TECHBRIEF

The Federal Highway Administration—in

collaboration with the Transportation

Research Board, the National Cooperative Highway Research Program, State

departments of transportation, and other

Federal agencies—has been investigating the effects of highway transportation

on air quality. These investigations have

primarily dealt with the evaluation of aircontaminant emissions produced by

motor vehicles at various speeds and

under various highway conditions. Dispersion of air-contaminant emissions in

various areas has been analyzed.

Highway agencies are also mandated to

evaluate whether mobile-source emissions conform to State implementation

plans and to make adjustments, as

required, to meet ambient air quality

standards.

Perspectives on Fuel 

Consumption and Air 

Contaminant Emission

Rates by Highway Vehicles

FHWA Contacts: Howard A. Jongedyk, HRDI, (202) 493-3077

Michael Savonis, HEPN, (202) 366-2080

Volpe National Transportation Systems Center: Gregg Fleming,

DTS-34, (617) 494-2372

Highway traffic operations, pavement conditions, and highway

designs affect rates of fuel consumption and air contaminant

exhaust emissions, as well as the types and numbers of highway

vehicles and the mileage driven by these vehicles. However, the

fuel consumption and emissions produced are not dependent

only on the vehicle mix and miles traveled.

This TechBrief summarizes the investigation, “Highway Effects

on Vehicle Performance,” undertaken at the Volpe National Transportation Systems Center. It refers to numerous other related

efforts. The report, Highway Effects on Vehicle Performance, Publication No. FHWA-RD-00-164, has been placed on the Federal

Highway Administration (FHWA) website (www.tfhrc.gov/hnr20/

00164.htm).

The main product of this study is a model, “Highway Effects on

Vehicle Performance” (HPP), a computer program that calculates

estimated fuel consumption and exhaust emission rates and the

amounts of each for a given highway segment for one or more

vehicles (traffic) as determined by the user for highway geometric

factors and idling or speeds, and accelerations (external loads,

also gears) and presents the results, including cumulative results,

in both pictorial and numerical forms. Hence, one can implement

the model to estimate the effects of highway geometry and pavement and/or traffic conditions. Essentially, the model combines

external loads from all sources, namely rolling resistance, aerodynamic drag, accelerations (inertia), grades, curves, and vehicle

idling with essentially engine/vehicle maps that provide the rates

of fuel consumption and air contaminant emissions for the condiResearch, Development, and

Technology

Turner-Fairbank Highway

Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

www.tfhrc.gov
tions of the external loads and

engine speeds and gears or vehicle idling, as appropriate. (Internal

energy losses for the vehicle could

be considered.) For most evaluations, a given warmed-up vehicle

is said to have external or road

loads for various speeds and

accelerations on a straight, flat,

smooth highway with no ambient

wind.

A CD-Rom has been prepared

that contains the following:

• Highway Effects on Vehicle

Performance, Publication

No. FHWA-RD-00-164.

• The program, “Highway

Effects on Vehicle Performance (HPP),” developed by

Klaubert, West, and Crowley.

(Questions may be addressed to Douglas Crowley,

(202) 493-3214, or M. West,

(617) 494-3417). Copies of

the CD-Rom have been given limited distribution. Requests for copies should be

addressed to the National

Technical Information Service (NTIS), Springfield, VA

22161.

The investigation, “Highway Effects on Vehicle Performance,”

included:

• Instrumenting four vehicles

to measure and record

propulsive demands, while

operating on highways with

appropriate geometric features, such as grades and

curves.

• Determining road loads for

three vehicles.

• Measuring three test vehicles’ fuel consumption rates

on a programmable largeroll chassis dynamometer

versus speed, load, and

transmission gears and

then developing databases

for the three vehicles, relating fuel consumption rates

to road loads at all speeds

and loads (for one of the

three vehicles, exhaust

emission rates were also

included).

• Testing the variability of driver performance for one of

the instrumented vehicles

in order to determine the

significance of driver variability on estimates of fuel

consumption and exhaust

emissions for a given speed

or set of conditions.

• Developing a single equation relating torque increase

on a curve to lateral acceleration relative to a straight

road for general application

to all automotive vehicles.

