52

The effects of single inertia-weight dynamometer (SIW) calibration
versus multiple inertia-weight dynamometer calibration (MIW) and
dynamometer roll spacing was also considered in the Ford program. The
SIW calibration procedure conforms to the method described in the
federal regulations. By this method ",.,the inertia flywheel for the
most common vehicle weight class for which the dynamometer is used"
is engaged during the prescribed coast-down procedure. The resulting
single calibration curve is thereafter applied to the dynamometer re-
gardless of the actual test inertia condition. For belted-type dyna-
mometers, this procedure is only accurate at the inertia weight at
which the dynamometer was calibrated. The MIW is an extension of the
SIW wherein a calibration is obtained at each available inertia weight
yielding a family of curves for the dynamometer.

The effect of MIW versus SIW dynamometer calibrations was studied
for the three test vehicles. Analysis of results show that the single
compared to the multiple procedure produced higher HC, CO and No,
emissions by an average of 2.2%, 0.7% and 1.7%, respectively. The SIW
dynamometer calibration indicated that dyno-road-load horsepower at
50 mph was higher for the 5000 1b inertia-weight vehicle and lower for
the 3000 1b inertia-weight vehicle than the corresponding loads based
on the MIW calibration procedure. The effect of 17} in. to 20 in.
roll spacing at a constant roll diameter of 8.65 in. was also quanti-
fied on CVS-H emissions for the three inertia-weight vehicles. This
variable was controlled during the experiment by physically changing
roll spacing alternately between tests.

Analysis of results showed that the 20 in. roll spacing as com-
pared to 17 in. produced higher HC, CO and No, emissions by an average
of 3.1%, 2.4% and 0.6%, respectively. Roll spacing had no significant
effect on co, emissions, Results also showed that the magnitude of the
effect on all emission constitutents was changed by driver skill and by
vehicle inertia weight. In addition, roll spacing effects on some of
the vehicles were changed by dynamometer calibration procedure and

driver's aid resolution.


116

Table 5,2 Summary of CVS-H Fuel Economy within, between and over

Various Laboratories!

Vehicles
1973 1974 1974
2.6L Capri 351W_ Montego 460 T'Bird
Facilities x s s/kK | xX s s/x | x s s/x

1. Environmental

Protection Agency | 20.0 .54 .027]/ 12.6 .24 .019]} 10.5 .61 .058
2. Ford Emission Test

Laboratory (ETL-75)| 19.7 .56 .028/12.5 .12 .010} 10.5 .16 .015
3. Ford Emission Test

Laboratory (ETL-74)] 19.7 .59 .030/12.4 .15 .012] 10.6 .23 .022
4. Ford Allen Park

Testing Laboratory| 19.6 .30 .015{12.6 .19 .015} 10.7 .10 .009
5. Ford Los Angeles

Laboratory 18.7. .21 .O11] - - - 9.7.15 .016
6. California Air

Resources Board 18.9 .22 .012] - - - 10.5 .17  .016

Overall 19.5 .64 .033 12.5 .20 .016 10.4 .51 .049

lrests at EPA and ETL-75 were conducted with 1975 CO instrumentation.
Testing at ETL-74 and remainder of facilities were with 1974 CO in-

strumentation,.

* - fuel economy in mpg

s + standard deviation in mpg

s - standard deviation as percent of mean

x

REF. 50


18

EPA
Highway
Cycle

CYCLE DISTANCE TRAVELED (%)

SPEED (mph)

FIGURE 3.4 EPA Urban and Highway Fuel Economy Driving Cycle Velocity
Distributions

REF, 17


147

25. Additional information was obtained from the following Foreign

Manufacturers' presentations to CMVE meeting in Washington, DC,
May 21-24, 1974:

a. Daimler-Benz AG

b. Fiat, S.p.A./Ferrari

c. Honda Motor Company

d, Nissan Motor Company, Ltd.
e. Adam Opel AG

f£. Peugeot, Inc.

g. Regie Nationale des Usines Renault
h. Saab-Scania Aktiebolag

i. Toyo Kogyo Company, Ltd.
j. Toyoto Motor Company, Ltd.
k. Volkswagenwerk AG

1. AB Volvo


29.

30.

31,

32.

33.

34.

35.

36.

37.

38.

39.

40.

41,

142

Ford Emission Cell Correlation Program, Vols. 1-3, (Ford Motor
Company 1974.)

Hocker, A.J., "Effect of cold soak temperature on emissions of AMA
cars," California Air Resources Board, Project No. M-257, August 22,
1973.

“CVS cross‘reference service < 1973," Report No. 3, Scott Research
Laboratories, Inc., Plumsteadville, Pa,, April 4, 1974.

"Nitric oxide cross reference service ~ 1973," Report No, 3, Scott
Research Laboratories, Inc., Plumsteadville, Pa., April 18, 1974.

Hurn, R.W., Barlesville Energy Research Center, Bureau of Mines,
U.S. Department of the Interior, private communication June 27,
1974,

Polak, J.C., "Cold weather emissions," Workshop on the Influence
of Cold Weather on Automobile Emissions, Ottawa, Canada, October
1973.

Hromi, J.D., "Some aspects of determining new motor vehicie ‘emis-
sion levels," Presented at the Conference on Statistics and the
Environment, Washington, D,C,, March 6-8, 1974.

Heywood, J.B., "A preliminary assessment of automotive evaporative
hydrocarbon emissions," Department of Mechanical Engineering,
Massachusetts Institute of Technology, October 29, 1973.

“Sealed Housing’ for Evaporative Determinations (SHED) Technique,"
SAE Procedure J171, September 1970.

Martens, S.W., and K.W. Thurston, "Measurement, of total vehicle
evaporative emissions," SAE Paper No. 680125, January 1968.

Martens, S.W., "Evaporative emission measurements with the SHED -
a second progress report," SAE Paper No. 690502, May 1969.

Nelson, E.E., “Hydrocarbon-control for Los Angeles by Reducing
gasoline volatility," SAE Paper No. 690087, Vehicle Emissions,
Part II, (SAE, 1971), pp. 775-801.

Kramer, R.L,, and N.P. Cernansky, "Motor vehicle emission rates,”
U.S. Dept.” HEW, National Air Pollution Control Administration,
Office of Criteria and Standards Report, August 15, 1970.


This Page Intentionally Blank


112

standard conditions by multiplying the measured value by empirical cor-
rection factors designed to account for fuel properties and ambient
variations.

5.4 Statistical Variation of Fuel Economy Measurements

As in the case of exhaust emissions, information concerning the
statistical variability of fuel economy measurements is of importance.
Information concerning the variability of measured fuel economy in a
given test cell or test track, the variability of measurements from
cell to cell at a given laboratory and the variability of measurements
from laboratory to laboratory for a given vehicle are of interest.
Another major concern in fuel economy measurements is the problem asso-
ciated with the estimation of the fuel economy of an entire class of
vehicles based on tests carried out with a single or small number of
vehicles from that class. This type of error in reported fuel economy
is due mainly to the vehicle-to-vehicle variability. Data obtained
during this study concerning statistical variations in fuel economy
measurements are summarized below,

Due to the recently developed concern with fuel economy, only a
small amount of the data required to examine the variabilities men-
tioned above is readily available, However, since a large amount of
the exhaust emission data has included CO, and since CO.

2 2
predominate factor in determining fuel economy based on the Carbon

is by far the

Mass Balance Method, the statistical variability of CO, emission data
may be readily used to estimate the statistical variability of fuel
economy. Whenever possible, actual reported fuel economy data will be
quoted,

As previously noted in Section 4.3, Epaz? has reported the results
of 30 CVS-CH tests designed to determine the reproducibility of both
emissions and fuel economy. The Carbon Mass Balance Method was used to

determine fuel economy. The results of these tests give an average


TABLE 4.14

National Bureau
of Standards Calibration

Gas Standards

CiHy in Air co in Ny NO in Ny co, in Ny
Nominal Value (ppm) Nominal Value (ppm) Nominal Value (ppm) Nominal Value (4%)
3 10 25 1
10 50 50 7
50 100 100 14
100 500 250
500 1000 500

1000

REF, 59

19


1.

2.

4,

6.

9.

10.

11.

12.

APPENDIX A

Organizations Site-Visited or Interviewed

Environmental Protection Agency
Emission Control Technology Division
Ann Arbor, Michigan

Fuel Economy Measurement Procedures
Task Force

Society of Automotive Engineers

Romulus, Michigan

Environmental and Safety Relations
Chrysler Corporation
Detroit, Michigan

World Headquarters
Ford Motor Company
Dearborn, Michigan

Environmental Activities Staff
General Motors Corporation
Warren, Michigan

Transportation Systems Center
Department of Transportation
Cambridge, Massachusetts

Volkswagen of America, Inc.
(meeting in Washington, D.C.)

Environmental Protection Agency

Emission Control Technology Division
and

Surveillance Branch

Ann Arbor, Michigan

Mobil Research and Development Corporation
Paulsboro, New Jersey

California Air Resources Board
El Monte, California

Clayton Manufacturing Company
El Monte, California

Automotive Power Systems Evaluation Study
Jet Propulsion Laboratory
Pasadena, California

145

January 23, 1974

February 6, 1974

February 12, 1974

February 13, 1974

February 14, 1974

March 1, 1974

March 5, 1974

April 3, 1974

May 8, 1974

May 13, 1974

May 13, 1974

May 13, 1974


72

deterioration-factor variability. These values were used to randomly
adjust 5,000 mile increment emission-data points in order to calculate
statistically possible deterioration factors, 50,000 mile and 4,000
mile intercepts. The results were analzed to obtain the probability
that an emission test would yield adjusted emissions below the

federal standards given a deterioration factor and a 50,000 mile emis-
sion value. Also determined was the adjusted emission value below
which 95% of all adjusted emissions could be expected to lie. These
computations indicated that the various sources of variability con-
tribute to the probability that a given vehicle will pass an emission
test. Further discussion of the technique used and a complete table
of the results obtained may be found in Reference 58.

The Monte Carlo Simulation reported in Reference 57 indicates
that statistical variability associated with the determination of DF's
may reflect the special circumstances of the test rather than the
capability of the underlying technology. This idea is particularly
relevant when it is realized that deterioration factors are often
based on emission tests of a single durability-data car. In order to
reduce these errors, some type of data-averaging procedure over a
larger group of "similar vehicles" might be preferable for deterioration-
factor calculations. However, a too-extensive use of average treats
all vehicles and systems as equal and, hence, attractive technologies
may be counterbalanced by less desirable technologies. At the present
time, the manufacturer has the option of testing more than on "identical
durability-data vehicle" in each engine-system combination, with all the
emission data collected being used to calculate the deterioration
factor. If appropriate allowances could be made for possible malfunc-
tion of a durability-data car in a small fleet of "identical vehicles,"
a data-averaging technique would be statistically desirable but still
might not be cost-effective from the manufacturer's point of view.

It has also been suggested that the ratio method presently em-
ployed to compute DF based on the durability data may unnecessarily


3.0 VEHICLE USE PATTERNS AND DRIVING CYCLES

3.1 Introduction

The objective of a driving cycle is to simulate actual driving con-
ditions as accurately as possible within the constraints of time, cost,
instrumentation, etc. Light-duty motor vehicles are operated in a
complicated sequence of operational modes including idle, acceleration,
deceleration, and cruise, The time spent in each mode and the magni-
tude of the accelerations, decelerations and cruises can vary signifi-
cantly depending on whether the vehicle is being driven in an urban,
suburban, rural or interstate mode. In addition, two drivers traveling
the same route under identical traffic conditions are likely to drive in
a significantly different manner. Therefore, it is impossible to
develop an absolutely typical driving cycle that will accurately
represent the way all vehicles are driven.

However, since it has been established that both emissions and
fuel economy are dependent on the driving cycle, one or more standard-
ized driving cycles for both emissions and fuel economy testing must be
adopted, These cycles will be subsequently utilized to determine if a
vehicle meets legislated emissions standards, to evaluate the relative
fuel economies of various automotive-design parameters and to compare
the economies of one vehicle versus another. The driving cycles should
represent, as nearly as possible, actual usage patterns of LDMV,

They should be repeatable and capable of being driven easily and
accurately,

Considerable effort has been directed toward the development of
representative driving cycles for both emissions and fuel economy. In
addition, various organizations have attempted to establish typical
vehicle-use patterns. Since the establishment of representative
driving cycles is an important aspect of both emissions and fuel
economy test procedures, the results of these studies are summarized in
subsequent paragraphs.


121

one should not expect to obtain good agreement between the fuel econo-
mies measured on the track and the dynamometer for the low-weight vehicle.
It should be noted that the dyno was designed and constructed for test-
ing of vehicles near 4,000 to 5,000 1b and that the dyno could have been
designed to minimize internal friction which would allow coast-down
times for low inertia-weight vehicles to be accurately reproduced.

Inspection of the data, reported on all three driving cycles for
the two heavy vehicles, indicates that excellent, agreement within 1% to
4% of the test-track mean can be obtained on a large-roll chassis dyno-
mometer if care is taken to set the dyno load to reproduce actual road
coast-down times. The results for the low inertia-weight vehicle indii-
cate that significant errors in fuel economy can occur for dynamometer
tests if road load is not adequately simulated by the dynamometer.

