co2.ppt

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

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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

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12

<1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15+

Age of Automobiles (years)

Per

cen

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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

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SI_

base

line

SI_

PN

GV

CI_

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Insi

ght_

SI_

PN

GV

Insi

ght_

CI_

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GV

Insi

ght_

SI_

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Insi

ght_

CI_

PN

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Priu

s_S

I_P

NG

V

Priu

s_C

I_P

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Fue

l Cel

l_P

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cept

_PN

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alle

l_50

_PN

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1_P

NG

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SU

V

mp

g

Simulation Results – Vehicle MassVehicle Mass

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SI_

ba

selin

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ralle

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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

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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