• Developing a method for

comparing the rolling resistance of pavement surfaces

using a vehicle of known

mass and aerodynamic drag

on pavement of a known

grade and curves using a

vehicle instrumented for

measurements of drive-shaft

torque and speed for small

time intervals or distances

such as 5 m.

• Demonstrating for one vehicle that the energy loss in

the drive axle and tires was

described as a loss in

torque or tractive force

expressed as a quadratic

function of only total drive

torque of tractive force, independent of speed as an

operative variable.

• Demonstrating a technique

using drive-shaft torque on

an instrumented vehicle to

very consistently determine

vehicle road load as a quadratic function of speed.

For the study, “Highway Effects

on Vehicle Performance,” there

were only four vehicles tested.

However, for these vehicles, load

measurements were made with a

large-roll dynamometer and by

drive-shaft torque measurements

to provide measurements on the

road. This study is only one of

numerous efforts to evaluate the

fuel consumption and exhaust

emission rates of carbon monoxide, nitrogen oxides, and hydrocarbons. In the event that the

measurements were made from

the foregoing emission rates and

carbon dioxide emission rates, the

fuel consumption rates could be

calculated by carbon balancing

and then converting the weights

of the carbon into gasoline

weights and volume of gasoline

(gallons).

The references listed below

also include discussions of vehicle

external loads and other factors

affecting fuel consumption and air

contaminant emission rates, testing of vehicles for external loads

versus emission and fuel use rates

and the use of modal models.

Modal models for one or more

vehicles give fuel consumption

and/or air contaminant emission

rates that are dependent on high-
way and pavement conditions and

modes of operation of vehicles,

such as idling, acceleration, cruising at a constant speed, and deceleration, and vehicle characteristics, such as engine maps. An

example of modal models include

the HPP model in the study,

“Highway Effects on Vehicle Performance,” and modifications for

traffic models. There are also

numerous effects of highway

pavement surfaces and other factors on rolling resistance, driver

performance, and aerodynamic

drag (which includes the effects of

air density and direction velocities

and the wind gusts (for example,

colder air has a higher specific

weight and, thus, more drag due

to the higher density of cold air).

The modal models are superior

to the MOBILE models. MOBILE

models have been developed and

mandated by the Environmental

Protection Agency (EPA) to generate air contaminant emission rates

versus speeds based on sample

test data and an area’s vehicle

road network and vehicle fleet,

and whether an area has put certain policies in place, such as

required inspection and maintenance. Based on precisely defined

emission rates for various speeds

and vehicle-miles traveled in that

area, the gross air contaminant

emission rates are estimated.

MOBILE models neither do justice

to areawide air pollution problems, except to make gross estimates since they do not adequately consider the fate of exhaust air

contaminants, nor do they adequately address small project

areas. The MOBILE models do not

consider the grades or curves of

highways or the effects of pavement conditions. Nonetheless,

they have been mandated by regulations as tools in evaluations as to

whether highway emissions conform to an area’s quotas for motor

vehicle emissions given in a State

Implementation Plan (SIP).

MOBILE model usage puts a heavy

emphasis on an area’s vehicle mix

and miles traveled. They offer no

significant assistance in evaluations of the effects of pavements,

highway design features such as

grades and curves, or changes in

traffic flow (amount of idling and

acceleration as opposed to more

constant speeds). Several reference listed (for example, see Russell) discuss the merits of modal

models in contrast to the mandated MOBILE models (EMFAC models are California versions of

MOBILE models.)

Simulation models, as defined

more completely in the references, have been developed to

estimate vehicle performance or

fuel consumption and/or air contaminant emission rates based on

external loads and relevant engine

and vehicle component parts and

their responses or “maps” for

existing untested or as yet unbuilt

conceivable vehicles.

VEHSIM was one of the first

simulation models. (Contact H.

Gould, Volpe National Transportation Systems Center, Cambridge,

MA, (617) 494-2134.) It is referred

to in Publication No. FHWA-RD-00-

164 as offering a means of synthesizing data for the HPP model for

unmeasured vehicles. VEHSIM

and numerous subsequent models have been calibrated using

appropriate validation tests (measurements of fuel consumption or

emission rates versus model estimates) for sample vehicles.

