investigated technology, according the first assessment results, with a CO2 emission reduction potential of approximately 8%, followed by the thermoelectric generator technology that has a reduction potential of 2.6% for a typical Diesel and 4% for a typical petrol fuelled vehicle. The obtained first assessment results are roughly equal to the reduction potentials that are claimed in the literature.


In general the obtained first assessment results only show a rough estimation of the CO2 emission reduction potential of the investigated exhaust heat recovery systems. Some important effects are not considered in the investigation that leads to the first assessment results.

Discussion of Rankine cycle and thermoelectric generator results

A good example is that the effect of a varying exhaust heat exergy / energy ratio, due to varying exhaust temperature (load and speed varying) was not considered, but an assumption on a fixed (average) ratio was made. It might be possible that the ratio between Urban, Rural and Motorway reduction potential in the first assessment results is therefore not correct for Rankine cycle and thermo electric generator technology, because it is likely that the exergy / energy ratio is higher at higher vehicle speeds (higher engine load and thus higher exhaust gas temperatures). However, because the application of the assumed average ratio’s, based on literature, it is likely that the average cycle results do comply with an approach for average European driving. Also the exhaust heat at the spot of recovery technology implementation in the exhaust packaging was not considered in the investigation. The temperature differences between Diesel and petrol exhaust gasses were also not considered, which might have a major influence on exhaust heat exergy and energy recovery efficiency, especially at lower loads. It is likely that if these effects would also be considered in the first assessment results, the CO2 emission reduction advantage of Rankine cycle and thermo electric generator technology application on petrol engines would further increase. Because of the yet mentioned, not considered effects, it is highly recommended to collect exhaust temperature data during average European driving (cycles), if future investigations are to be executed. Exhaust heat exergy calculation should then be based on this data, in order to obtain more reliable cycle (section) results.

fuel consumption reduction potential of a typical Diesel vehicle over the CADC cycle

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%


fuel

consu

mption red

uct

ion p

ote

ntial



AEA 51

In the nearby future, the thermoelectric generator has a high potential for efficiency improvement that can be obtained, and therefore this technology might equal or exceed the Rankine cycle potential for CO2 emission reduction on a relative short notice.

Discussion of electrical turbo-compounding results

First of all, the electrical turbo-compounding results are yet based on a standard assumption for turbocharger surplus power, expressed as a fixed portion of engine power. In reality this surplus power strongly varies with the different turbocharger systems (VTG, etc.) and different engine types. The surplus power can be approached as a portion of engine power, but it would be better to measure it and simultaneously consider the backpressure increase and its effect on engine efficiency when (a part of) surplus turbocharger power is recovered. This would lead to a more reliable and better specified potential for CO2 emission reduction for the different types of average European driving (urban, rural and motorway), which also includes the consideration that not all surplus power might be recoverable without an engine efficiency penalty because of potentially increasing backpressure. The considered typical petrol fuelled vehicle was in fact not a turbocharged vehicle. Therefore, simulating electrical turbo-compounding on an already existing turbocharger is in fact not correct. However the obtained results might be considered as representative for a first assessment, because the obtained results were based on a calculation surplus turbocharger power as a portion of engine power, resulting in a reduction potential based on thermal engine efficiency increase. Alternately if power from the batteries can be used, making the generator / motor act as a motor in order to help accelerate the turbo, this would help to further increase the engine efficiency and drivability in dynamic driving conditions, which could also result in CO2 emission reduction. If future investigations are to be executed, it is recommended to also investigate the potential CO2 emission reduction of this extra application possibility.

Further general point of discussion of results

The effects on CO2 emission of vehicle mass increase and thus engine load increase, due to exhaust waste heat recovery system implementation, were not considered in the current simulation. It is recommended to do so, if future investigations are to be executed. Investigation of the implementation costs, and thus the costs per percentage of CO2 emission reduction potential, of each exhaust waste heat recovery technology was beyond the focus of the case study. This is in the end also an important parameter that determines the feasibility of the different exhaust waste heat recovery technologies, and should therefore also be considered if future investigations are to be executed. The studied cases were yet based on typical European vehicles with a standard (non hybrid) powertrain. Implementation of the investigated exhaust heat recovery technologies in hybrid powertrains is certainly worth considering, because some system parts are already part of the hybrid powertrain (motor, battery’s, etc.) and synergy in improving the powertrain efficiency might be found.