Another laboratory has reported fuel economies of eight vehicles
for the EPA highway cycle as measured on both a dynamometer and a test
track.26 The fuel economy of the vehicles driven on the SAE 55-mph
interstate cycle was also measured on the test track. These data are
presented in Table 5.4, and the measured dyno versus track results for
the EPA highway cycle are graphically represented in Figure 5.8. The
dynamometer data were obtained on a Clayton-type dyno, and the road load
at 50 mph was set according to the: "cook book" method established in the
Federal Register.

Inspection of these data indicates that, in all cases, the fuel
economy measured on the dynamometer is larger than the value obtained on
the track. Percentage differences in the values (fuel economy dyno
minus fuel economy track divided by fuel economy dyno) range from
approximately 4% to 16%. It is also important to note that fuel econo-
mies measured on the track for these eight vehicles as measured on the
SAE 55-mph interstate cycle are in ‘good agreement with values obtained
on the EPA highway cycle.

Various sources have analyzed the energy required to drive a vehi-
cle over the CVS-CH cycle, and it has been shown that inertia forces and


127

to receive an average fuel economy for his vehicle which is significant-
ly below that which could be obtained in longer trips and warmer cli-
mates, Reference 54 also indicates that a percentage of fully warmed-
up fuel economy can be calculated for a highway-type driving cycle.

The highway-type warm-up schedule curve reported in Reference 54 falls
only slightly above that of the urban or city warmed-up schedule. Note
that Figure 5.9 has only been discussed in terms of cold-start condi-
tions. Reference 55 suggests that the trend indicated in Figure 5.9
would also apply to vehicles which are in a warmed-up condition before
the trip is started. It would be expected that for a short trip, the
average fuel economy of a hot start would be greater than that of the
equivalent fuel economy of a cold start for the same driving cycle and
trip length.

The influence of ambient temperature on automotive fuel economy
is also of interest. The fuel economy of various classes of vehicles
on the CVS-CH test cycle as a function of ambient soak and operating
temperature as reported by Reference 33 is shown in Figure 5,10. In-
spection of these results indicates that a reduction in ambient temper-
ature from 75°F to 20°F results in an average fuel economy penalty of
approximately 5% for the twenty 1969 to 1971 model production vehicles
and 11% for the prototype catalyst equipped vehicles. Fuel economy
penalties of 13% and 9% between 20°F and 75°F were reported for the
diesel-equipped and stratified-charge PROCO vehicles, respectively.

Since warm-up is seen to have a significant effect on the average
fuel economy of a vehicle and since short trips and cold starts are
known to occur with high frequencies as previously discussed, a fuel
economy test which iricludes both a cold and a hot start in an urban
cycle would more closely parallel real urban fuel economy, This idea
has been incorporated into the CVS-CH test procedure. Note that the
hot start of the CVS-CH procedure occurs after a cold start and the
first 7.45 miles of the cycle have been driven. Thus, it can be seen


67

ar

at
2
£
2
Bs
Ke
= a -
rs) —-———___——~"
g
Ss)
2 4
a
& 1920 Production Cars, 1967-1973
g © 4 Prototype Emission Cars (all catalyst)
= 3r X Diesel
> © Stratified Charge (Proco)
=z

2 —

1 L

lel Sree --
1 | in niente Panel
0 20 40 60 80 100 120

TEST AMBIENT TEMPERATURE (°F)

FIGURE 4.5 Effect of Ambient Temperature on HC Exhaust Emissions
During the CVS-CH Test

REF. 33


25

factors for HC, CO and NOx are based on the CVS-CH test procedure.
Therefore, statistical variations in the CVS-CH test procedure play an
important role in the certification procedure, and hence the statistical
reliability and factors affecting the variability of the CVS-CH test
method are considered.

Other important factors such as the effect of ambient conditions
on exhaust emissions, the effectiveness of the test methods and pro-
cedures employed to obtain durability data, test methods and procedures
associated with LDMV evaporative HC emissions and other related infor-

mation are also discussed in subsequent paragraphs.

4.2 Certification Procedure

In order to obtain a Certificate of Conformity for a class of
vehicles, the manufacturer must demonstrate that the vehicles meet the
appropriate emission standards over the “useful life" of the vehicle.
The regulations require a manufacturer to test two separate fleets of
prototype vehicles representing models to be sold to the public. The
emission-data fleet is intended to determine the emissions of relatively
new vehicles. The vehicles in this fleet are driven 4,000 miles to
break in the engine and stabilize emissions. The emissions are then
measured, using the CVS-CH test procedure. Allowable maintenance on
emission-data vehicles is limited to the adjustment of engine idle
speed at the 4,000-mile test point.

The second fleet, the durability-data:- fleet, is designed to
determine the capability of the emission-control system to keep emis-
sions below the standards over the expected useful life of the vehicle.
Each engine-system combination, which is defined as an engine family-
exhaust-emission-control-system combination, in the durability-data
fleet is examined separately. The vehicles are driven for 50,000
miles and tested for emissions every 5,000 miles. The procedure for
mileage accumulation is the Durability Driving Schedule over a modified
AMA route. The maximum speed is 70 mph, and the average is 30 mph.


96

4500}
Standard
Size
Chevrolet
2 4000+ Standard
and Size
3 Ford
wu
=
a
c
=)
© 3500/-
3000) ! aa i J
1958 1962 1966 1970 1973

MODEL YEAR

FIGURE 5.3 Vehicle Weight Versus Model Year for Two Standard Size
Vehicles

REF. 47


32

TABLE 4.1

Factors Affecting Exhaust Emissions Variability of a Given Vehicle

at Various Levels

LAB OA Lab to Lab LAB OB
>
7 Variability ;
L I etc. I I etc,
Cell Cell Cell Cell
—> kK
Al A2 Bl B2
A
Cell Cell-to-Cell
Variability Variability
MAJOR SOURCES OF EACH LEVEL
OF VARIABILITY
Sources Cell Cell-to-Cell Lab-to-Lab
Vehicle Vehicle Vehicle
Driver Driver Driver
Ambient Condition Ambient Condition Ambient Condition
Dynamometer Dynamometer
cvs cvs
Analyzer Analyzer
Operator Operator
Calib. Gas
Computer

REF, 23


57

the low-emission standards and the necessity of subtracting the concen-
tration of the pollutants simultaneously collected in a background
sample bag from the measuréd emissions may cause both systematic and
random errors in the measurement of pollutants collected during an
emissions test. Typical sample-bag concentrations of pollutants for
vehicles meeting the 1975 interim California standards and the 1978
Federal standards are listed in Table 4.12. Instrument sensitivity
may cause problems at the 1978 Federal levels.

The preparation, stability and labeling of calibration gases at
the levels required for exhaust-emission measurements has accounted
for significant random errors ii the past. In order to provide a
mechanism for developing comparisons of the accuracy and repeatability
of gas analysis procedures utilized at various laboratories, the Scott
Calibration Gas Cross-Reference Service has been developed.

At the present time, there are four services available, including
Automotive Exhaust, Diesel Exhaust, Nitric Oxide and Constant Volume
Sampling. Four times a year, analytical laboratories who subscribe
to one or more of the services receive gas cylinders of unknown gas
mixture. The components are specified, but their concentrations are
unknown. Each participating laboratory analyzes the mixture and re-
ports their results to a coordinator. Subsequently, each participating
laboratory receives a detailed report listing results from all partici-
pauis and providing a statistical analysis of the results. The results
of a recently published CVS Cross-Reference Service+ are summarized
for HC, CO and co, in Table 4.13. The unknown samples of HC in air,
Co in air and CO, in air were analyzed for HC as ppm propane with
FID's and both the CO and CO, were determined with NDIR analyzers. »
The results of a recent Scott Nitric Oxide Cross-Reference Service
are also listed in Table 4.13. The NO data were obtained with chemi-
luninescence detectors.

In an effort to reduce systematic errors associated with calibra-
tion gases, the National Bureau of Standards (NBS) has recently agreed .


141

15. Kruse, R.E. and C.D. Paulsell, "Development of a highway driving
‘ eycle for fuel economy measurements," Environmental Protection
Agency, Emission Control Technology Division, Ann Arbor, Michigan,
March 1974,

16, Paulsell, C.D., "Amendments to the report on development of a high-
way driving cycle for fuel economy measurements," Environmental
Protection Agency, Emission Control Technology Division, Ann Arbor,
Michigan, April, 1974.

17, LaPointe, C., Ford Motor Company, private communication, June 1974.

18. Society of Automotive Engineers Recommended Practive, "Fuel Economy
Measurement - Road Test Procedure," SAE J1082, (New York, April 1974).

19, Cole, E.N., "Statement to Senate Public Works Committee by General
Motors Corporation, Attachment 7," November 5, 1973.

20. Code of Federal Regulations, Title 40 Protection of Environment,
Office of the Federal Register, July 1, 1973, Revised.

21. The Federal Register, XXXIX, 92, (May 10, 1974) 16904.

22, Hellman, K., EPA Ann Arbor, private communication to R.A. Matula,
1974,

23, Elder, C., General Motors Corporation, private communication to
R.A. Matula, 1974.

24, General Motors Request for Suspension of the 1976 Emission Stan-
dards, Appendix 27, June 20, 1973.

25. Report on Honda Emission-control Systems for 1975 and Subsequent
Model Years, Prepared for the Committee on Motor Vehicle Emissions
of the National Academy of Sciences, May 24, 1974.

26. Heinen, C., Chrysler Corporation, private communication to R.A.
Matula, June 1974,

27. Klingenberg, H., M. Fock, K. Lies, and L, Pazsltka, "A critical
study of the United States exhaust emission certification - test -
error analysis for the test procedure," APCA Paper. No. 74-242,
Presented at the 67th Annual Meeting of the Air Pollution Control
Association, Denver, Colorado, June 1974, ,

28, "The method of emission averaging as it relates to the 1975 federal
emission standards," Preliminary Report of AQC-Ad Hoc Statistical
Panel of MVMA, Feburary 26, 1973.


28

initiated from a cold start. Complete descriptions of the CVS-CH
test method may be found in the literature.2977#

The CVS-C test method was employed for emission testing on vehicles
in model years 1972, 1973 and 1974. The CVS-C test is very similar to
the CVS-CH test except that all emissions are collected in a single bag
and the hot transient phase of the test is eliminated. The CVS-H test
is also employed to measure emissions from a fully warmed-up vehicle.

In this test, the vehicle is fully warmed-up prior to initiating the
CVS-C test.

It is possible to estimate the probability that a given emission~
data car or an entire engine family will pass the certification procedure
assuming that the statistical variations associated with the vehicles
and test procedures follow a normal probability distribution. In order
to make these computations, it is necessary to have data concerning the
variability (s,) relative to the true adjusted emission mean (x) and
the ratio of the true adjusted emission mean (x) to the appropriate
emission standard @,). The true adjusted emission mean &,) is de-
fined as:

FL gx
DF, = Appropriate deterioration factor for vehicle under
consideration and pollutant, i

Day = True mean emission value of pollutant i for
emission-data car at 4,000 miles.

i = subscript corresponding to HC, CO or NO,

The following probability parameters are defined:

Py (1) - the probability of a single pollutant i being
below the standard for one test.

P, (2) - the probability of a single pollutant i being
below the standard in at least one out of two
tests.

P (2,3,1} - the probability that all three pollutants

(HC, CO and NO.) are Simultaneously below


60

to develop a set of master calibration gas standards with, accuracy
within +1% of the specified cylinder value. The proposed NBS standard
calibration gases are listed in Table 4.14. At the present time, the

Cau 8 in air, CO in Ny and co, in’ Ny have been produced, and the NO in
Ny standards are projected to be available in September 1974. A
meeting was held at NBS in May 1974 to discuss user experiences with
the prepared Standards. In-general, there appeared, to be agreement
among all government and industry ‘participants that the NBS standards
were within the specified +1% tolerance levels, except possibly for
the nominal’ 10 ppm Cally in air standard. Additional work with this
mixture is being undertaken.

In many instances, a significant fraction of the total mass of
both HC and CO collected during the CVS-CH test is collected in the
cold transient phase of the ‘test and, hence, in these cases,the cold-
start weighting factor in the test method -plays a Significant role in
the technological ‘demand placed on a éontrol system. ,The results
listed in Table 4.2°Endicate that the cold transient phase of the
cvs-cH test accounted for approximately 52% and 59% of the total mass
of HC and co collected during the 30 tests on a specific 1971 vehicle.
In these tests, the. variability of the HC and CO collected in the
cold transient phase of the test was also reported to be greater than:
the variability associated with the other two phases of the test.

The mass of HC and CO collected during each phase of the CVS-CH
test for seven production wehicles ranging from the 1967 to the 1973
model year has also been reported. >” In these tests, which were
carried out at an ambient temperature of 75°F, the cold transient
phase of the test accounted. for ‘approximately 35% to 51% and 39%
to 77%.o£ the mass of the HC and CO collected during the total test,
respectively.