Since 1995, the leading simulation model developed, validated,

and widely used is ADVISOR,

which was developed by the

National Renewable Energy Laboratory of Golden, Colorado (Wipke). It is used by more than 2,000

users worldwide. It has the capability to model conventional,

hybrid, or electrical vehicles for

fuel consumption and air contaminant emission rates. It has been

checked for fuel consumption and

air contaminant emission rates for

selected vehicles. This model not

only can make estimations of current vehicles that may not have

had actual measurements, but

also can be used to make estimations of unbuilt vehicles being

conceived and designed (www.

ctts.nrel.gov/analysis/advisor_doc/

advisor_ch1.htm).

Present Action

Use modal models with the

available data on fuel consumption and air contaminant emission

rates related to external loads for

one or more vehicles where the

external loads can be evaluated

from road conditions, aerodynamic drag, grade, curves, speeds, and

accelerations. Such data can be

obtained from measurements on

the vehicles or similar vehicles.

Use a simulation model such as

ADVISOR to make estimations of

vehicle performances where there

are no data or when projections

for future vehicles are desired

(vehicle mix estimations to represent traffic).
Future Prospects

With the expected improvements in vehicle performance

with regard to fuel consumption

and air contaminant emission

rates, it is expected that the

impacts of highway vehicles on

fuel consumption and air pollution

will gradually be reduced, assuming no significant changes in vehicle operations or increases in

vehicle-miles traveled.

Several sources of such improvement include:

• Improved tires to provide

lower rolling resistance.

• Reduction of energy losses

during braking by using

electrical systems for regenerative braking.

• Reduced internal combustion engine operations during idling.

• Pre-warmed vehicles to

reduce cold-start emissions

from engines and to make

the catalytic converter more

useful and improve the fuel

economy using storage of

energy at least for a time of 2

to 3 days (high-temperature

energy or increased electric

energy battery storage).

• There can also be improvements in fuel consumption

and air contaminant emission rates by better pavement design and management, bare (snow-free/icefree) pavements, and dry

pavements, and improved

highway design by optimizing grades and curves and

wind exposures, and decreasing irregular speeds,

accelerations, and decelerations as opposed to more

constant speeds by traffic or

highway management (Intelligent Transportation Systems).

References

General:

Austin, T.C.; Dulla, R.G.; and

DiGenova, F.J. Design and Operation of an Instrumented Chase Car

for Characterizing the Driving Patterns of Light-Duty Vehicles in

Customer Service, Sierra Research EPA Report SR92-02-01.

Developed means to measure

grade by moving vehicle; evaluations of traffic speed variations.

Bauer-Bosch. Automotive Handbook, Stuttgart, Germany, 1996,

pp. 326-340. Society of Automotive

Engineers, Warrendale, PA. Describes external load as grades,

curves, rolling resistance, aerodynamic drag, and inertia (acceleration).

Cadle, S.H.; Carlock, M.; Cullen,

K.; Gorse, R.A.; Knapp, K.T.; and

Lawson, D.R. “Real-World Vehicle

Emissions: A Summary of the

Fourth Annual CRC-APRAC OnRoad Vehicle Emissions Workshop, Air and Waste,” Journal of

the Air and Waste Management

Association, Vol. 44, 1994, p. 1180.

Removal of “clunker” cars, effects

of varied drivers, effects off-grade,

driving patterns (cycles) evaluated, etc.

Evans, L. “Driver Behavior

Effects on Fuel Consumption in

Urban Driving,” Human Factors,

21(4), 1979.

U.S. Department of Energy/

U.S. Environmental Protection

Agency. Energy Technology and

Fuel Economy (http://www.fueleconomy.gov/feg/atv.shtml). Illustrates the typical loss of energy in

urban driving.

Laboratory and field testing

of vehicles for modal 

and other models (load vs. 

fuel consumption and 

emission rates):

Barth, M., et al. Development of

a Comprehensive Modal Emissions Model, University of California at Riverside. In press. The report includes a CD-Rom with an

extensive database of measurements of air contaminant emissions on a dynamometer. Contact

R. McCready, Transportation Research Board, (202) 334-3224.

Lenner, Magnus. “Measurement

by On-Board Apparatus of Passenger Car’s Real-World Exhaust Emissions and Fuel Consumption,”

Swedish National Road and Transport Research Institute, Linkoping,

Sweden, 1995, 24 pp. Both field

and dynamometer testing for fuel

consumption and exhaust emissions on level, straight highway are

included.

