28-136Fuel Saving of an Automobile Using Fuzzy Logic

5/23/2018 28-136Fuel Saving of an Automobile Using Fuzzy Logic

2014 IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT)

ISBN No. 978-1-4799-3914-5/14/$31.00 2014 IEEE 136

Fuel Saving of an Automobile Using Fuzzy LogicBased Embedded Controller

M. D. Baldania1, D. A. Sawant2, A. B. Patki31,2,3Department of Electronics & Telecommunications, COEP

[email protected]

1

,[email protected]

2

,[email protected]

3

Abstract In the last two decades, in the transportation sector,

use of air conditioner in buses, cars, trains and aviation

industry increased rapidly. Further, with the growth inagriculture sector towards food processing industry, includingstorage plants which need high capacity refrigeration plants

for storage, preservation and transportation of end products,

use of an air-conditioner or refrigeration is increased. As fuelconsumption is the only available energy in transportation for

mobile air conditioner, reduction of fuel consumption hasdirect positive effect in improving fuel consumption efficiency,

reducing pollution and saving economy. So far as moving

vehicles are concerned, the air conditioner (passenger based

transportation) or refrigeration (preservation of different fooditems during transportation) units are in the form of pay-loads

carried on vehicles. Thus, the primary objective istransportation, while luxury, comfort and preservation are the

secondary considerations. In this context, the availability of

embedded processor based electronic modules installed in air

conditioner or refrigeration units is the technological need. In

order to realize such embedded systems, the associatedelectronic hardware has to have built-in features for energysaving. The emphasis at the technical specification (including

tender document requirement) for incorporating these energysaving modules does not appear specifically since most of the

times, these units do not support the hardware features forenergy saving. This paper brings out fuzzy logic based

approaches for energy saving in the design and

implementation of electronic hardware systems for air

conditioner units.This paper proposes an off-the shelf methodfor making air conditioner units more energy efficient, which

reduces fuel consumed by mobile air conditioner facility

available in different transportation vehicles. Reduction in fuelconsumption has direct impact on the environment which isvery unique thing while addressing issues in the renewable and

non-renewable energy sectors. The electronic hardware

implementation is carried out using Xilinx ISE Design Suite14.2 with Verilog-HDL.

Keywords Air conditioner; Compressor; Energy saving; Fuzzy

logic; Embedded electronic systems; Verilog-HDL; Xilinx.

I. INTRODUCTIONIn 1902, Willis Haviland developed the first modern air-

conditioner to solve the humidity problem in an industry and

gave a birth to a new technology. In a very short time, airconditioner started popping up at different public places toachieve comfort level in temperature and became integralpart of almost every institution.

HAVC (Heating, Ventilation and Air-conditioning)systems are developed, which is an extended version of a

simple air-conditioner, to get better control of anenvironment, which led to the wide use of an air-conditionernot only in industry but also at business and commercialplaces, storage plants and storage vehicles, automobileindustry, home applications, aviation and train. Because ofthat power consumption became one of the very importantfactors to take into consideration. Different researches arecarried out every year to get better and efficient performancewith as much as possible energy saving of an air-conditionerwhile maintaining comfort level.

The use of an air-conditioner can increase the fuel

consumption as much as 20% in the automobile as it adds itsown weight to the vehicle and draws power from the enginewhich affects the fuel efficiency. As passenger requires morecooling, the air-conditioner consumes more fuel and affectsthe vehicle performance also [1].

Fuzzy logic is capable of simulating operators behaviourinto mathematics i.e., transferring human knowledge andexpertise into mathematical model with the help of if-thenrules [2, 3]. While designing an energy efficient model of anair-conditioner, it behaves as multi-input and multi-outputnon-linear system. Normally PID (Proportional, Integral andDerivative) controllers are used in real time applications forair-conditioner which gives better performance when thesystem is a linear system. As fuzzy logic has the potential to

deal with non-linear problems with better performanceguaranteed [4, 5, 6, 7], it gives more stable and efficientoutput as compare to PID controller which is proved basedon researches carried out in past [8, 9, 10, 11, 12, 13, 14, 15,16].

Fuzzy Logic Controller (FLC) is available for differentapplications. Normally, off the-shelf approach is followedfor FLCs design. So, at the outset, one gets an impressionthat such off-the shelf FPGA controller can be used with rulebase modification anywhere as application varies. Howeverthis, off-the shelf approach is not suitable in view of theinherent characteristics of air-conditioners installed in avehicle.

This paper proposes a methodology to control an air-

conditioner of an automobile with taking engine load intoconsideration because air-conditioner compressor takesrequired energy from a vehicle engine, which finally leads tothe fuel consumption. Hybrid vehicle approach is suggestedi.e., engine heat can used in cold or winter conditions towarm the vehicle, which is very efficient and fuel saving



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approach. The whole system is designed based on a prioritylevel i.e., considering engine load, battery load, atmosphericconditions etc.