2.2 Issues regarding variations in the effectiveness of the eco innovations

Based on the findings of the previous chapters, the following overview summarises the main aspects that have to be considered when determining the effectiveness of the regarded eco-innovations. A general discussion with regard to the eligibility of technologies and the definition of a baseline configuration is not carried out here, but can be found within the sections discussing the three case studies that were selected.


52 AEA

As already illustrated within the different case study sections, the quantification of the effectiveness of eco-innovations is determined by the definition of standard assumptions on the real-world application, characteristics and use of eco-innovative technologies. In particular with regard to future technologies that are not yet applied at larger scales and where empirical data on their average use is not available, the definition of reasonable assumptions represents a non-trivial task. In order to facilitate a reliable estimation of potential emission reduction potentials of eco-innovative technologies standard assumptions should be defined that reflect, as closely as possible, the real-world usage and resulting efficiency of the proposed eco innovations. The following discussion highlights the most relevant parameters, summarises aspects of data availability and illustrates potential approaches in order to derive reliable standard assumptions with regard to the selected case study technologies (see also Error! Reference source not found. & Error! Reference source not found.).

2.2.1 Efficient vehicle lighting As illustrated in section 2.1.1 on efficient vehicle lighting, technological specifications of vehicle lighting are well known and publicly available. Therefore, depending on the configuration of the vehicle lighting system the required power can easily be defined for single vehicles. The availability of data in terms of market penetration rates of different lighting technologies enables an assessment of the overall impact for the passenger car market. In contrast, the use of vehicle lighting represents the greatest source of uncertainty when defining standard assumptions for an assessment of its GHG emission reduction potential. The use of vehicle lighting is determined by several influencing factors, but empirical data is available only at a very coarse resolution and showing high variation among different sources of data. In order to facilitate a reliable assessment of efficient vehicle lighting at the national level, data on the average use of every type of vehicle lighting would be required, which consider variations that are likely to occur due to different national legislation (e.g. on daytime running lights), geography and topography and reflect variations in driver behaviour. The examination of available empirical data on vehicle lighting use and approaches to determine the fuel consumption of vehicle lighting found in the literature illustrate the uncertainty that is related to data on lighting use in terms of representativeness. The available data is either derived from small field observation tests or based on general assumptions where the source of data is not further specified. A further outcome of field tests on vehicle lighting is the appraisal that the individual use of vehicle lighting varies considerably among drivers and depending on external conditions. A reliable approach to quantify these effects and to enable a transferability of the data to other regions is not available. First estimations on the average use of vehicle lighting are presented in section 2.1.1.5. In order to improve reliability and to include national specification among EU Member States in the differentiation, an EU-wide survey on vehicle lighting use comprising a representative sample of vehicle users would be required. The efficiency of vehicle’s engine and alternator, as well as the annual mileage, are additional parameters with significant influence on the fuel consumption related to vehicle lighting. In practice, the efficiency of engine and alternator is likely to vary between different vehicles. With regard to the formulation of standard assumptions a single distinction between petrol and diesel engines (see Table 2.3) represent a rough, but substantiated, approximation. In order to reflect potential future improvements of engine and alternator efficiency, corresponding information would have to be provided by OEMs. In this context, it is suggested to rely rather on the (higher) marginal engine efficiency that is related to the additional power demand of vehicle lighting than on the (lower) average engine efficiency. The variation of annual mileage among vehicle classes can be reflected by a corresponding variation of vehicle lighting use as it can be assumed that increasing vehicle use is related to an increasing operation time of vehicle lighting. Therefore, within the approach presented in section 2.1.1.5, the standard assumption on the use of vehicle lighting is correlated with the annual driving distance.