Due to thermal effects, it has been suggested that the cold
transient phase may account for an ‘even greater fraction of the

total HC and CO emissions when oxidation catalysts are employed on


25,
20--
7)
Qa
£—
2 ist
fo)
8 1957-1967 Vehicles
a “NX
@ 10 “—
2 1973 Vehicles SO ~e
5k
l | l at { | | |
2000 2500 3000 3500 4000 4500 5000 5500

INERTIA WEIGHT (Ib)

FIGURE 5.4 Fuel Economy of Vehicles on the CVS-C Cycle as a Function
of Inertia Weight

REF. 47

L6


119

Data reported in Reference 29 have indicated that the dynamometer
load applied by a Clayton-type dyno while driving the CVS-H cycle with
three different inertia-weight vehicles was a function of both dyno-roll
spacing and dyno-calibration method. The total work (measured by drive
shaft torque) during the CVS-H test using 20 in. roll spacing. versus
17% in. roll spacing on all inertia-weight vehicles was higher by an
average of 1.3%. However, analysis of the data indicated that roll
spacing had no significant effect on co, emissions and, hence, it can be
concluded that roll spacing did not have a significant effect on fuel
economy.

The dynamometer calibration technique for setting road load at
50 mph was also shown to affect total work required to drive the CVS-H
cycle. Differences in work ranging from 1.2% less total work for the
3,000 1b inertia-weight vehicle to 2.4% more work for the 5,500 1b vehi-
cle were reported as a function of dynamometer-calibration method.

Another manufacturer?» has reported that’ the calibration of the
indicated load on a given Clayton-type dynamometer is not as reproduci-
ble as might be desired and that this factor may cause variations of as
much as 10% in fuel economy measured for low inertia-weight vehicles on
the CVS-CH test.

The SAE-recommended urban, suburban and 70-mph interstate driving
cycles fuel economies were determined at three different test tracks,
one resu site and on a large roll chassis dynamometer. The results of
these tests are summarized in Table 5.3.92 The road loads on the large-
roll, mechanical-chassis dynamometer were set by matching as closely as
possible the coast-down times of the vehicles on the River Road Highway
to the dyno coast-down times, Coast=down times could be accurately
matched for the two heavy vehicles, but due to internal friction in the
dynamometer, the road coast-down times for the light vehicle could not
be simulated, Therefore, numerous tests at different dyno loads were
carried out for the low inertia-weight vehicle. Due to this problem,


Summary of Emission Test Variability for Stratified Charge CVCC Vehicles

Test Cell No. of Tests
x
A 5 0.245
B 10 0.294
B 5 0.326
c 7 0.273
¢ 10 0.325
1 -
x
&
i — standard deviation as percent of mean

— mean emission value on CVS-CH test in g/mi

TABLE 4.5

6.9

13.2

7.6
6.1

4.2
3.4

x
423.9
476.3
454.4
509.2

454.0

1

co2
—~s

x
2.1

2.5
2.6
1.5

2.2

REF. 25

8€


80

TABLE 4.17

Summary of Evaporative HC Emission Test Results
Obtained During Surveillance tests?

L. A, Data (g) Denver Data (g) Weighted
Model No. Values __
Year Tests Diurnal Hot Soak Diurnal Hot Soak B/mi
57-69 102 26.08 14.67 2.7
70 13 17.75 10.70 1.9
71 21 14.87 10,89 - - 1.9
71 22 - - 47.2% 34.8% 6.0%
72 22 12.40 11.80 - - 1.9
72 22 - : 17.4 14,2 2.4

Note: “Winter grade fuel (11.7 RVP) used on all tests. L.A. data
up to 1971 used all types of fuel (7.8 - 12.0 RVP).

lexperimental data based on SHED method

REF. 42, 43


1.0 SUMMARY AND CONCLUSIONS

1,1 SUMMARY

In order to evaluate the technological feasibility of meeting the
automotive emission standards, with particular ‘emphasis upon systems
and engines for meeting various levels of NOx emissions and upon the
question of fuel economy, the Committee on Motor Vehicle Emissions
(CMVE) of the National Academy of Sciences required information ,re-
lating to the reliability and reproducibility of emissions and fuel
economy measurements. Since the reliability and reproducibility of
any experimental measurement is defined by the test methods and pro-
cedures utilized to obtain the measurement, the important aspects of
present and projected emission and fuel economy test methods and
procedures for light-duty motor vehicles (LDMV) have been considered,

The CVS-CH exhaust-emission test procedure plays an important role in
the certification process for 1975 and subsequent model-year LDMV.
Hence, the statistical variability of CVS-CH emission tests for these
vehicles and the relative magnitudes of the various factors affecting
both systematic and random errors encountered during CVS-CH tests are
considered. Additional questions concerning the effect of ambient
temperature on exhaust emissions, the suitability of present exhaust-
emission-control durability test methods and procedures and the
possible modifications of the present HC exhaust-emission standards
and measuring techniques designed to account for only reactive HC
are also addressed. Finally, recent data relating to the effectiveness
of present evaporative HC emission test methods and procedures and
LDMV evaporative-control systems are presented and discussed.

At the present time, generally accepted standardized fuel economy
test methods and procedures are not available. Due to the significance
of this issue, it is important that standardized test methods and pro-
cedures, based on sound engineering and scientific considerations, be
developed as soon as possible. In the general area of fuel economy,
the important factors affecting LDMV fuel economy, the important


PREFACE

The National Academy of Sciences, through its Committee on Motor
Vehicle Emissions (CMVE), initiated a study of automobile emissions-
control technologies at the request of the United States Congress and
the Environmental Protection Agency (EPA) in October 1973. To help
carry out its work, the CMVE engaged panels of consultants to collect
information and to prepare consultant reports on various facets of mo-
tor vehicle emissions control. This Consultant Report on Emissions and

Fuel-Economy Test Methods and Procedures is one of five consultant re-
ports prepared and submitted to the Committee in connection with the

Report by the Committee on Motor Vehicle Emissions of November 1974.

The other consultant reports are:

An Evaluation of Catalytic Converters for
Control of Automobile Exhaust Pollutants,
September 1974

Emissions Control of Engine Systems, September 1974

Field Performance of Emissions-Controlled
Automobiles, November 1974

Manufacturability and Costs of Proposed Low-

Emissions Automotive Engine Systems, November

1974
These five consultant reports are NOT reports of the National Academy
of Sciences or its Committee on Motor Vehicle Emissions. They have
been developed for the purpose of providing a partial basis for the
report by the Committee as described more fully in the cover NOTICE.

The reader should note that most of the data reférred to in

this consultant report were obtained prior to August 1974,

Acknowledgment
The author would like to extend his sincere thanks to Mr. David

Milks of the Combustion Kinetics Laboratory, Drexel University, for his
significant contributions in data collection, interpretation and analysis
which were essential elements in the development of this consultant
report,

iii


42,

43.

44.

45.

46,

47,

48,

49,

50.

51.

52.

53.

54,

55.

56.

143

Paulsell, C.D., "Mobile source evaporative emissions - a draft,"
EPA, Ann Arbor, Michigan, March, 1974,

"Automobile exhaust emission surveillance, a summary," EPA Report
APTD-1544, prepared by Calspan Corp. under Contract No, 68-01-0435,
May, 1973. .

The Federal Register, XXXIX, 92, May 10, 1974, 16904.

Ford Motor Company - Petition for Amendment of Part 85 of Title 40
of the Code of Federal Regulation Control of Air Pollution from
New Motor Vehicles and New Motor Vehicle Engines,

Heubner, Jr., G.J., and D.J. Gasser, “Energy and the automobile -
general factors affecting vehicle fuel consumption," SAE Paper
No, 730518, 1973.

Hutchins, F,P. (Project Officer) "Passenger car weight trend
analysis - volume II - technical discussion," EPA Report No,
460/3-73-006b, January 1974,

Elliott, D.R., W.K. Klamp, and W.E. Kraemer, "Passenger tire
power consumption," SAE Paper No. 710575, June 1971.

U.S. Department of Transportation, private communication to R.A.
Matula, June, 1974.

Nolan, J., Ford Motor Company, private communication to R.A, Matula,
May 1974,

SAAB-SCANIA, private communication to R.A. Matula, June, 1974.

Baker, J.B,, Memo to SAE Fuel Economy Measurement Procedures Task
Force, April 1, 1974,

LaPointe, C., "Factors affecting vehicle fuel economy," SAE Paper
No. 730518, 1973.

Scheffler, C.E., and G.W. Niepoth, "Customer fuel economy esti-
mated from engineering test," SAE Paper No. 650861, 1965.

"A report on automobile fuel economy," U.S, EPA, Office of Air
and Water Programs - Office of Mobil Source Air Pollution Control,
October 1973.

General Motors Request for Suspension of 1975 Federal Emissions
Standards, Appendix 27, March 5, 1973.


35

The results of a series of 16 CVS-CH tests carried out on a

Chevrolet Impala equipped with a 350 CID engine, a 4 bbl carburetor,

air injection, EGR and an oxidizing catalyst are summarized in Table 4.3.23
These experiments were carried out in the same test cell at constant
ambient conditions with the same driver and bench operator in order to
determine the repeatability of a catalyst-equipped vehicle operating at
emission levels near the interim 1977 emission standards. Inspection

of these results indicates that the standard deviation ranges from a

low value of approximately 1% for CO, to a high of approximately 30%

for HC. Other data provided by General Motors”* for test-to-test

variability of CVS-CH tests in a single test cell for experimental
vehicles with emissions near 1977 interim levels are summarized in
Table 4.4.

Exhaust-emission tests on the CVS-CH test for a group of vehicles
equipped with 2.0 liter CVCC stratified-charge engines in various test
cells at a given laboratory are summarized in Table 4.5.2 Inspection
of these results indicates that for these low-mileage vehicles, which
have emissions near the 1978 Federal Standards, the reported standard
deviation as percent of the mean is in the range of 7% to 13%, 2.5%
to 7.5% and 3% to 5% for HC, CO and NOL, Fespectively.

Data provided by Chrysler Corporation for a specific 1973 model-
year production vehicle that has been periodically tested on the CVS-H
test in a number of test cells are listed in Table 4.6. Inspection of
these data indicates that emission variability in a single cell is in
the range of 5% to 35% even for CVS-H tests.

Chrysler Corporation” also reported the mean and standard devia-
tion as percent of the mean for exhaust emissions of 90 tests of the
same vehicle as discussed in the preceding paragraph at five test cells
to be 1.46 + 13.5%, 11.30 + 27.1%, 2.23 + 9.3% and 780.4 + 4.7% g/mi
for HC, CO, No. and 0,, respectively, Comparison of these results with
the data listed in Table 4.6 indicates that the mean value and standard
deviation for the composite cell-to-cell emissions lies between the

maximum and minimum values obtained in the various individual cells.


66

temperature on HC, CO and No, exhaust emissions for the various types
of vehicles tested aré graphically represented in Figures 4.5 to 4.7.
Inspection of these results indicates that ambient temperature has a
Significant effect on HC and CO emissions for the twenty 1967-1973
production vehicles. Hydrocarbon and CO emissions increase by 60% and
52%, respectively, when the vehicles were tested at 20°F in comparison
to tests at 75°F. The No, emissions from the same group of vehicles
increased by approximately 25% in the same temperature interval.

The HC and CO emissions from the four prototype, catalyst-equipped
vehicles increased by 160% and 409%, respectively, when the tests were
carried out at 20°F rather than 75°F. The No, emissions for these same
vehicles increased by approximately 33% over the same temperature inter-
val.

Hydrocarbon emissions for the diesel and stratified-charge PROCO-
powered vehicle were also found to increase significantly between 75°F
and 20°F. In contrast, the CO emissions from these two vehicles were
relatively constant with ambient temperature. No, emissions for these
two vehicles were also shown to be less dependent on ambient tempera-
ture than the emissions from either class of spark-ignition, engine-
powered vehicles.

As indicated earlier, the cold transient phase of the test
accounted for approximately 64% and 73% of the total mass of HC and
CO, respectively, for the four prototype, catalyst-equipped vehicles
when the test was run at 75°F. At 20°F, the cold transient phase
accounted for approximately 89% and 96% of the total HC and CO col-
lected for the same vehicles.

4.6 Durability Test Methods and Procedures

The test methods and procedures associated with the development
of emission-deterioration factors (DF) for the durability-data fleet

have been discussed in Section 4.2. Some concerns have been raised


rh

Certification value = DF x X = (1 + 46,000 m) X. (5)
I

If the certification value, as computed from Equation (5), is less than
the appropriate standard, the vehicle passes; if not, it fails.

If one assumes that the rate of deterioration of the emission-
control system is not a function of either the extrapolated value of
the emissions at 4,000 miles (e.g., m #m (I)) for the durability-data
vehicle or the calibration of the system, then this technique, as out-
lined in Equation (5), may unnecessarily penalize an emission-data
car whose corresponding durability-data car had a low value of extrapo-
lated emissions at 4,000 miles (I).

In order to circumvent this potential problem, Hromi?> has
suggested another method for determining whether a vehicle passes
certification. This technique is based on a simple difference formu-
lation as given by Equation (6):

Certification Value = X + E(50,000) - E(4,000) (6)
X + 46,000 m
The vehicle would pass if the certification value, as computed

from Equation (6), was less than the appropriate emission standard
and fail if it was greater than the standard.

Sufficient data could not be obtained during the course of this
study to determine if m # m(I) for various control systems, durability-
car calibrations, etc. If at a later date sufficient data are available
for a range of emission-control systems, it might be appropriate to
consider changing the method of combining durability data with emission
standards as outlined by Equation (6) rather than the method presently
employed (Equation 5).