McGill, R. “Fuel Consumption

and Emission Values for Traffic

Models,” Publication No. FHWA/

RD-85/053, 1985, 90 pp. Development of fuel consumption and

emission maps for 15 passenger

cars.

West, B.H.; McGill, R.N.; and

Sluder, S. Development and Validation of Light-Duty Vehicle Modal

Emissions and Fuel Consumption
Values for Traffic Models, Publication No. FHWA-RD-99-068, 1999.

Eight vehicles (five cars, three lightduty trucks). Field and dynamometer testing for emissions and

fuel consumption at different

speeds and accelerations.

Younglove, T.; Barth, M.; Scora,

G.; and An, F. “Prediction of Future

Vehicle Emissions by Modification

of Physical Parameters,” 10th CRC

On-Road Vehicle Emissions Workshop, San Diego, CA, University of

California at Riverside, March 27-

29, 2000.

Discussions about MOBILE

and other models:

Akcelik, R., et al. Progress in

Fuel Consumption Modeling for

Urban Traffic Management, Research Report ARR No. 124, Australian Road Research Board, Victoria, 1983. Mainly deals with the

effects of traffic variations and

combinations of idling, various

speeds, acceleration, etc.

Hallmark, S.; Fomunung, I.;

Guensler, R.; and Bachman, W.

“Assessing Impacts of Improved

Signal Timing as a Transportation

Control Measure Using an Activity-Specific Modeling Approach,”

Journal of the Transportation

Research Board, 1738, 2000, pp.

49-55.

Russell, A., et al. “Technical

Issues Associated With the

MOBILE Model.” Committee to

Review EPA’s Mobile Source Emissions Factor Model, Board on

Environmental Studies and Toxicology, TRB, NRC, Washington,

DC, 2000, National Academy Press

(http://www.nap.edu/books/

0309070880/html/index.html).

Rolling resistance:

Claffey, P.J. Running Costs of

Motor Vehicles as Affected by

Road Design and Traffic, NCHRP

Report 111, Highway Research

Board, National Academy of Sciences, Washington, D.C., 1971.

Numerous factors, including air

temperature, road roughness, altitude, grade, etc., affecting fuel

consumption rates.

Constantino, D.M.; Law, D.A.;

and Ungerer, R.P. The Quantitative

Effect of Rough Pavement on

Motor Fuel Consumption, Engineering Research and Development Bureau, NY State DOT,

Albany, New York, 1984. Rough

roads having approximately 20 to

30% higher rates of fuel consumption (increased rolling resistance,

especially at 20 to 50 mi/h).

De Raad, L.W. The Influence of

Road Surface Texture on Tire

Rolling Resistance, Society of

Automotive Engineers, 1978.

Leasure, W.A. “Variations in

Truck Tire Rolling Resistance and

Its Effect on Fuel Economy,”

National Highway Traffic Safety

Administration, 1979. Variables

affecting tire rolling resistance.

Mitchell, T. WesTrack—Track

Roughness, Fuel Consumption,

and Maintenance Costs. TechBrief

available at www.tfhrc.gov. TechBrief reports on the decrease of

rolling resistance and fuel consumption rates after pavement

rehabilitation.

Schuring, D.J. “The Rolling

Loss of Pneumatic Tires,” Rubber

Chemistry and Technology, Vol.

153-9475, July-August, 1980, Rubber Division of the American

Chemical Society, Inc., pp. 601-

727. Variations of rolling resistance by speed, loads, ambient

temperature, rubber type, tire size,

road, texture, presence of water

and snow on pavement, tread

geometry, tire reinforcement, etc.

Very significant paper indicating

the benefits of proper tires, tire

inflation, smooth pavements, and

dry (snow-/ice-free) pavements.

Taylor, T., and Clark, S.K.

“Effect of Automobile Tire Pressure Changes on Fuel Economy,”

Corporate-Tech Planning, Inc.,

Waltham, MA, 1980. Tire type and

temperature (warm-up period

lengths) also affect rolling resistance.

