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Reducing the Global Warming Impact of the Passenger Vehicle
Fleet
Harriet Gu
Jason Martz
Sara Soderstrom
Global Warming Reduction via Greening the Automotive Powertrain
Objective:
To evaluate the impact of passenger vehicles on the feasibility of achieving the Kyoto Protocol
standards for CO2 emission reductions
• Engineering Design– Relate fuel efficiency to carbon dioxide production
• Policy Development– Relate fleet composition to total carbon dioxide
production
Global Warming
Figure from www.epa.gov/globalwarming
Radiative Forcings
Fraction of total radiative forcing contributedby individual GHGs since 1850
CO264%
CH419%
HC's11%
N2O6%
Data from ME 599 coursenotes
U.S. Greenhouse Gas Emissions
Figure from www.epa.gov/globalwarming
Kyoto Protocol
• Agreement negotiated among 160 industrialized nations
• Establishes binding greenhouse gas emission reductions
• Target achievement between 2008 and 2012• United States
– 7% below 1990 emissions– Currently 10% above 1990 levels!– Under current growth 33% greater than 1990 levels
Challenges to Kyoto Protocol• Can targets be met?
– American Council for Energy-Efficiency Economy • Proactive sector involvement • Increased R&D efforts • Strengthened state programs and policies• Focused effort to develop and transform markets for low-
carbon energy options
– American Society of Mechanical Engineers
• Can sinks (trees, agriculture, etc.) be counted? – Reduces U.S. emission decreases to 3-4% below 1990
levels
• Can tradeable permits be used?
Transportation Fleet
• 18% of CO2 emissions are from cars, SUVs, and passenger trucks
• 201 million vehicles in 1997
• 1.1% vehicle growth/year
• 64% automobiles, 36% SUVs & trucks
• CAFE automobile standards = 24 mpg
Transportation Ownership and Usage
• 18.5% of household expenses for transportation (1997)• 17.3% of households have 3 or more vehicles (1990)• Average travel per vehicle per year = 11,800 miles• Average occupancy
– Automobile 1.6 persons– Pickup Truck 1.4 persons– SUV 1.7 persons– Van 2.1 persons
• 13.4% of workers carpool (1990)
Automobile Age Profile
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
<1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15+
Age of Automobiles (years)
Nu
mb
er o
f V
ehic
les
(th
ou
san
ds)
Average Vehicle Age = 8.7 years
Automobile Usage Profile
0
2
4
6
8
10
12
<1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15+
Age of Automobiles (years)
Per
cen
t o
f A
uto
mo
bile
Tra
vel
Current US Passenger Car Configuration• Engines oversized for performance
– Allow for high accelerations, but …– These performance requirements are not required for the
majority of the vehicle operation
• Large vehicle mass– Requires larger engine sizes to maintain performance
• Non-optimal vehicle drag coefficients– Vehicle experiences higher drag forces at a given speed
• High tire rolling resistance– Rolling losses due to friction in the tire as it flattens to
conform to the road
• Overall Effect: High vehicle fuel consumption
What Does This Mean?
• Lower fuel economy means more fuel is consumed to perform a desired task
• An increase in fuel consumption results in an increase CO2 production
• Fortunately, organized research is being conducted in order to increase vehicle fuel economy
PNGV• PNGV: Partnership for a New Generation
of Vehicles• Collaboration between the Federal Gov’t
and the Big Three• Goal is for each company to produce an 80
mpg family sized sedan concept vehicle by 2004, that has performance, safety and cost characteristics similar to today’s family sedans
PNGV Goals• Obtain 80 mpg goal by integrating the
following concepts into the auto:– Efficient fuel converters, such as fuel cells,
turbocharged direct injection diesels, hybrids– Better sizing of powertrain components– Lighterweight components– Bodies with lower drag coefficients– Tires with lower rolling resistances– Effect: Higher fuel economy
PNGV Performance ConstraintsAcceleration Time, 0-60 mph: 12.0 secAcceleration Time, 0-85 mph: 23.4 secAcceleration Time, 40-60 mph: 5.3 secMaximum Acceleration: 16 ft/s^2Distance In 5 Seconds: 135 ftGrade Target: 6%Cargo Capacity 136 kgTop Speed, Minimum 90 mph
Study Data Goals• Isolate the effects that powertrain components
have on vehicle fuel economy• Base study on components and fuels that are
available in the near future• Model the components in a PNGV type vehicle
• Maintain constant body and tire characteristics throughout the study, except for baseline vehicle case, which is representative of a contemporary passenger vehicle
• Study accomplished using Advisor, which allowed for easy substitution of powertrain components within a given vehicle configuration
Simulation InputsDrivetrain
File Name Configuration
SI_baseline Conventional
SI_PNGV Conventional
CI_PNGV Conventional
Fuel Cell_PNGV Fuel Cell
EV1_PNGV Electric
Insight_SI_PNGV Insight
Insight_SI_PNGV Insight
Insight_CI_PNGV Insight
Insight_CI_PNGV Insight
Precept_PNGV Parallel
Parallel_50_PNGV Parallel
Prius_SI_PNGV Prius
Prius_CI_PNGV Prius
SUV SUV
Advisor• Forward/Backward vehicle simulation developed
by NREL• Available as freeware at www.ctts.nrel.gov• Capable of modeling conventional, fuel cell,
electric, and hybrid electric vehicles of all types• Allows designers and policy makers to search for
an optimal combination of powertrain components, or to simulate existing powertrain components for a given design objective
• Not an engineering design tool for individual components
Simulated Powertrain Component Characteristics
• Spark Ignition Engines– Low compression ratios, throttle intake manifold for
load control– Low thermal efficiencies compared to diesel engines.