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2.2.2 Solar roofs According to the discussion in section 2.1.2 solar roof applications that result in significant reductions of GHG emissions are only expected from future technologies; current marketable applications are not regarded as providing corresponding benefits. Therefore, the definition of standard assumptions should concentrate on future applications of solar roofs that are likely to be introduced to the market. It is assumed that solar roofs can only contribute a relevant emission reduction if the generated electricity, stored in an on-board battery, can be used for the operation of on-board electric devices. In order to assess the GHG emission potential of corresponding solar roof applications, the following parameters are of major relevance and need to be represented by the definition of adequate standard assumptions (see also section 2.1.2.3). The theoretical maximum output of photovoltaic (PV) panels under standard conditions is a technological feature which depends on the size and efficiency of the module which is given by the manufacturer. In order to determine the real-world efficiency of an automotive PV panel, a two-step approach is suggested. The mean annual output of a solar roof can be derived from global data on the average solar radiation. According to the approach presented in section 2.1.2.5, reliable data is available for all European Member States at different spatial resolution and could be used in order to define country-specific standard assumptions for theoretical solar roof efficiency; or even an aggregated value for the entire EU-27 that considers national variations of solar radiation and the national share within the European passenger car market. While the generated results consider the horizontal position of the panel and losses of the electric system, further losses that are related to shading effects are not included. Therefore, in a second step, assumptions on the average shading of mobile solar roofs have to be made in order to determine the average real-world energy output. As illustrated in section 2.1.2.3, the shading of solar roofs can be caused by many different factors (see also Table 2.5) and lead to various effects on the panel’s efficiency. Due to this new kind of mobile PV module application, no empirical data on their use and average degree of shading are available. Current approaches are therefore based on estimations that encompass great uncertainty. In order to improve the current practise, empirical data for a representative sample of vehicles / users would be required – a theoretical derivation of the average shading of solar roofs is considered to be of only limited reliability. According to vehicle lighting, the GHG emission benefit of solar roof applications is further dependent on assumptions on engine’s and alternator’s efficiency. Standard assumptions are likely to be defined for petrol and diesel cars (see efficient vehicle lighting). In contrast to vehicle lighting, the assumed annual mileage is of much greater importance. When defining standard assumptions, it should be considered that the GHG emission benefit per unit of distance decreased with increasing annual mileage. Therefore, it is crucial to consider variations of the annual mileage among vehicle classes when determining the effectiveness of solar roofs. Further efficiency losses that could be associated with the storage of electric energy (e.g. battery discharge losses) could be relevant, but reliable data is not available due to the early status of technological development. Effects of an increase of electric driving range and substitutable mileage with regard to future electric cars is not discussed in greater depth here. The definition of a productive approach would first require agreement on a procedure to determine emissions that are related to grid-electricity, which is beyond of the focus of this study. In summary, to improve the definition of standard assumptions and the assessment of solar roof applications, empirical data on the real-world use of solar roofs is required. Further, with regard to possible technological configurations, real-world measurement are essential in order to determine the efficiency gains (amount of fuel consumption reduction) that can be achieved by the use of on-board generated electricity on the vehicle-level under real-world conditions.

2.2.3 Exhaust heat recovery As illustrated in the previous sections, there is enough data available to derive first order standard assumptions on exhaust waste heat recovery technologies, in order to obtain first order


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assessment results on CO2 emission reduction potential. The determining factors for CO2 emission reduction potential that are described in paragraph 2.1.3.4 are:

- The amount of available exhaust (heat and kinetic) energy and exergy during average European driving.

- The exhaust waste heat recovery systems’ efficiencies (including the usage of the recovered energy)

- The driveline and engine efficiency penalties as a consequence of application of exhaust waste heat recovery systems

An overview of available data, further need of data and standard assumptions on the determining factors are given in Table 2.16 - 2.18. Supplementary to this overview, the following comments and standard assumptions regarding variations in the effectiveness of the investigated three exhaust waste heat recovery technologies can be made:

- In order to determine the feasibility of the different exhaust waste heat recovery technologies, standard assumptions on implementation costs should also be made

- Application of exhaust waste heat recovery technology might be more beneficial on petrol fuelled vehicles, compared to Diesel fuelled vehicles.