Zaniewski, J.P.; Butler, B.C.;

Cunningham, G.; Elkins, G.E.; Paggi, M.S.; and Machemehl, R. Vehicle Operating Costs, Fuel Consumption, and Pavement Type

and Condition Factors, Publication No. FHWA-PL-82-001, 1982.

Simulation models:

Brooker, A.; Hendricks, T.; Johnson, V.; Kelly, K.; Markel, T.;

O’Keefe, M.; Sprik, S.; and Wipke,

K. ADVISOR 3.1 Documentation

(http://www.ctts.nrel.gov/analysis/advisor_doc/advisor_ch1.htm).

Buck, R.E. A Computer Program (HEVSIM) for Heavy-Duty

Vehicle Fuel Economy and Performance Simulation, Vol. I: Description and Analysis, Report No.

DOT-HS-805-910/UMTA-MA-06-

0119-81-1, U.S. Department of

Transportation/Urban Mass Transportation Administration, 1981.
Gould, H.H., and Milliaris, A.C.

Highway Fuel Consumption Computer Model (Version 1), Report

DOT-TSC-OST-73-43, 1974.

Johnson, V.; Wipke, K.; and

Rausen, D.J. “HEV Control Strategy for Real-Time Optimization of

Fuel Economy and Emissions,”

Proceedings of SAE Congress,

Presentation No. 2000-01-1566,

Detroit, MI, 2000 (ADVISOR

example).

Milliaris, A.C.; Hsia, H.; and

Gould, H. “Concise Description of

Auto Fuel Economy and Performance in Recent Model Years,”

Paper 760045, Society of Automotive Engineers Congress, Detroit,

MI, February 1976.

Milliaris, A.C.; Withjack, E.; and

Gould, H. “Simulated Sensitivities

of Auto Fuel Economy, Performance, and Emissions,” Paper

760157, Society of Automotive

Engineers Congress, Detroit, MI,

February 1976.

U.S. Department of Energy,

Assistant Secretary of Conservation and Renewable Energy, Office

of Transportation Technologies,

1995. Oak Ridge National Laboratory summarized 39 of these simulations (examples: Eagles, Diane,

Marvel-Argonne National Laboratory, DOE; VPS, University of Illinois; DSIM, J.D. Murrel; CARSIM,

Aeroenvironment; VEHSIMVEHSIME (Volpe Center DOTAerospace Corp. - Sierra Research).

Zub, R.W. Computer Program

(VEHSIM) for Vehicle Fuel Economy and Performance Simulation

(Automobiles and Light Trucks),

Volumes I-IV, Report DOT-TSCNHTSA-81-23.1, 1981.

Researcher—This TechBrief is based mainly on a study performed at the Volpe National Transportation Systems

Center by E. Klaubert, Highway Effects on Vehicle Performance, which is available at www.tfhrc.gov/hnr20/00164.htm.

Numerous other studies mentioned in the references provide additional information and concepts supplementing the

study by Klaubert.

Distribution—This TechBrief is being distributed according to a standard distribution. Direct distribution is being

made to the Resource Centers and Divisions.

Availability—The primary report, Highway Effects on Vehicle Performance (Report No. FHWA-RD-00-164), is available at www.tfhrc.gov/hnr20/00164.htm. Other references are available from the organizations or agencies cited.

Key Words—Air pollution emissions, vehicle external loads, fuel consumption rates, road load tests, driver variability, lateral acceleration, aerodynamic drag, vehicle rolling resistance, chassis dynamometer, drive shaft torques, vehicle/highway performance predictor algorithm, simulation models, VEHSIM, ADVISOR.

Notice—This TechBrief is disseminated under the sponsorship of the Department of Transportation in the interest of

information exchange. The TechBrief provides a synopsis of the study’s final publication. The TechBrief does not

establish policies or regulations, nor does it imply FHWA endorsement of the conclusions or recommendations. The

U.S. Government assumes no liability for the contents or their use.

SEPTEMBER 2001 FHWA-RD-01-100

This RD&T TechBrief summarizes an experiment, its results, data collected from analysis, or findings and recommendations.