• Diesel Engines– High compression ratios, vary equivalence ratio for
load control, no throttling– More efficient than Spark Ignition– Turbocharged– NOx and particulate emissions are relatively high
• Fuel Cell– Uses a fuel reformer to produce H2 from hydrocarbon
based fuels– Relatively high thermal efficiency at mid and high
loads– Output energy from the fuel cell is stored in a battery,
so the fuel cell can be used in its efficient load regimes– Battery powers a DC motor
• EV1– Electric vehicle– Stores energy obtained from the electric grid in
batteries, limited range– Batteries power an electric motor– No vehicle emissions, but emissions from powerplant
that produced the electricity for the vehicle
• Honda Insight– Hybrid electric vehicle: Starter/Alternator type– Uses a motor/generator in combination with an
IC engine. Motor generator used to load the engine to its efficient operating regime, or to suppliment the engine under high load conditions
– Smaller IC engines can be used as a result of the motor
– Energy for the motor is stored in batteries– Engine cannot be disconnected from the motor
gearbox, so both are always turning
• GM Precept– Parallel hybrid electric vehicle
– Similar to the Starter/Alternator HEV, except that the engine can be decoupled from the motor/generator
– Parallel 50 input is a slightly more hybridized parallel vehicle
• Toyota Prius– Similar to Parallel hybrid, except that the vehicle uses a
CVT transmission, and has a separate generator and motor
• SUV– Sports Utility Vehicle used to model trucks later in the
project, as a performance comparison to cars
Backward Facing Simulation• Assumes vehicle will meet a given speed trace without violating
the performance constraint inputs• Advisor contains two different optimization routines for the
selection of optimal component configurations• PNGV Performance Constraints were used for the comparison of
vehicles in the performance study• Powertrain components are sized according to the given
optimization objective and its constraints• The MatLab based bisection optimization routine for minimizing
component capacity (power) requirements was used, when necessary for this study
• Component performance data is contained in a series of lookup tables
• Performance data was obtained from steady state tests, conducted by private and public sources
• Component capacity is linearly scaled by the optimization routine to find an optimal solution
• This feature allows for the integration of optimally sized components, whose characteristics are based on one original parent component
• Components that were already close to the PNGV configuration were not optimized
• The performance of the vehicles was verified to be close to the PNGV vehicles, by running the vehicle through a single load step that outputs vehicle performance, which can be checked against PNGV constraints, in the Simulation Results Screen
Forward Facing Simulation
• Once the size of the powertrain components has been determined, the vehicle is run through a drive cycle to determine fuel economy and emissions
• Drive Cycles:– Combined City/Highway– SAE J1711 (for hybrid electric vehicles)
Advisor Vehicle Input Screen
Autosize Optimization Routine
Drive Cycle Selection
Simulation Results Screen
Simulation Results – Fuel EconomyVehicle Fuel Economy
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
SI_
base
line
SI_
PN
GV
CI_
PN
GV
Insi
ght_
SI_
PN
GV
Insi
ght_
CI_
PN
GV
Insi
ght_
SI_
PN
GV
Insi
ght_
CI_
PN
GV
Priu
s_S
I_P
NG
V
Priu
s_C
I_P
NG
V
Fue
l Cel
l_P
NG
V
Pre
cept
_PN
GV
Par
alle
l_50
_PN
GV
EV
1_P
NG
V
SU
V
mp
g
Simulation Results – Vehicle MassVehicle Mass
0
500
1000
1500
2000
2500
SI_
ba
selin
e
SI_
PN
GV
CI_
PN
GV
Fu
el C
ell_
PN
GV
EV
1_
PN
GV
Insi
gh
t_S
I_P
NG
V
Insi
gh
t_S
I_P
NG
V
Insi
gh
t_C
I_P
NG
V
Insi
gh
t_C
I_P
NG
V
Pre
cep
t_P
NG
V
Pa
ralle
l_5
0_
PN
GV
Pri
us_
SI_
PN
GV
Pri
us_
CI_
PN
GV
SU
V
kg
Fuel Economy CO2 Production
gallonmiles
EconomyFuel
CgCOg
RatioMassCarbonfuelgCg
ContentCarbongallon
fuelgDensityFuel
.