4.7 Evaporative HC Emissions

In addition to HC exhaust emissions discussed previously, fuel
evaporation losses may contribute significantly to the total HC emis-
sions from LDMV. Evaporative emissions differ from exhaust emissions

in that evaporative emissions are formed as a result of physical


EMISSIONS AND
FUEL-ECONOMY
TEST METHODS
AND
PROCEDURES

CONSULTANT REPORT TO THE:
Committee on Motor Vehicle Emissions
Commission on Sociotechnical Systems

SEPTEMBER 1974

SZ
U.S. ENVIRONMENTAL PROTECTION ACENCY
Office of Air and Waste Management

Office of Mobile Source Air Pollution Control


101

120-—
tw = 4500 Ib
cgA = 13 ft
100--— a = 0015 |
= 3
p 0.074 ib/ft (HP) ace
a= 4,84 ft/s?
Ed 80/—-
in
3
fo)
o 60}—
(HP) acc
40/— a= 2.0 ft/s?
20;- (HP) Aero |
(HP) Roll
. —— =
10 20 30 40 50 60
SPEED (mph)

FIGURE 5.6 Horsepower Required to Overcome Inertia, Aerodynamic and
Rolling Loads as a Function of Speed for a Specific Vehicle


124

idle conditions dominate fuel consumption, “993 Therefore, potential

errors in dynamometer road-load encountered during CVS-CH tests should
not significantly affect the measured fuel economy, Similar computa-
tions concerning the, energy required to traverse the EPA highway cycle
indicate that rolling ‘resistance and aerodynamic drag may constitute as
much as 65% to 75% of the energy required, Therefore, errors associat-
ed with dynamometer road loads may significantly affect the measured

fuel economies on the EPA highway cycle.

5.6 The Affect of Cold-Start and Ambient Temperature on Fuel Economy

As discussed in Section:3,2, many automobile trips are very short,
and in the U.S., more vehicle miles are driven for trips within 0.5
miles of 4.5 miles than trips over any other l-mile interval. In addi-
tion, a significant number of vehicle trips are initiated from a cold-
start condition which is defined as the initiation of a trip after the
vehicle has remained in a stationary position for a period sufficiently
long so that it is essentially in’ thermal equilibrium with local anbi-
ent conditions, - The severe fuel economy penalties associated with
short trips initiated from cold-start are discussed below. In addition,
data relating to fuel’ economy for'a specified driving cycle as a func-
tion of ambient temperature are presented,

When considering trips of various lengths, it has been ‘proposed
that two phases of an urban-cycle fuel economy , cold and warm, must be
considered, 46 The cold phase of urban operation includes approximately
the first 10 miles of travel and the warm phase is represented, by trips
longer than 10'miles’ in duration. During the cold-phase operation, the
choke and lubricant warm-up are considered to be major factors in
determining fuel economy, The warm phase may be expected to have sig-
nificant improvements over the cold phase in fuel economy. One method
of graphically illustrating the expected fuel economy due to vehicle
warm-up versus trip length is shown in Figure 5.9. This figure


Modif..

MON. ...-.00-
MPS.eeeeeere
MT. ce eeeeeee
MVMA.. ee eee
NIASE....-.
\

Preeeescvees

PCV veeeoeee

PP ancarecees
PROCO.......

| Se

RE. cesses eeee
RON. eee eseee
SAE....e.00-
SHED........
std. dev....
TCCS.......-

3-way cat...
UDDS.....006
VME. eee eee ee

152

lean-burn engine system
light-duty motor vehicle
liquefied petroleum gas
Manufacturing and Costs Panel of CMVE

standard internal-combustion engine modified with emissions
controls such as spark retard and air pump

motor octane number

miles per gallon fuel economy

manual transmission

Motor Vehicles Manufacturers Association

National Institute for Automotive Service Excellence
various nitrogen oxide compounds

production

positive crankcase ventilation

pre-production

Ford--Programmed Combustion Process (direct-fuel-injected,
spark-ignited, open-chamber, stratified-charge engine)

research

rotary engine

research octane number

Society of Automotive Engineers

sealed housing for evaporative (emissions) determinations
standard deviation

Texaco controlled combustion system (direct-fuel-injected,
spark-ignited, open-chamber, stratified-charge engine)

combined oxidizing and reducing catalyst
urban dynamometer driving cycle

vehicle miles traveled


NOTICE

This consultant report was prepared by a consultant at the
request of the Committee on Motor Vehicle Emissions of the National
Academy of Sciences. Any opinions or conclusions in this consultant
report are those of the consultant and do not necessarily reflect
those of the Committee or of the National Academy of Sciences.

This consultant report has not gone through the Academy review
procedure. It has been reviewed by the Committee on Motor Vehicle
Emissions only for its suitability as a partial basis for the report
by the Committee.

The findings of the Committee on Motor Vehicle Emissions, based
in part upon material in this consultant report but not solely depen-

dent upon it, are found only in the Report by the Committee on Motor
Vehicle Emissions of November 1974,

ii


102

rolling resistance horsepower, ‘ (HP) However, the importance of

aerodynamic drag on total road- Toad Lorsepover becomes very signifi-
cant at high speeds.. Thus, at high speeds the aerodynamic styling of
the vehicle will-have a significant effect on both the vehicle's fuel
economy and its maximum speed.

Obviously, the aerodynamic drag must also be a function of the
surrounding air velocity in the form of head winds and crosswinds
which can. significantly affect fuel economy. Inspection of Figure 5.6
also indicates. that the instantaneous power required to accelerate the
vehicle at 4,84 ft/sec” is very significant when compared to the road-
load power.at the same speed. Even relatively moderate accelerations,
2.£t/sec’, require significant instantaneous power outputs when com-
pared to road load in order to overcome the inertia effects. Since
the product CA is not a Linear function of a vehicle's mass, the
relative importance of aerodynamic drag tends to increase for lower
inertia-weight vehicles.

“The spark-ignition, internal-combustion engine does not effi-
ciently convert the energy released from the combustion process to
mechanical work available at the drive shaft. In the theoretical
limit, an ideal spark-ignition engine with a compression ‘ratio of
approximately 8.2 could attain a maximum thermal efficiency in the
range of 5The However, this ideal efficiency represents an engine
operating without -heat losses to the cooling water or lubricating oil,
without energy losses‘due to friction ‘drive train or pumping losses
and without combustion inefficiencies etc. Dué to these and other
factors, actual spark-ignition engines only have thermal efficiencies
in the range of 20%. An estimate of: the percent of energy liberated
by the combustion ‘process available to ‘propel the vehicle and drive
the vehicles accessories along with an estimate of the relative mag-
nitude of the losses as a function of vehicle cruise speed are shown
in Figure 5.7.49 In general, increasing engine compression ratio

within operational limits results in both fuel economy and acceleration


23

driving cycle, is not in complete agreement with the composite driving
pattern results obtained recently. However, since it has been shown
that emissions in an urban driving cycle are not very sensitive to
changes in the cycle, it is concluded that the UDDS cycle represents an
average urban trip, as far as emissions are concerned, "as well as it
needs to."

Since driving patterns change with time and two drivers would tend
to drive the same route in a different manner it is not possible to
develop an absolutely typical fuel economy driving cycle. However,
since the driving cycle strongly influences fuel economy, it is
important to adopt standardized fuel economy driving cycles that can be
utilized to evaluate the relative fuel economies of various automotive
designs and to compare the economies of one vehicle versus another.

Since significant vehicular miles are accumulated in both urban
and nonurban environments, and fuel economies in these two driving modes
are significantly different, it is concluded that two standard LDMV fuel
economy driving cycles--one designed to represent urban vehicle
operation and one designed to represent highway driving--are needed to
allow rational consumer choice. Data presently available indicate the
fuel economy for a given vehicle is approximately 50% greater for a
typical highway cycle than for a typical urban cycle. (See Section
5.2.)


82

Based on these results, two immediate needs are obvious. First,
an accurate test method and procedure for measuring evaporative HC
emissions must be developed, which corresponds closely to "real life.”
It is possible that a careful evaluation of the situation may show
that the SHED method is adequate for this purpose. Second, an exten-
sive study should be undertaken to determine the relative importance
and cost effectiveness of control strategies designed to control
automotive HC emissions based on both exhaust and evaporative HC

emission standards.
4.8 Consideration of Nonreactive HC Exhaust-Emission Standards

Presently there is some question about both the absolute magni-
tude and method of measuring exhaust HC emissions during the federal
certification procedure. This concern is based on the fact that
national primary and secondary HC air-quality standards are specified
in terms of non-methane HC's while the exhaust-emission measurement
techniques and standards include methane. Methane has been excluded
from the air-quality standards since it is not considered to partici-
pate in atmospheric photochemical reactions leading to the formation
of photochemical oxidants and since substantial ambient levels of
methane are known to originate from uncontrollable sources.

The measurement of total HC exhaust emissions rather than non-
methane hydrocarbons was promulgated by the EPA’ Administrator since:
(1) at the time, adequate techniques for the routine measurement of
methane in LDMV exhaust were not available; (2) the methane fraction
of HC emissions was assumed to be low; and (3) potential emission-
control systems were expected to reduce all exhaust HC components
equaily.“*

The introduction of oxidation catalysts as an important HC and
CO emission-control technology and the development of new instrumen-

tation techniques may invalidate some of the above assumptions,


77

to convert evaporative test- results to g/mi. Reference 36 has sug-
gested that an appropriate expression for converting evaporative-

emission results to g/mi is given by:

evaporative HC emissions) _ dirunal losses) VA
( in g/mi in g/test y (niles per day) +

running and hot-soak losses) / (niles per trip)

in g/test (7)

Suitable average values of miles per day and miles per trip are 34 and
7.5, respectively.

Two different methods have, been developed for collecting and
measuring evaporative HC emissions. Presently, the method used by the
federal government for certification of evaporative emission-control
systens””. is based on measuring the weight of fuel vapor absorbed in
carbon canister traps. The traps are connected to the fuel tank vents
and to the carburetor external vent during the course of the test.
After the test is completed, the traps are disconnected from the
vehicle and weighted to determine if the 2.0 g/test standard is met.
The second test method, the Sealed Housing for Evaporative Determina-
tions (SHED) method, 2” is more comprehensive. Basically, the SHED
method involves placing the vehicle in a sealed enclosure throughout
the test, and the HC concentration in the enclosure at the end of the
test, measured with an FID, is used, to determine the mass of HC
evaporative emissions. Further discussion of the SHED method may be
found in References 38 and 39.

A study"? employing the SHED method to determine HC evaporative
emissions reported that average evaporative, HC emissions for 55
preevaporative-controlled vehicles was about 37 g/test. Based on
these results, it has been estimated that evaporative emissions from
precontrolled vehicles (i.e., pre-1971 model-year vehicles) were
approximately 3 g/m?

The results of evaporative-emission certification tests for
model years 1971-1974, based on the carbon canister trap method, are


2.0 INTRODUCTION

2.1 Purpose and Panel Organization

The National Academy of Sciences (NAS), through its Committee on
Motor Vehicle Emissions (CMVE), initiated a study of automobile
emission-control technologies at the request of the United States
Congress and the. Environmental Protection Agency (EPA) in October 1973.
Particular emphasis in this study was to be placed upon systems and
engines that can meet various levels of NOx emissions and upon the
question of fuel economy, In order to assess the feasibility of
meeting emission standards and the relative merits of present and
alternate automotive technologies, CMVE required information relating
to the reliability and reproducibility of emissions and fuel economy
measurements.

The Emissions and Fuel Economy Test Methods and Procedures Consultant
Panel, established by CMVE, was organized in January 1974. The charge to
the Panel was to assess present and projected test methods and pro-
cedures pertaining to both regulated emissions and fuel economy of
light-duty motor vehicles (LDMV).

Panel members made site visits to most domestic automobile manu-
facturers, various state and federal agencies and a number of other
organizations concerned with automotive emissions and fuel economy
testing to gather data from which to draw conclusions. Information
from nondomestic automobile manufacturers was collected at a meeting
in Washington at which many such companies were represented. A
number of foreign organizations concerned with testing were also site-
visited. In addition, data were collected from the open literature,
material presented at technical meetings and from various professionals,
Appendix A lists the organizations visited or interviewed, and Appendix
B contains a typical questionnaire that was sent to most organizations

prior to the visit.


47

4.4 Factors Affecting Statistical Variability of Exhaust-Emission

Measurements in CVS-CH Tests

A schematic diagram of the relationship between the various
factors influencing the overall uncertainty of measured mass emissions
for a given CVS-CH test is shown in Figure 4.2. (See Section 4.2 for a
description of the CVS-CH test.) Inspection of Figure 4.2 indicates
that the overall uncertainty of mass emissions is due to the uncertainty
in measurement of both the concentration of. the pollutants and the
volume of gas collected in the exhaust sample bags.

General Motors Corporation”? has estimated the sources of vari-
ability and the probable relative contribution for mass-emission errors
in the CVS-CH test as shown in Figure 4.3. These results are based on
tests of four vehicles with HC, CO and NO, emissions ranging from 0.2 to
0.4, 2.0 to 4.4 and 1.0 to 2.4 g/mi, respectively.

Klingenberg et al. 27 have recently discussed errors associated
with the CVS-CH test and concluded that the overall measuring un-
certainty will be largely due to vehicle variability if the vehicle
variability is in the range of 10% to 20% of its mean emission value.
They also concluded that the other factors influencing the uncertainty
in mass-emission measurements will predominate the overall measuring
uncertainty only when vehicle variability is less than approximately
5% of its mean emission value.