This paper is divided into three different modules. Section2 discusses energy consumption related blocks of an air-conditioner where power can be saved. Section 3 explainsmethodology to develop electronic hardware to save energyconsumption by an air conditioner based on fuzzy logicusing Verilog-HDL (Hardware Description Language) and

Matlab.II. ENERGYSAVINGBLOCKSOF ANAIR

CONDITIONER

The automotive air-conditioner must be capable of doingfour basic things:

1. Must cool the air.2. Must circulate the air.3. Must purify the air.4. Must dehumidify the air.There are different kinds of units in an air-conditioner

which can be controlled to save energy consumption. Out ofthem, compressor is the one which consumes more energy.

When the module is mobile or portable (car, truck, buses,etc. in automotive industry.), compressor uses power of anengine to work. By controlling the pressure parameter ofrefrigeration into a pipe, compressor generates hot and coldenvironment in pipes. This paper proposes a method to runcompressor at a various speed with respect to its maximum% efficiency. The Delphi (Harrison) V5 compressors arevariable stroke or variable displacement compressor andother companies have also developed variable speedcompressor which can be useful in FLC system design.

Expansion valve is another main block which controlspressure of an air-conditioner and has a significant role incooling cycle. Fan located near evaporator and condenser isused to circulate air inside and outside of the room and can

be saved significant amount of energy with faster response ifcontrolled properly. While controlling pressure parameter,freezing of a refrigerant must be avoided otherwise damageto the component will occur.

Humidity controlling is one of the very important factorsof an air-conditioner. In dehumidification, chilled air ispassed through the hot side of heat exchanger which can beachieved without any change in output temperature. Theaverage person feels comfortable when the temperature isbetween 21C to 26C, with a relative humidity between45% to 50% [17]. Conventional air-conditioners are capableto control humidity automatically. Different kind ofresearches were carried out in past to control humidityaccording to user preference [18, 19, 20], but it has a demerit

of more energy consumption and thus reducing efficiency.Therefore, authors have left humidity controlling operationon the automated feature of an air conditioner.

III. FUZZY LOGIC BASED IMPLEMENTATIONAs concluded previous sections and proved from different

researches, air-conditioner is a non-linear system as it hasmore number of input parameters which haveinterdependency on different output parameters. FuzzyExpert System (FES) is especially capable to deal with non-linear and uncertain systems whose mathematical behaviouris unknown because of its complexity [21, 22, 23, 24, 25,

26].Figure 1 shows the basic block diagram of a fuzzy logic

controller. The outputs from all sensors are input to the FLC.Fuzzification is the first step in which all inputs arecategorized based on its value. First of all, the input to anFLC is converted into Hexadecimal format and membershipvalue is assigned to it based on its value.

The authors have followed a unique approach in whichevery calculation inside a controller is performed andprocessed into hexadecimal format. Please refer to reference[27] for more information about FLC controllerimplementation in Xilinx ISE Design Suite 14.2 usingVerilog-HDL coding language.

Fig. 1. Fuzzy Control System [21].

In our implementation, current temperature of the room,difference between the current room temperature and user settemperature which can be positive of negative to switch ONair-conditioner or heater (finally both are in-builtfunctionality of an air-conditioner), load on the engine aretaken as inputs to the FLC.

As previously mentioned, compressor is the main unit inan air-conditioner which uses significant amount of energyand it draws required energy from engine i.e., belt isconnected via a pulley to the engine. Transportation is themain priority in an auto-mobile as compare to air-conditioner, so there is a need to design an electronicembedded system which is capable to take decisions basedon engine load. The vehicle may be climbing up the hill,moving freely at higher speed on a highway or climbingdown the road, the load on the engine varies. The authorshave taken engine load into consideration to make a system



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which is capable to take decision based on priority by itsown to get better performance. Inputs are divided intodifferent ranges and different linguistic variables areassigned to them with detailed research data and expertiseknowledge. Table 1 shows the current temperature andtemperature difference range division and linguistic variablesassignment. Please refer reference [28] to get detailedclassification and range division information for every inputand output variables.

Authors have divided temperature difference input intotwo basic categories i.e., whether heater should be turnedON or cooler should be turned ON. In table 1,PVerySmallstands for Positive temperature difference Very Small andNVerySmall stands for Negative temperature differenceVery Small. As nowadays, HAVC systems are capable to actas a heater or cooler, this type of system implementation is avery unique approach to save space and energy byintegrating two different functionalities into one unit.

After dividing different inputs into different linguisticvariables, the next step is to design Rule Base which is theheart of the FLC. Design of a rule base is one of the veryimportant tasks and requires deep and expertise knowledgeof a system under design [22].

Table 1. Temperature and temperature difference linguistic variablesassignment.