_2_
.._
_.
_.
Note: For electric vehicle, fuel efficieny is multiplied by 0.32, the efficiency of the electrical distribution grid.
CO2 Production Levels
0
50
100
150
200
250
300
350
400
450
CAFE sta
ndar
d
SI_ba
selin
e
SI_PNG
V
CI_PNG
V
Insig
ht_SI_
PNGV
Insig
ht_CI_
PNGV
Insig
ht_SI_
PNGV
Insig
ht_CI_
PNGV
Prius_
SI_PNG
V
Prius_
CI_PNGV
Fuel C
ell_
PNGV
Prece
pt_P
NGV
Parall
el_5
0_PNGV
EV1_PNGV
SUV
Ca
rbo
n D
iox
ide
Pro
du
cti
on
(g
/mile
)
Fleet Characterization
• Predicted miles traveled by automobiles in 2012
1519972012 _1.#..#. RateGrowthMilesAutoMilesAuto
• Determination of 1990 CO2 production by automobiles
CarsFractionGasFraction
tionTransportaFractionCOCO TotalsAutomobile
..
._1990_1990 22
Fleet ProjectionsNumber of Autos: 124673000 1997Number of Miles: 1.50182E+12with growth (2012): 1.82289E+12fraction cars 0.6384974211990 CO2 from cars 568.1311743 million metric tons CO2 1990 CO2 4943.3 million metric tons
Name Fuel Economy CO2 (g/mile) Avg. CO2 2000 2001 2012
CO2 baseline 24 mpg 359 359 1 0.99 0.25SI_PNGV 44.5 mpg 193.0 193.0 0.005 0.3CI_PNGV 54.7 mpgge 186.4 186.4 0.005 0.1Insight_SI_PNGV 56.3 mpgge 151.8Insight_CI_PNGV 62.0 mpgge 139.8Insight_SI_PNGV 54.5 mpgge 155.5 147.7 0.1Insight_CI_PNGV 60.5 mpgge 143.7Prius_SI_PNGV 57.7 mpg 146.9 142.4 0.1Prius_CI_PNGV 63.2 mpgge 138.0Fuel Cell_PNGV 63.6 mpgge 137.3 137.3 0.05Precept_PNGV 59.5 mpgge 146.5Parallel_50_PNGV 64.6 mpgge 135.1 140.8 0.07EV1_PNGV 152.4 mpgge 176.2 176.2 0.03
CO2 production/avg. vehicle 359 357.3067 217.3033
percentage of vehicle travel: 20% 5% 6% Total:CO2/year 1.28E+14 3.06E+13 2.42E+13 5.59E+14 g CO2/yr
558.6546 million metric tonnes1.7% reduction
Predicted New Sales
Effect of Future Fleet on CO2 Emissions
-100.0%
-80.0%
-60.0%
-40.0%
-20.0%
0.0%
20.0%
No Change
Moderate Change
Significant Change
Auto
Truck
Total
4.4% reduction
Policy Requirements
• Increase CAFE standards– Automobiles ~57 mpgge– Trucks ~48 mpgge
• New standards effective 2009
Policy Feasibility
• Knowledge/understanding of consequences of global warming– Political and corporate acceptance– Public awareness and consumer acceptance
• Oil/gasoline availability and cost
• Cost of new technology
• Similar vehicle performance
Model Uncertainties and Weaknesses• Advisor
– Use of available components in simulations• Use of “real” data• Data for most recent technology is not available
– Emission predictions are qualitative at best– Optimization routine linearly scaled components
• Heat transfer, friction don’t scale linearly!
– Based on steady-state data, not on dynamic performance
• Fleet characterization– Automotive, SUV, and truck growth and use rates assumed
constant – Vehicle age distribution assumed constant
Future Considerations
• Cost/benefit analysis for automotive changes versus energy consumer changes
• Effects of economic incentives for carpooling and mass transportation usage
• Cost analysis for mass transportation development and improvements– Mass transport currently takes 2x’s longer!
• Cost/effect of future technology
Conclusions• Kyoto Protocol is a good guideline for initially
decreasing CO2 emissions• Advisor is a useful tool for designers and policy-makers
to explore future vehicle designs• Model predictions
– Improved vehicle technology can lead to achievement of Kyoto Protocol standards
• Policy incentives are needed– CAFE standards: autos 57 mpgge, trucks 48 mpgge
• Multiple political, consumer, and technological issues will also affect implementation