The Ford Motor Company created an emissions correlation task force
in October 19737? and charged it with the responsibility of evaluating
the importance of various factors on the variability of vehicle mass-
emission measurements. The results of a three-phase program, including
audits of emission-test facilities at various laboratories, development
and implementation of a statistically designed program to assign pri-
orities to and quantify factors that significantly affect emission-test
results and a correlation test program have been reported.


89

Some concerns have been raised over the methods that are presently
employed to determine the deterioration factors of durability-data cars
that are subsequently used in the certification procedure, It has been
shown that the statistical variability associated with the determination
of deterioration factors may reflect the special circumstances of the
test rather than the capability of the underlying technology. This idea
is particularly relevant when it is realized that deterioration factors
are often obtained from emission tests on a single durability data car.
An averaging procedure over a larger group of "similar vehicles" might
be preferable for deterioration factor calculations. However, if
averaging is used too extensively, the averaging will treat all vehicles
and systems on equal terms, and attractive technologies may be counter-
balanced by less desirable technologies.

Since the deterioration of emission-control systems has been
assumed to take place in a linear fashion, it has been suggested that a
simple difference technique rather than the ratio technique, which is
presently employed for determining deterioration factors, might be more
appropriate. Sufficient data were not available to determine which of
these two techniques .is more appropriate.

Finally, the possibility of modifying the present HC exhaust-
emissions standards and measuring techniques to include only reactive
HC's has been discussed. This proposal is presently under consideration
by EPA and it is suggested that the resolution of this issue should be
deferred until the additional data collected by EPA have been analyzed
from both a technical feasibility and cost-benefits point’ of view.


80/-

70-
— 60)-
2
E
3S
6
i 50-
Ww 50)
x
9
g 1 20 Production Cars, 1967-1973
6 40 © 4 Prototype Advanced Emission Cars (all catalyst)
a x Diesel
x © Stratified Charge (Proco)
2
fe}
= 30
2
fo}
a
ra
<
3)

20;-

10}-

Ped
=== ——
0 ¢ FF Sr Ft Or FS Se Eee

20 40 60 80 100 120
TEST AMBIENT TEMPERATURE (°F)

FIGURE 4,6 Effect of Ambient Temperature on CO Exhaust Emissions
During the CVS-CH Test

REF, 33


29

the appropriate standards at the same time in
at least one out of two tests for a single
vehicle. For the special case where the
three pollutants are independent and the
values of (s,/%,) and Gi, /4,) are the same
for each pollutant, the symbol P*(2,3,1}

is used.

P (2,3,4) - the probability that all three pollutants
(HC, CO and No.) are simultaneously below
the appropriate standards in at least one
out of two tests for four independent ve-
hicles in an engine family. for the special
case where the three pollutants are indepen-
dent and (8, /%,) and /AD values are the
same for each pollutant, the symbol P* (2,3, 4)
is used.

The results listed in Table 4.1a, which are based on an assumed
normal probability distribution, can be utilized to determine the
various probabilities, in percent, listed above as a function of the
two parameters &/AD and (,/*,). The main body of Table 4.la,
contained within the solid lines, represents specific values of a
vehicle's true adjusted emission mean dividied by the appropriate
emission standard, (e,/4,) = OF,) CH Dag/Ay in percent. The numerical
values in the far left-hand column of the Table represent specific
values of the parameter (s,/%,) in percent. Numerical values of
PAL), F, (2), P*'(2,3,1) and P* (2,3,4) in percent are obtained from
Table 4.1a as functions of (8, /%,) and C/A.) The equations used
for calculating the entries in the Table are listed in Table 4.1la.

The utility of Table 4.la can be illustrated by considering some
examples:

4. Determine the required value of the true, adjusted emission

mean aS a percent of the appropriate standard GMA, in %)


TABLE 4.7

Summary-of Emission Test Variability for a Catalyst Equipped Vehicle at Two Laboratories!

Laboratory No. of tests No. of Cells HC co NOx con
x 8 x &§ x 8 z 8&8
x x x x
Chrysler 16 4 0.54 27.8 7.0 25.8 2.65 2.2 667.2 10.6
EPA 3 1 0.43 4.9 5.6 19.7 2.65 3.3 647.9 2.1
1-

— mean emission value on CVS-CH test in g/mi

Xie

standard deviation as percent of mean

REF, 26

1


110

The advantages of test methods based on the use of a chassis dyna-

mometer include:

1.

2.

3.

4.

The test can be conducted independent of local weather condi-
tions.

Since test cell conditions can be controlled, correction fac-
tors for the effect of ambient conditions on experimental
results are minimized,

The same driving cycle (speed versus time trace) can be fol-
lowed within specified close tolerances.

Fuel economy and exhaust emissions can be simultaneously mea-
sured,

There are also a number of disadvantages to employing a chassis

dynamometer test procedure, These include:

1.

3.

Total load simulated on the chassis dynamometer may not accu-
rately duplicate the rolling resistance and aerodynamic drag
experienced by the vehicle on the road.

In general, the cooling fan airflow characteristics in a dyna-
mometer facility do not exactly reproduce the airflow charac-
teristics of a moving vehicle. Therefore, the effect of
vehicle warm-up may be slightly different than that encoun-
tered on the road,

The present method of accounting for the existence of air con-
ditioning, by setting in the dynamometer a 10% increase in
road load horsepower at 50 mph, may not exactly duplicate the
overall effects of air conditioning on fuel economy.

The large discrete inertia-weight differences, 250 1b and
500 1b on the chassis dynamometer presently employed for fuel
economy testing that are used to simulate load may bias the
simulated load too high or too low for a given vehicle due to
the vehicle's true inertia weight being too close to the cut-
off point between inertia-weight classes. Due to the manner
in which inertia-weight loads are presently set in the CVS-CH
test method, a vehicle at the upper limit of a given weight
class receives a fuel economy advantage over its expected
road fuel economy in the range 5% to 8%. Conversely, a vehi-
cle at the low end of the inertia-weight class receives a
penalty in the range_5% to 8%. These computations were
obtained using EPA's“ simple correlation of fuel economy
versus inertia weight.


TABLE 4.9

Summary of General Motors Exhaust Emission Audit Tests

in California for the Period 1/1/74 thru 3/31/74

Engine No. HC co NOx
Make Family of tests a 8 - s - 8s
x = x = x =
x x x
Chevrolet Al 198 1.9 22 21 24 1.6 19
A2 130 2.0 19 24 27 1.5 19
A3 234 1.7 32 26 29 1.5 21
A4 844 1.8 26 29° 32 1.4 21
AS 63 1.9 36 28 32 1.5 23
Pontiac Bl 91 1.9 18 28 23 1.5 22
B2 3 1.9 8 16 10 1.5 15
B3 46 2.4 16 23 49 1.5 15
Oldsmobile cl 75 2.5 19 24 38 1.5 17
c2 46 1.6 31 21 29 1.4 24
Buick DL 48 2.4 25 23 40 1.5 21
D2 49 2.2 25 27° 22 1.2 15
D3 27 2.6 23 23° 21 1.7 15
Cadillac El 109 2.1 32 24 40 1.8 36
1s g/mi

= standard deviation as percent of mean

REF, 23

9”


131

the second method is based on driving the vehicle on a chassis dynamome-
ter. Both of these procedures have distiiict advantages and disadvan-
tages. It has been concluded that there is no inherent technical reason
for eliminating the use of chassis dynatiometers from fuel economy test-
ing if it can be shown that they adequately simulate the actual’ iner-
tial, aerodynamic, rolling resistance and accessory loads experienced
by a vehicle as it traverses the driving cycle. Unfortunately, the
results of definitive studies designed to evaluate the ability of chas-
sis dynamometers to accurately simulate vehicle loads under a wide
variety of conditions and to evaluate errors in fuel economy imeasure-
ments associated with specified errors in dynamometer load simulation
have not been reported.

Based on the limited data presently available, one can speculate
that fuel economy tests incorporating chassis dynamometers, with suit-
ably fine inertia-weight controls, can be successfully employed to
determine fuel economies for urban driving cycles where inertia forces
and idle conditions rather than road loads dominate LDMV fuel consump-
tion. In addition, limited data have indicated that fuel economy data
obtained on chassis dynamometers and road or track tests can be made to
correlate well even for nonurban driving cycles, where road loads domi-
nate vehicle fuel consumption, if care is taken to set the dynamometer
loading so that vehicle coast-down times obtained on the dynamometer
closely match vehicle coast-down times obtained on the road. ‘The
results of another study indicate that fuel economies for the EPA high-
way driving cycle as measured on a Clayton-type: dyno, where the road
load at 50 mph was set according to the "cook book" method established
in the Federal Register, did not correlate well with results obtained
on a test track. In all cases, the fuel economies measured on the dyno’
were larger than the corresponding values measured on the track and dif-
ferences between the two values ranged from 4% to 16%. These results
indicate that certain vehicles may obtain significantly higher fuel


42

laboratories were measuring CO, values that fell outside the mean plus

or minus two standard deviations. The co, standard deviation as percent
of the mean was approximately 1.8%. This may be due to systematic errors
associated with co, measurements that are encountered in some labora-
tories.

Klingenberg et al?” have reported the results of a round-robin
emission test carried out on a "relatively stable" vehicle at various
laboratories in the USA and at Volkswagen AG in Germany during 1973.

The results of these tests are presented in Figure 4.1. In order to
permit comparison between the data obtained, the mean value and standard
deviation first obtained for 13 tests at W AG are plotted in Figure 4.1.
Inspection of these data indicates that the values obtained at some
laboratories do not fall within the mean plus or minus two standard
deviations. A t-test was performed on all measurements obtained and

the computations indicated that the results of the tests differ sig-
nificantly among the different laboratories. It was reported that at
the time these data were collected some of the mean values obtained
were suffering from systematic errors amounting in some cases to as
much as 30%,

The vevma® reported the results of a study designed to compare
the emissions data variability of the CVS-CH versus the CVS-C test
procedure. The data utilized in this study were obtained from the
Single Catalyst Fleet Riverside data from Ford Motor Company's status
report to EPA dated October 13, 1972, the 1973 MVMA Correlation Cross
Check Program data and 1973 California 2% quality audit data.

A fleet of eight vehicles representing four engine families (two
vehicles per family), equipped with 1975-type single-catalyst emission
systems was tested by Ford Motor Company as part of the Riverside test
program. This program involved conducting back-to-back CVS-CH tests
on the eight vehicles at each of the mileage intervals prescribed by
the Federal Durability Test Procedure. These tests were conducted at a
single facility under highly controlled test conditions, and, consequently,


TABLE 4,15a

Monte Carlo Simulation of Possible Variability in DF
as a Function of Test-to-Test Variability

TRUE DF = 1.0

TRUE DF = 2.0

EMISSIONS -

AT cov = 10% cov = 20% cov = 30% cov = 10% cov = 20% COV = 30%
“gm | oe | c*| of [2] oe [2%] ol et] oe [2%] oe (2?

Al 978 8 |1.00 | 15 1.20 | 37 2.11 9 2.12] 39 2.36 | 50
1.5 931 9 11.05 | 22 966) 32 2.02 6 1.99 | 26 2.19) 48
3.1 949 12 | .980] 19 1.05 | 24 2.06 | 12 2.29] 29 1.99 |. 22
9.0 1.03 12 986] 17 1.13 | 24 2.03 9 1.97 | 21 2.22 | 34
15 983 11 .998] 19 +901] 23 1.99 lL 2.24 16 1.70 | 20

cov

Kila
1 i)

3|
u

Fleet Size = 10

test-to-test coefficient of variation, %

mean deterioration factor from Monte Carlo Simulation

deterioration factor coefficient of variation % from Monte Carlo Simulation

REF. 57

Te


81

the 1971 and 1972 model-year evaporative emissions obtained in Denver
has been attributed to the differences in fuel volatility that.were
employed during the testing. The 1971 Denver vehicles were tested
using commercial winter-grade fuel of high volatility (RVP = 11.7 psi),
and the 1972 vehicles were tested using the standard test fuel of
summer-grade volatility (RVP = 8.8 psi). Significantly higher
evaporative emissions are to be expected when testing with high-
volatility fuel as compared to lower-volatility fuel. The same situa-
tion occurred during tests of model year 1957-1971 vehicles in Los
Angeles, but the effect on the overall average is’ less pronouncéd since
a wide variety of vehicles were tested at random times with both types
of fuel. Epa‘? has indicated that the test data obtained during the
Fy 1971 surveillance program will be reanalyzed in the near future to
account for the effects of fuel volatility and other procedural factors
on the evaporative emissions.

Standard test fuel was employed in both the Denver and Los Angeles
evaporative-emission tests for the 1972 vehicles, and the differences
in values reported in Table 4.17 have been attributed to the effect
of barometric pressure (i.e., 24.5 in. Hg at Denver as compared to
30.2 in. Hg at Los Angeles).

Comparison of the results. listed in Tables 4.16 and 4.17 indi-
cates a significant difference in the assessment of the relative
importance of evaporative HC emissions on the overall strategy designed
to control HC emissions to the atmosphere. The 1975-76 Federal
Interim Standards and the 1975-76 California standards for HC exhaust
emissions are 1.5 and 0.9 g/mi, respectively. While the SHED-method
data are relatively limited, they nonetheless raise a very important
issue. These data indicate that vehicles which are supposed to have
95% effective evaporative-emission controls, have evaporative HC
emissions that are larger than the 1975-76 exhaust-emission standards
when both are compared on}grams-per-mile basis. It has been estimated

that refueling losses amount to approximately an additional 0.4 g/mi.“?