2.2.4 Overview of main factors determining CO2 reduction potential of eco-innovations, further need of data and standard assumptions

Table 2.16: Overview of main factors determining CO2 reduction potential of vehicle lighting, available and further need of data and potential approaches to derive standard assumptions

Factors determining CO2

reduction potential

Available data Further need of data Standard assumptions

Technical configuration & efficiency of vehicle lighting

Information from vehicle and lighting equipment manufacturers on applied lighting technologies

Real-world efficiency of innovative vehicle lighting (e.g. LED for headlamps)

Assumptions on configuration and efficiency can be derived for different vehicle classes

Use of vehicle lighting

Non-representative data on operation hours of different types of vehicle lighting

Empirical representative data for different EU member states

Only average assumptions based on little and non-representative data without any spatial differentiation


Average efficiency of alternator and marginal engine efficiency (petrol & diesel)

Data (information from OEM) on average alternator and marginal engine of specific passenger car in order to determine fuel / emission reduction potential

Annual vehicle mileage of different vehicle classes for EU member states

Standard assumption on country-specific annual mileage per vehicle class in order to quantify distance-based emission reduction


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Table 2.17: Overview of main factors determining CO2 reduction potential of solar roof application, available and further need of data and potential approaches to derive standard assumptions


reduction potential


Technical configuration & efficiency of solar roof application

Information on current low performance solar roof applications (technical specifications)

Information on future high performance solar roof applications, possible configurations (e.g. on-board storage of electricity) and related efficiency Information on the on-board electricity system and its ability to absorb the electricity produced

Assumptions have to rely on estimates of future applications and configuration of solar roofs and estimated system efficiency

Use of solar roof applications & real-world efficiency

Solar radiation and theoretical energy output of PV module at high spatial resolution

Standard assumptions on the theoretical maximum energy output of solar roof applications depending on location

Real-world efficiency of mobile solar roof applications, considering local shading and other limiting factors

Standard assumptions need to be made although they have to rely on rough estimates that are unlikely to be validated due to lack of empirical data


Average efficiency of alternator and marginal engine efficiency (petrol & diesel)

Data (information from OEM) on average alternator and marginal engine of specific passenger car in order to determine fuel / emission reduction potential

Annual vehicle mileage of different vehicle classes for EU Member States

Standard assumption on country-specific annual mileage per vehicle class in order to quantify distance-based emission reduction


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Table 2.18: Overview of main factors determining CO2 reduction potential of exhaust heat recovery technology, available and further need of data and potential approaches to derive standard assumptions


reduction potential


Amount of available exhaust (heat and kinetic) energy and exergy during average European driving

Databases with emission data of typical European driving (and thus data on average applied fuel energy and engine efficiency)

Exhaust temperature, pressure and flow data during typical European driving in order to determine exhaust gas energy and exergy. Exhaust temperature level differences between Diesel and petrol are part of this needed information. If the heat recovery system is coupled to the on-board electrical system, data on the electrical system and its capability to absorb / buffer the recovered energy.

A standard assumption on the drive cycle used to assess the CO2 reduction potential needs to be made. It is proposed to use the CADC cycle (Common Artemis Driving Cycle). Further standard assumptions need to be made for the ambient conditions during testing (temperature and humidity)

Exhaust waste heat recovery system efficiencies (incl. usage of recovered energy)

Rankine cycle efficiencies as a function of exhaust energy or as a function of exhaust temperature

Electrical Turbo-compound (ETC) efficiencies as a function of engine power

Electrical Turbo-compound efficiencies as a function of driving conditions, considering different engine types and turbocharger technologies

Standard assumptions on the typical on-board electricity demand, as this depends on what auxillaries are used (e.g. vehicle lighting, various electrical heating functions, HVAC, in-car entertainment) as well as how often they are used

Effect of the ETC motor, helping the turbocharger to accelerate, on drivability and CO2 emission reduction

Thermoelectric generator efficiencies as a function of temperature and applied thermoelectric material specifications + the specifications of currently applied thermoelectric material

Specification of applied thermoelectric materials in the nearby future, because the positive effect on efficiency will be significant


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Efficiencies of storage of electrical energy and conversion to kinetic energy

Information of extra efficiency benefits and penalties of application of the technologies on a hybrid powertrain

Driveline and engine efficiency penalties as a consequence of application of exhaust waste heat recovery systems

CO2 emission and fuel consumption penalties as a function of increased exhaust backpressure

Effects of the different technologies on exhaust backpressure

Information on increasing vehicle mass, due to exhaust heat recovery technology application, and it’s effect on CO2 emission


58 AEA

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