CurrentTemp.LinguisticVariables

Current Temp.RangeDivision(C)

Temp.DifferenceLinguisticVariables

Temp.DifferenceRangeDivision(C)

VeryLow Less than 13 PVerySmall Less than 2

Low 12 to 20 PSmall 1 to 3

Medium 19 to 27 PNormal 2 to 4

High 26 to 36 PMuch 3 to 7

VeryHigh More than 35 PVeryMuch More than 6

NVerySmall Less than 2

NSmall 1 to 3

NNormal 2 to 4

NMuch 3 to 7NVeryMuch More than 6

Stability is one of the important criteria while designingany system and whole system performance parameters aredependent of stability factor. As closed loop system are morestable in performance as compare to open loop systemswhich is achieved in fuzzy logic by different rule connectorslike AND, OR, NOT. As the number of input parameterincreases, the number of rules also increases and rule basedesign task gets very complicated because of parameterdependency

Before defining rule table, output range parameters of thesystem is also defined in Matlab implementation. Here, the

output variables are compressor speed, expansion valve andfan speed and air-conditioner mode i.e., heater or cooler.Output variables are also divided into different ranges anddifferent linguistic variables are assigned to them based onexpertise knowledge. All output variables are considered into% efficiency form as compared to its maximum capacity.Figure 2 is the compressor speed range division in %

efficiency of X-axis with different linguistic hedgesassignment.

Rule table is the one which contains combinations of allpossible inputs and based on those combinations what shouldbe the output. As defined previously, current temperatureinput is divided into 5 different linguistic hedges,temperature difference is divided into 10 different linguistichedges and engine load is divided into 3 different linguistichedges which gives total 150 different rule combinations and

based on that 4 different outputs i.e., compressor speed (%),fan speed (%), expansion valve open condition (%) and air-conditioner mode are decided.

Authors have taken care of proper effect ofthermodynamics second law i.e., heat flow rate and based onthat the rules are designed. For instance, consider this rule:

IFtemperature is VeryHigh ANDtemperature difference is

PVeryMuch AND engine load is Low THEN fan speed is

Fast, compressor output is VeryHigh (i.e., higher

compression), Expansion valve is Almost Close, cooler is

ON.

Fig. 2. Compressor Speed (%) is divided into different linguistic hedges(generated in Matlab 2013).

Above stated rule defines the proper decision makingcondition to achieve cooling comfort at faster rate with lesserpower consumptions i.e., running compressor and fan atmore than 80% capacity rather than running it at lower speedfor more time and wasting energy which is completely basedon heat transfer logic i.e., 2ndlaw of the thermodynamics. Itis worth to mention that final decisions are taken based onoutputs from the rule table.

Defuzzification is the last block of an FLC where finaloutputs of a controller, which are fuzzy in nature, areconverted into crisp or non-fuzzy form to perform requiredactions. Different kind of defuzzification methods are used,like center-of-gravity (COG), MIN-MAX defuzzification etc.and among them, COG is the most widely used method inpractice because of its more stability and higher accuracy.

Different output variables are also used to calculate finaloutput of the defuzzification block which is explained indetail in [27]. Figure 3 is the SurfView plot of the



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compressor speed (%) output, which is generated usingMatlab, signifies the maximum performance of the airconditioner with full-filling its energy saving goal.

Similarly, SurfView plot for the expansion valve (%) andfan speed (%) can be generated. Figure 4 shows the ISimgenerated waveform diagram with input temperature 70H (Hstands for Hexadecimal form) and input temperaturedifference is 6CH and calculated outputs are as follows at thetime when inputs are applied to the controller: compressor

speed (%) is 92H, expansion valve (%) is AEH and fanspeed (%) is 8CH.

The simulator generated output are same as theoreticallycalculated outputs which ensures that generated hardware inXilinx 14.2 using Verilog-HDL is functioning correctly. Forfurther information of how to develop hardware in Xilinx14.2 using Verilog-HDL, refer [27].

The controller is designed in Xilinx 14.2 withsynthesized results and with the help of simulationswaveform; the final output is cross-checked which matcheswith the theoretical calculations.

Fig. 3. SurfView plot of the Compressor Speed (%) output.

IV. CONCLUSION:The fuzzy logic controller gives fast response as

compare to normal air conditioning systems with reachingsteady state position as soon as possible. The overallresponse of an FLC system is 1.6 times faster than the PIDcontroller which is highly dependent on how rule base iscreated. Variable speed of compressor, expansion valve andfan speed gives better results with better fuel saving and at

the same time, with better cooling effect with faster responseand efficiency.

ACKNOWLEDGEMENTS:

The authors would like to thank to the Departmentof Electronics and Telecommunication Engineering, COEPfor their infrastructure and lab facility and in particular Prof.(Mrs.) Vanita Agarwal for her help and support.

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Fig. 4. ISim generated waveform for air-conditioner inputs and outputs in Xilinx 14.2 Design Suite.

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28-136Fuel Saving of an Automobile Using Fuzzy Logic