36

TABLE 4.3

Summary of Emission Results for 16 Tests on a Chevrolet
Impala Equipped with an Oxidizing Catalyst in a Single Test
Cell

Variable HC co NO, CO,
Composite-CVS-CH 0.37 4,44 2.32 862.1
Emissions

(g/ml)
Standard Deviation 27 7 3.4 1.2

(Percent of Mean)

Contribution to 87 94 33 -
Total Grams from

"Cold Transient"

Phase (percent)

Contribution to 99 99 25 =
Overall Standard

Deviation in "Cold

Transient" Phase

REF. 23


Table 5.4 Comparison of Fuel Economies for Highway Cycles Measured on a

Track and on a Dynamometer

Fuel Economy (mpg)

Dyno Test Track Tests

Engine EPA EPA SAE

Displ. Inertia Highway Highway Interstate 55
Body (CID) Weight Cycle __byele Cycle
‘AY Body 225 3,500 25.07 22.6. 21.5
'B' Body 318 4,000 20.9 17.5 1754
"BY Body 360 5,000 18:1 16.6 16:5
'B' Body 360 5,000 18.6 15.9 16.1
'C! Body 400 5,000 17.4 16.2 16.2
‘C' Body 400 5,000 14.6 14.0 14.4
'C' Body 440 5,000 16.7 - 15.8
'C' Body 440 5,000 17.6 16.4 16.4

Iyyno-load set as per Federal Register,

REF. 26

ZeT


106

influence the fuel economy of a LDMV. Based on these discussions, it
can be concluded that the relative fuel economy of various vehicles
can only be reported with any degree of certainty if standardized fuel

economy test methods and procedures are developed,
5.3 Test Methods and Procedures

The critical elements in any standardized fuel economy test method
and procedure must include: a representative standard driving cycle or
cycles; a method to determine the mass or volume of fuel consumed and
the distance traveled during the test; and a procedure for simulating
vehicular loads encountered during the course of the driving cycle,

Questions concerning the development and choice of appropriate
fuel economy driving cycles have been discussed in Section 3.4, These
considerations led to the conclusion that since driving patterns change
with time and two drivers would tend to drive the same route in a dif-
ferent manner, it is impossible to develop an absolutely typical fuel
economy driving cycle, However, it was recommended that two standard-
ized fuel economy driving cycles, one designed to represent urban fuel
economy and one designed to represent highway driving, be adopted to
evaluate the relative fuel economies of various automotive designs and
to compare the relative fuel economies of one vehicle versus another
in order to allow rational consumer choice,

Two techniques have been commonly applied to measure fuel economy.
In the first technique, a direct measurement of the mass or volume of
fuel used during the course of the test is obtained from appropriate
instrumentation and this data is used in conjunction with the distance
traveled and conversion factors to compute the vehicle fuel economy in
miles per gallon (mpg). The second technique may be termed the Carbon
Mass Balance Method. When employing this technique, the HC, CO and
CO, emissions are collected and measured during the course of the driv-

2
ing cycle as in the CVS-CH test procedure. Since the mass of carbon


115

Table 5.1 Summary of Round Robin Fuel Economy Test Program

No. of Laboratories

No. of Tests

Mean CVS Fuel Economy
Standard Deviation of Tests
Percent Std, Dev. of Tests

Range of Fuel Economy

Compact Conipact. Full Size

6 Cyl. v-8 v-8

5 5 6

8 7 8

15.6 MPG 11.8 MPG 11.0 MPG
+95 MPG -45 MPG +97 MPG

6.1% 3.8% 8.8%

14,3-16.7 11.3-12.4 9,6-11.0

Dynamometer Horsepowers Set Per Federal Register

REF, 26


Table 5.3 Fuel Economy Measurements as Measured on Both Road Track Tests and Dynamometer Tests

Vehicle Company Load Facility Corrected Fuel Economy
SAE Urban SAE Suburban SAE 70 mph Interstate
Cycle Cycle Cycle
(mpg) (mpg) (mpg)
1973 Dodge Charger
IW = 4,400
CID = 318-2V Chrysler Track 10.2 17.3 15.8
reve Track 10.3 17.4 16.1
Ford Track 10.2 16.7 15.4
Chrysler Track 10.0 17.2 15.8
Shell River-Road
Highway 10.1 16.5 15.
Shell Dyno 9.9 16.3 15.0
1973 Buick Century
IW = 4,620
CID = 350-4V Chrysler Track 9.9 15.5 14.0
fev Track 10.1 15.6 13.8
Ford Track 9.7 15.2 13.7
Chrysler Track 9.9 15.5 14.0
Shell River Road 10.3 15.9 14.0
Shell Dyno-normal
load 10.0 15.6 14.3
Shell Dyno-light 9.8 15.6 14.6
1973 Ford Pinto
IW = 2,740
CID = 122-2V Chrysler Track 15.4 22.4 18.3
feud Track 15.8 22.5 18.8
Ford Track 15.5 22.4 18.5
Chrysler Track 15.6 22.8 18.9
Shell River Road 16.2 22.7 18.7
Shell Dyno-Load, * 14.3 20.0 16.1
Shell Dyno-Loady * 14.9 20.8 18.3
Shell Dyno-Load3 * 14.7 22.6 19.2
Shell Dyno-Load, * 15.2 25.4 23.0

*Dyno-Load, to Dyno-Load, represent decreasing dynamometer loading. REF, 52

O2@T


57.

58.

59.

144

Bowditch, F.W., General Motors Corporation, private communication
to R.A. Matula, September 1974.

EPA Methodology Report, Appendix B, Decision of the Administrator
on Remand from the United. States Court of Appeals for the District
of Columbia, April 11, 1973.

Kirchhoff, W., National Bureau of Standards, private communica-
tion to R, A. Matula, June 1974.


A.

B.

148

APPENDIX B

General Questions to Organizations Prior to Site Visit

from the Consultant on Testing
of the
Committee on Motor Vehicle Emissions

Test Cycles

1. Discussion of the advantages and disadvantages of the application
of the 1975 FIP as a basis for emissions standards testing and
for the determination of urban fuel economy.

2. Summary of any studies that have been carried out to evaluate
typical driving patterns in urban, nonmetropolitan and rural
areas. Items of particular interest include distribution of
number of trips versus trip length, percentage of trips
initiated from "cold start" versus "hot start," average trip
speed, number of stops per mile, etc.

3, Constructive evaluation of EPA's recently proposed nonmetropol-
itan fuel economy driving cycle.

Test Methods and Procedures

1. Emissions

a.

Discussion of any special shortcomings or problems associated
with present emissions test procedures, special emphasis
should be given to CVS sampling system, instrumental
limitations for pollutant measurements, etc.

Discussion of relative advantages and disadvantages of
modifying HC standards to incorporate only a non-methane
hydrocarbon standard,

Summary of work to date on development of test methods and
procedures developed to measure HS, So, and sulfates in
automotive exhaust.

Discussion of the accuracy of present gas calibration
standards used in emission testing and its effect on
accuracy of emission measurements.

Discussion of the contribution of various factors to the
statistical variability of emission tests.


CONSULTANT REPORT

to the
Committee on Motor Vehicle Emissions
Commission on Sociotechnical Systems
National Research Council
on

EMISSIONS AND FUEL-ECONOMY TEST METHODS AND PROCEDURES

PREPARED BY:

Richard A. Matula

Washington, D.C.

September 1974


16.

17.

18.

138

Limited data presently available indicate that fuel economy
tests incorporating chassis dynamometers, with suitably fine
inertia-weight.controls, can be successfully employed to deter-
mine fuel- economies for urban driving cycles where inertia
forces and: idle conditions, rather than road ‘loads, dominate
LDMV fuel consumption.

Limited ‘data have indicated:that fuel economy data obtained on
chassis dynamometers and. road or track tests can be made: to
correlate well.even for nonurban driving cycles, where road
Toads dominate vehicle fuel consumption, if care is taken to
set the dynamometer loading so ‘that vehicle coast-down times
obtained on the dynamometer closely match vehicle. coast-down
times obtained on the road. However, the results of another
study indicate that fuel economies for. the EPA highway driving
cycle as measured on a Clayton-type dyno, where the road load .
at 50 mph was set according to the "cook book" method estab-
lished in the Federal Register, did ‘not corrélate well with
regults obtained on a test track. In all cases, the fuel
economies measured on the dyno were larger than the corre~
sponding values measured‘on the track and differences between
the two values ranged from 4% to 16%. . These results indicate
that certain vehicles may obtain significantly higher fuel
economies than are: acttally.warranted on the EPA highway cycle
using present-EPA fuel ‘economy, test methods and procedures.
Fuel economy measurements: are considerably more reproducible
than’ emission measurements, Data indicate that fuel economy
measurements employing chassis dynamometers for an urban driv-
ing- cycle (e.g., CVS-H, CVS-C, and CVS-CH tests). are reason-
ably repeatable. In fact, the data indicate that the vari-
ability of measured fuel economy in terms of the standard

‘deviation as a percent of the mean in a given cell, from cell

to cell at a given laboratory ‘and from laboratory to laboratory


99

bias, bias-belted and radial. Typical rolling resistance coefficients
for these three types of tires vary as shown in Figure 5.5,48

The power to overcame aerodynamic drag, (HP) sero? is given by

cup), = SAY (3)

aero
where
Pt density of air surrounding the vehicle

cy = vehicle drag coefficient

A = projected vehicle frontal area
The drag coefficient, Cy, is in the range of 0.4 - 0.6, and the pro-
duct CgA ranges from approximately 8 to 15 ft? for most LDMV.

The total power required to overcome road load can be computed by
adding Equations (2) and (3)

3
CHP) oad = Peo + PP aero = mv + 2A CANT (4)

road
load

Inspection of Equations (1) and (4) indicates that the vehicle

aero

inertia weight has a direct contribution to two out of the three power
terms, The third term, LAV » is also indirectly influenced by the
vehicle's weight in that heavier vehicles may have larger frontal sur-
face areas, A, than lighter vehicles.

The relative magnitudes of the horsepower required to overcome
rolling resistance, aerodynamic drag and various acceleration rates
for a "typical" 4,500 1b inertia-weight vehicle are shown in Figure
5.6. In these computations, the rolling resistance coefficient f,
the cA term and the air density at standard conditions were taken to
be 015, 13 et? and .074 1b/£t?, respectively. In order to compare
CHP) ce with the other power requirements, the acceleration horsepower
for two acceleration rates of 4.84 ft/sec’ (maximum acceleration rate
in CVS-CH cycle) and 2.0 ft/sec” is also plotted in Figure 5.6.

In general, due to the magnitude of the coefficients and the
cubic dependence on velocity, the aerodynamic horsepower, (HP)

aero’
is insignificant in urban low-speed driving when compared to the


Measurement of the Concentration

No. of Data
Average, x
Median
Range
Estimate of Standard Deviations

s/x, %

TABLE 4.

13

HC co co2
(ppm, propane) (ppm) M)

12 18 17
100.85 1163 1.44
100.80 1166.5 1.44

98.0 - 103.7 1100 - 1203 1.35 - 1.50

1.78 24.84 0.04

1.8 2.1 2.8

REF. 31, 32

of Pollutants in an Unknown Sample at Many Laboratories

No
(ppm)
26
158.6
157.5
140.75 - 180.0
8.48

5.3

6S


45

TABLE 4.8

Summary of Emission Test Data for CVS-CH Tests on the "Riverside"
Catalyst Equipped Fleet!

Engine
Family HC co NOx
x 8 x g x s
x x , x
A 0.748 29 4.50 20 2.55 13
B 0.586 9 5.37 31 2.51 8
c 0.423 17 2.69 24 2.32 9
D 0.679 9 4.21 17 2.90 8
Fleet 0.607 19 4.19 26 2.56 10
1 xr grand mean of emissions on CVS-CH test, g/mi
3 - standard deviation as percent of the mean

REF. 28


94

vehicles when compared to light vehicles. Also, in a similar manner,
the addition of accessories to a vehicle, such as an air conditioner,
not only requires energy for its operation but also increases the
inertia forces that the vehicle must overcome. Therefore, it is not a
simple matter to optimize simultaneously all of the important parame-
ters influencing fuel economy to achieve. the "best" fuel economy.
Indeed, it is often even difficult to obtain a base line in fuel econ-
omy for comparison purposes since car weights have fluctuated, base
engines have changed, some models have been introduced and others
dropped etc.

Based on a multiple regression analysis on the measured fuel
economies of over 1,400 vehicles as determined for a cold-start urban
driving cycle, it has been concluded that vehicle inertia weight is
the single most important vehicle parameter affecting fuel economy.2
These results indicated that a typical vehicle in the 5,000 lb inertia-
weight class has approximately a 50% lower fuel economy than a typical
vehicle in the 2,500 lb inertia-weight class when the CVS-C driving.
cycle is used for the comparison,

Since vehicle weight is seen to be an important factor in fuel
economy, comments on trends in vehicle weight are relevant. The
results of a recent study“? indicate that the curb weight of passenger,
cars in all market classes has steadily increased with time in the
period between 1956 and 1974, (Note: Inertia weight is generally
defined as curb weight plus 300 lb.) The conclusions reached in
Reference 47 are summarized below:

1. Passenger cars in all market classes have shown a marked and
steady increase ‘in curb weight with time. This curb-weight
‘increase trend is independent of manufacturer, For example,
Chevrolet and Ford standard-size cars increased approximately
1,100 1b (33%) and 980 1b (29%), respectively, between 1956 and
1974. In the intermediate class, the Fairlane/Torino series
increased curb weight by approximately 1,100 1b (36%) from 1962 -
to 1974;' the ‘Chevelle increased curb weight 900 1b (28%) from 1966
to 1974, In the compact class, from 1962 to- 1974, the, Chevy II/
Nova series increased curb weight by 940 1b (36%), while the
Valiant increased by 620 1b (24%).


19

The Society of Automotive Engineers (SAE) Technical Board has
recently created the SAE Fuel Economy Measurement Procedures Task and
charged it with a two-phase program to develop fuel economy test
Procedures and driving cycles and to suggest procedures that can be
utilized to evaluate the effect of vehicle parameters on fuel economy.

The SAE Task Force reviewed the various manufacturers' driving
cycles, and concluded that these cycles, though not identical, were
similar and produced fuel economy values that did not greatly differ.
Based on these considerations, the SAE has recommended the adoption of
four fuel economy driving eyeles!® including: (a) an urban cycle--
designed to simulate driving conditions in the central business district
of a large city; (b) a suburban cycle--designed to simulate the driving
conditions in suburban areas of a large city; and (c) two inberstate
cycles, one with an average speed of 55 mph and one with an average
speed of 70 mph--designed to simulate driving conditions on an express-
way. All of these cycles are detailed in Reference 18, and speed versua
time traces for these cycles are shown in Figure 3.2. The important
characteristics of the proposed fuel economy driving cycles are listed
in Table 3.3, u

Inspection of the data listed in Table 3.3 indicates that the
primary differences between the EPA urban driving cycle and the SAE
urban driving cycle are the average cycle speeds of 21.2 mph and 15.5
mph, respectively, the number of stops per mile, 2.0 and 4.0
respectively, and the percent of time spent in the various driving
modes, More than one half of the time in the SAE urban cycle is
represented by a cruise condition while only approximately 8% of the
time is spent in the cruise mode for the EPA urban cycle, Correspond-
ingly more time is spent in the acceleration, deceleration and idle
modes in the UDDS cycle than in the SAE cycle, Since the SAE urban
cycle is designed to represent driving in the central business district


TABLE 3.2

Comparison of Urban Driving Patterns And Driving Cycles

CYCLE OR CITY AVERAGE PERCENT TIME IN EACH MODE PERCENT OCCURANCE IN EACH MODE
SPEED -MPH % IDLE % CRUISE % ACCL % DECEL % IDLE % CRUISE % ACCEL % DECEL

New York City 21.6 17.45 26.49 29.12 26.95 7.60 42.40 25.43 24.57
Chicago 24.5 14.11 30.86 28.30 26.78 7.81 42.19 25.38 24.62
Cincinnati 25.9 11.34 30.72 30.89 27.06 7.42 42.58 25.44 24.57
Houston 27.7 11.30 36.80 27.35 24.58 6.97 43.03 25.43 24.57
Los Angeles 29.3 10.13 34.28 29.78 25.82 7.60 42,40 25.04 24.96
5-City Comp. ‘)) 25.8 12.87 31.83 29.08 + —-26,23 7.48 42,52 25.34 24.66
5-city Comp, (2) 26.0 13.06 31.50 29.16 26.30 7.59 42.41 25.26 24.74
L.A. 4) 21.0 13.56 27.25 31.73 27.49 9.50 40.50 25.26 24.74
pa, 44) 17.4 18.43 25.42 29.82 26.28 10.70 39.30 25.41 24,59
wos 9) 19.7 18.2 30.2-27.7—S 23.9 12.0 38.0 26.7 23.3
original 1.a.-4° 20.9 13.6 27.3.0 31.7275 9.5 40.5 25.3 24.7

(1) Cities weighted equally.

(2) Cities weighted by vehicle registration.

(3) Results are for defined hours 9:00 a.m. - 11:00 a.m. and 1:00 p.m. - 3:00 p.m.
(4) Results are for off-hours 7:00 a.m. - 9:00 a.m. and 3:00 p.m. - 5:00 p.m,

(5) Data from Reference 6.

REF. 6, 10


98

Figure 5.4 indicates ‘that a given weight increase has-a more signifi-
cant effect on fuel economy for lighter cars than for heavier cars.

The significance of inertia weight as related to vehicle fuel
economy for any given driving cycle on a level road can be readily
explained by considering the power that must be supplied to the drive
wheels of the vehicle in order to overcome inertia and road load.
Power is required to accelerate. the vehicle from one speed to another,
and once the vehicle is in motion, the’ drive wheels must provide power
to overcome ‘the road load, Road load is' usually considered to be due
to the sum of vehicle rolling resistance and’ aerodynamic drag.

The acceleration horsepower is readily computed in terms of the
acceleration of thé vehicle multiplied by the vehicle speed

(HP) =mdv v
acc at
where
CHP) ace = horsepower required to overcome acceleration load

mass of vehicle

m
v = vehicle speed

av
dt

Various correlations have been suggested to determine the power

vehicle acceleration

required to overcome vehicle rolling resistance. Many organizations
have recommended that the power required to overcome rolling resis-
tance, CAP) oi? can be accurately represented by the following rela-
tionship

(HP) mfv

roll ~
where m and v are as defined above and f is thetire rolling resistance
coefficient. The. parameter f is difficult to determine accurately and
tends to depend on a number of parameters, including tire type, vehi-
cle speed, ambient conditions; tire-inflation pressure, road-surface

conditions, etc, There are three common types of tires available--

q)

(2)


27

fails, it may be tested a second time. If the car passes the second
test, it is considered to havecertified. Every emission-data car in
an engine family must pass the certification procedure before the
family can be certified.

The CVS-CH test method is utilized for measuring true mass emis-
sions for 1975 model-year and later vehicles. The vehicle is tested
on a chassis dynamometer after a temperature-conditioning period of at
least 12 hours between 60°F and 86°F. The key is turned on and exhaust
gas sampling begins immediately, whether the engine starts or not, and
continues until the engine stops. The entire exhaust gas stream is
mixed with purified ambient air and passed through a heat exchanger
to make a constant volume flow of variably diluted exhaust gas.
Samples, drawn at a constant rate from this diluted stream, are col-
lected and analyzed for HC, CO,NOx and C02 by specified methods. The
driving cycle for the CVS-CH test is based on the UDDS. The test is
initiated from a cold start, and after deceleration ends at 505
seconds (see Figure 3.2), the diluted exhaust flow is switched from
the "cold transient bag" to the "stabilized bag." Diluted exhaust is
collected in the stabilized bag during the remainder of the 1372-
second driving cycle. After a 10-minute shutdown, the engine is
restarted in a hot condition and the first 505 seconds, or the trans-
ient phase, of the driving cycle is repeated. During this phase of
the test, the diluted exhaust is collected in the "hot transient bag."
During the "stabilized phase" of the hot-start run, it is assumed that
the vehicle would produce the same emissions as were produced during
the stabilized phase of the cold-start cycle. Therefore, it is not
necessary to repeat the stabilized phase of the hot-start cycle.
Emissions in the cold transient bag and hot transient bag are weighted
and are added to the emissions in the stabilized bag to obtain the
CVS-CH mass emissions, These weighting factors reflect the EPA's
estimate that 43% of the vehicle trips, on a national average, are


108

were both a fuel weight and HC, CO and CO, data. The same type of

calculation yielded a 3.3% difference with the standard deviation of
the difference being 8.1%. Conversations with a number of individuals
from various laboratories during the course of the present study sug-
gested that excellent correlation can presently be obtained between the
two fuel economy test methods discussed above.

Recent data obtained from an automotive company?? in which three
vehicles were tested nine times each on both the CVS-CH cycle and the
EPA highway cycle have indicated that the standard deviation as a per-
cent of mean for fuel economy measurement based on fuel-metering tech-
niques and the Carbon Mass Balance method are approximately equal.

These results are given by:

s Ss
= x
Carbon Balance Fuel Meter
Cycle Method Method
CVS-CH 2.7% 1.9%
EPA's Highway 1.6% 1.9%

All of these results indicate that either the fuel meter method or
the Carbon Mass Balance Method can be successfully employed to accu-
rately determine fuel consumption if careful experimental techniques
and procedures are developed and followed during testing. Alternate
satisfactory techniques are readily available to determine distance
traveled during the test.

Once the fuel economy driving cycles and procedures for determin-
ing fuel consumption and distance traveled have been defined, one must
specify how the appropriate inertial and road loads are to be applied
to the vehicle as it traverses the specified driving cycle. Basically,
two alternate procedures have been suggested. First, there is the
obvious dynamic technique of simply driving the vehicle on the road or

on a test track with appropriate instrumentation to allow the driver to


129

by referring to Figure 5.9 that the hot start of the CVS-CH procedure
is initiated from a slightly less than fully warmed-up condition.

5.7 Summary

Some of the most important factors that influence the fuel economy
of LDMV include the driving cycle and the driving habits of individ-
uals, vehicle characteristics including inertia weight, the effect of
cold-start operation, particularly on short trips, and the state of
maintenance of the vehicle. It has been suggested that since’ driving
patterns change with time and that two drivers would tend to drive the
same route in a different manner, it is impossible to develop an abso-
lutely typical fuel economy driving cycle, However, since fuel economy
is strongly dependent on the driving cycle, it is important to develop
standardized fuel economy driving cycles and test methods and proce-
dures in order to evaluate the relative fuel economies of various auto-
motive designs and to compare the relative fuel economies of one vehi-
cle versus another. In order to obtain a reasonably accurate determi-
nation of the fuel economy of a vehicle, it is concluded that two
standard LDMV fuel economy driving cycles, one designed to represent
urban driving and one designed to represent highway driving, are needed,

It -has been shown that severe fuel economy penalties are incurred
when an LDMV is driven on a short trip that is initiated from‘a cold-
start condition. In addition, it has been shown that many automotive
trips are very short and that more vehicle miles are driven for trips
within 0.5 miles of 4.5 miles than trips over any other l-mile inter-
val. Therefore, it is concluded that in order to obtain economies that
are in good agreement with expected real-life, urban fuel economies, an
urban fuel economy test method and procedure should include both a cold-
start and hot-start phase.. The driving cycle associated with the
CVS-CH test method meets this requirement.


51

specific humidity on CVS-H, HC, CO, co,
sions were studied on the three inertia-weight test vehicles. Humidity

. * -
and No. & corrected)* emis

was an uncontrolled variable ranging from:20 to 66 gr/lb dry air. The
experimental results showed that the Ky correction factor for No. was
not correcting observed emissions such that observed emissions were
independent of humidity. Test results showed that ‘the HC and CO emis-
sions increased with increasing humidity for the 3000 and. 5000 1b
inertia-weight vehicles and had no.effect on the 4500 1b inertia-
weight vehicle. co,
vehicles. These results were reported to be consistent with published

emissions were not affected on any of the test

reports in that humidity increases HC and CO emissions and effects
vary with vehicle calibration.

The effects of barometric pressure on CVS-H emissions: of HC, CO,
co, and No. Oy corrected) emissions were also estimated, During. the
studies, barometric pressure was an uncontrolled variable ranging from
28.70 in. Hg to 29.51 in. Hg.

Analysis of results show that increasing barometric pressure by.
1 in. Hg decreases average HC and CO emissions 13.6% and 21.0%,
respectively, at 90% confidence. No, and co, were increased an
average of 12.5% and 7.7% at 90% confidence. The effect of barometric
pressure on HC, CO, No, and co, emissions on‘ the three vehicles varied
from -5.7% to -22.5%, -7.2% to -34.9%, -3.5% to 23.2% and 5.5% to 8.1%,
respectively.

Due to the nature of the CVS-H test, neither the effect of cell
ambinent temperature or vehicle soak-area temperature could be
determined. The effect of high ambient air-pollutant concentration
CHC ax = 10 ppm, CO ax = 17.9 ppm, No, max =~ 2.27 ppm and CO, max ~
700 ppm) on the variability of exhaust emissions was unknown, ‘but
considered to be insignificant,

* Correction factor presently employed in CVS-CH test method to cur-
rent No, emissions for humidity variations.


105

conditioning is 9% to 20%. In general, all power-assist devices decrease
the vehicle's fuel economy because they require additional power to
operate and add weight to the vehicle.

It is generally acknowledged that the fuel economy of many vehicles
has decreased due to the introduction of emission controls. However,
the magnitude of this decrease is a relatively controversial subject.
EpA2 has compared the fuel economies, measured on the CVS-C test cycle,
of pre-controlled vehicles (1957-1967 average) to the -fuel economy of
1973 vehicles as a function of inertia-weight class. Their results
indicated the fuel economy of vehicles in'all inertia-weight classes up
to 3,500 1b obtained slightly improved fuel economy even in spite of
the installation of emission controls while vehicles in the inertia-
weight class 4,000 1b and above have poorer fuel economy (ranging from
approximately 14% to 18%) than comparable uncontrolled vehicles. Other
authors have contributed a greater fuel economy penalty to emission
controls.

Since vehicles are not generally driven by the consumer in the
steady-state cruise mode’ and an individual driver strongly influences
the rate of accelerations and decelerations, the fuel.economy obtained
by different drivers over the same route under identical traffic con-'
ditions will vary significantly.

Significant differences have been reported for fuel economy of
vehicles for a trip started from a "cold-start condition" as compared
to the fuel economy for the same trip and vehicle when it is started
from a "hot-start condition." Data, which will be discussed in more
detail in Section 5.6, have indicated that short trips in the range of
3 to 5 mi initiated from a cold-start condition can result in fuel
economy penalties of as much as 20% to 35% when compared to fuel econ-
omy of a fully warmed-up vehicle. In addition, variations in ambient
conditions affect vehicle fuel economy.

The preceding discussion has been designed to provide an overview
rather than a dissertation on large numbers of important factors that


69

Ir
20 Production Cars 1967-1973 ’

zB 6-

E

3

7

F 5

3

P

o

> s

& 4

Qo

°

c

Ee

2

w 3f-

°

n

w

9

x

Oo oe

O- Stratified Charge Car (Proco)
—0.
te o 2
i | | | | J
0 20 40 60 80 100 120

TEST AMBIENT TEMPERATURE (°F)

FIGURE 4.7 Effect of Ambient Temperature on NO Emissions During
the CVS-CH Test *

REF, 33


21

of a large city it has more stops per mile than the UDDS urban cycle
that is based on the L.A.-4 road route.

The proposed EPA highway cycle is designed to incorporate driving
conditions on various classes of highways, including freeways with a
55 mph speed limit, and hence its average speed of 48.8 mph falls
between the average speeds of the SAE suburban and the SAE 55 mph
interstate cycles. As in the urban cycle, the EPA highway cycle
includes considerably more time in acceleration and deceleration modes
than either the SAE suburban or interstate cycles. This may be
principally due to two factors: (a) EPA data indicate the drivers do
not tend to drive at a constant speed but tend to drive at an uneven
speed even when they are in an approximate cruise mode; and (b) the
SAE driving cycles were developed for road and/or track procedures where
cycles based on combination of constant accelerations, decelerations and
cruise modes can be most accurately reproduced from test to test.
Presently, there is some controversy as to the relative differences in
fuel economy of a given vehicle when it is driven at a constant speed as
compared to a varying speed centered about the same constant level.

Based on a study of actual vehicle driving patterns in Phoenix and
central Arizona, it has been suggested that typical driving patterns may
be correlated in terms of the number of stops per mile and average trip

speed. 19

This correlation is shown in Figure 3.5 and the proposed fuel
economy cycles are plotted in Figure 3.5 for the sake of comparison.
Inspection of these data indicates that all of the proposed fuel
economy driving cycles are in agreement with the proposed correlation.
Based on these relatively limited data, one should not conclude that the
proposed correlation represents all driving patterns. However, any
proposed driving cycle that was in significant disagreement with the

correlation should be carefully scrutinized,

3.5 Summary
The UDDS, which is presently employed as the official emission


87

The mandatory correlation test programs should be designed to
determine systematic errors in exhaust emission measurements from cell
to cell and between various laboratories. Once systematic measurement
errors are isolated at a given facility, they can be corrected or the
measurements can be adjusted to take them into account.

It has been shown that one of the important factors contributing
to emission-test variability is variation in ambient conditions.
Unfortunately, the effect of ambient-condition variations during the
CVS-CH test on the exhaust emissions can vary from vehicle to vehicle
and, hence, correction factors designed to correct measured exhaust
emissions for ambient variations should only be employed when it is
impractical to control ambient test conditions. Therefore, it is
concluded that .the CVS-CH test procedure should be modified to require
close control of both ambient temperature and humidity during the
course of the test. Presently, no controls are placed on humidity,
and ambient temperature is allowed to vary between 68 °F and 86 °F
during CVS-CH tests. Good control of ambient temperature and humidity
will require the installation of air conditioning systems at most
laboratories. Unfortunately, barometic pressure cannot be conveniently
controlled during the course of CVS-CH tests. Since barometric pressure
has been shown to significantly affect exhaust emissions and both
systematic and random variations of barometric .pressure occur between
test laboratories, it is concluded that a program designed to determine
exhaust-emission correction factors for variations in barometric
pressure should be developed and incorporated in the CVS-CH test
procedure as soon as possible. More stringent control of the
temperature range allowed for vehicle soak areas prior to testing would
require significant capital expenditures for air conditioning equipment.
It is recommended that a program be carried out to determine the cost

effectiveness of placing more stringent controls on vehicle soak
temperatures.


elements in any standardized fuel economy test method and procedure,
the currently proposed test methods and procedures and the statistical

variability of fuel economy measurements are discussed.

1.2 CONCLUS TONS

A. Evaporative hydrocarbon emissions, based on tests employing
the SHED test procedure, from vehicles equipped with present technology-
control systems have been shown to be higher than 1975-76 Federal
hydrocarbon-exhaust standards when both are compared on a grams-per-
mile basis. Evaporative-emission tests, based on the method presently
specified in the 1975 FTP on similar vehicles, have indicated that
evaporative-hydrocarbon emissions are considerably lower than the
1975-76 exhaust standards. These conflicting results indicate that an
accurate test method and procedure for measuring evaporative-HC emis-
sions must be developed and implemented.

B. The driving cycle associated with the CVS-CH test presents an
average urban trip "as well as it needs to" for the purposes of deter-
mining light-duty motor vehicle-exhaust emissions.

C. Significant consequences should not be attached to a single
CVS-CH exhaust-emission test.

D. Significant systematic errors in mean emission values of a given
test vehicle have been reported between various emission-testing
laboratories. Routine mandatory exhaust-emission-correlation-test
programs between laboratories could significantly reduce these
systematic errors.

E. Variations in barometric pressure and fluctuations in test-cell
temperature and humidity, within the ranges specified in the CVS-CH
test method, have been shown to significantly affect measured exhaust
emissions. Hence, the establishment of close tolerances on the
ambient test-cell temperature and humidity for the CVS-CH test method

and the development of correction factors relating barometric pressure


70

over the methods that are presently employed to determine the deterio-
ration factors which are subsequently used in certification. It has
been suggested that statistical variability associated with exhaust-
emission tests may cause errors in the determination of deterioration
factors when only a limited number of durability-data cars are tested

for a particular engine-system combination,°697

In addition, concern
has been raised over the ratio method that is presently employed to ob-
tain the deterioration factors for durability-data vehicles.» Both of
these points are discussed below.

Monte Carlo Simulation techniques have been used?! to generate
statistically possible emission test measurements at 5,000 mile, incre-
ments in order to estimate the effect of test-error variability on cal-
culated deterioration factors. In this simulation, fleets of 10, 30
and 50 durability-data vehicles with various mean emission values,
specified deterioration factors and test-to-test variability were hy-
pothesized, Test-point measurements for each vehicle in the fleet were
computed using the test variability for 5,000 through 50,000 miles of
simulated durability mileage accumulation, Subsequently, a least-
square regression line was fitted through each set of simulated data
and a DF was calculated for each vehicle.

Typical results based on the Monte Carlo Simulation computations
for a fleet of 10 identical vehicles indicating the possible variability
in the DF as a function of exhaust-emission, test-to-test variability
are listed in Table 4,154.27 Inspection of these results indicates
that the mean value of DF for the 10-vehicle fleet is in reasonable
agreement with the true value of DF as a function of both the exhaust
emissions at 4,000 miles and the test-to-test coefficient of variation.
However, the coefficient of variation of the DF's computed for each 10-
vehicle fleet are generally approximately equal to the corresponding
test-to-test coefficient of variation.

Another Monte Carlo Simulation which included deterioration-
factor variability as well as car-to-car and test-to-test variability
has been reported by Reference 58. The necessary input in this simu-
lation included a 50,000 mile emission point, an absolute deterioration
factor, and absolute values of the test-to-test, car-to-car and


76

rather than chemical processes. In general, fuel hydrocarbon can be
emitted as a result of the evaporation process from both the fuel tank
and the carburetion system. A motor vehicle experiences evaporative
hydrocarbon emission as a result of its normal operating procedure.
For example, at the end of every vehicle trip, evaporation may occur
from the carburetor bowl due to heat being transferred from the engine
block. The evaporated vapor may then escape through any available
opening in the carburetor system. This type of hydrocarbon evaporation
is known as "hot soak losses." Other evaporative losses have been
termed "diurnal," "running," and "refueling" losses. The diurnal loss
is the result of the daily temperature rise and the corresponding
evaporation of hydrocarbon fuel from the fuel tank. Running losses
are similar to both the diurnal and hot-soak losses except that the
necessary temperature increase and heat transfer are provided by the
engine when it is operating. Refueling losses occur whenever fuel
vapors are emitted during fueling operations.

A test method has been developed to measure diurnal, running and
hot-soak evaporative emissions. Prior to initiating the test, the
vehicle is soaked for at least 12 hours to insure that the engine has
completely cooled down. Cool fuel is placed in the tank and the di-
urnal losses are collected by heating the fuel from 60°F to 84°F in
one hour, The vehicle is subsequently run on the CVS-CH cycle and
the engine is shut down. The running and hot-soak emissions are col-
lected during the test cycle and the one-hour period following engine
shutdown. The HC emissions collected during this test can be subse-
quently utilized to estimate the grams of HC evaporated per day from
the fuel tank (diurnal losses) and the grams of HC evaporated from the
system during an average urban trip and the one-hour period subsequent
to engine shutdown (running plus hot-soak losses). The present federal
standard for evarporative emissions is 2.0 g/test.

In order to compare the magnitude of exhaust and evaporative HC

emissions, it is necessary to develop a formula that can be utilized


4.14
4.15

4, 15a

4.16

4.17

5.1

5.2

5.3

5.4

Typical Pollutant Concentrations in Exhaust Emissions
Sample Bags at Various Emission Levels....csccccccccsccscccccceese

Measurement of the Concentration of Pollutants in an
Unknown Sample at Many Laboratories... ...eseee

National Bureau of Standards Calibration Gas Standards......sesoees

Effect of Ambient Temperature on Exhaust Emissions of
Various Vehicles on the CVS-CH Test.....ccececcccscrercccccccccsees

Monte Carlo Simulation of Possible Variability in DF as
a Function of Test-to-Test Variability... ..cccccsccccccccccvccccecs

Summary of Evaporative HC Emission Test Results for
1971-1974 Certification Test Results....ccccoccccccvcsccccccccccces

Summary of Evaporative HC Emission Test Results Obtained
During Surveillance Tests....ccccccccsccccccccccccccccvcccrcccccess
Summary of Round Robin Fuel Economy Test Program......ceccscccccees

Summary of CVS-H Fuel Economy within, between and over
Various Laboratories... ceccccccccscccccccnccrcccescccccenscccssscees

Fuel Economy Measurements as Measured on Both Road Track
Tests and Dynamometer TestS....ccccccsscccccccccccvccscecsecees

Comparison of Fuel Economies for Highway Cycles’ Measured
on a Track and on a Dynamometer..

vii

58

59

61

65

71

79

80

115

116

120

122


104

gains, whereas, an increase in engine displacement tends to result in
fuel economy losses and acceleration gains. An increase in engine dis-
placement does not necessarily result in fuel economy losses since an
increase in displacement could be accompanied by a reduction of the
axle ratio. A reduction of the axle ratio would result in lower engine
speed at the same vehicle speed which could tend to increase the fuel
economy of a given vehicle. In general, a numerically lower axle ratio
will allow for a better fuel economy because the engine will turn
slower for a given vehicle speed at the same power and will have less
internal friction.

The axle is only one of the driveline characteristics that can
affect fuel economy. Another source of fuel economy loss is within
the automatic transmission with its associated torque converter slip-
page. A change from a high-slip loose to a low-slip, tight-torque
converter can increase fuel economy, The basic fuel economy differ-
ence between a manual and automatic transmission should also be con-
sidered, In general, a manual-transmission-equipped vehicle will
obtain better fuel economy than the equivalent automatic-transmission-
equipped vehicle. However, depending on the test cycle, the vehicle
speed, and the rear-axle ratio, it is possible for an automatic-
transmission-equipped vehicle to obtain better fuel economy than a
manual-transmission vehicle.

The state of a vehicle's maintenance can also affect its fuel
economy. Proper tire inflation and wheel alignment can reduce rolling
resistance and improve fuel economy. In addition, the state of a
vehicle's tune and other calibration factors can significantly affect
fuel economy.

The addition of convenience accessories such as air conditioning,
power steering, power brakes, heater and defroster blowers, power win-
dows, power seat adjusters, lighting systems, etc. can also signifi-
cantly lower a given vehicle's fuel economy. For example, the esti-

mated penalty in fuel economy over an unequipped car for air


74

Emission Standard

E(x) = mx + b (least mean square
line through experimental data)

£160,000) _ | 46,000m

DF = F400) = 1+ FT

MASS OF POLLUTANT (g/mile)

IT

a
x
(value of emissions of 4,000-mile emissions data car)

| A es OS
0 5 10 15 20 25 30 35 40 45 50

MILEAGE (1,000 miles)

FIGURE 4,8 Alternate Methods for Evaluating the Deterioration of
Emission Control Systems


100

45

40

f X 103 (Ib)

35

30

25

20

ROLLING RESISTANCE COEFFICIENT

Bias-Belted

15)-

Radial

10 a7 L ! ! | |
) 20 40 60 80 100 120

SPEED (mph)

FIGURE 5.5 Tire Rolling Resistance as a Function of Speed

REF, 48


85

A final decision concerning this issue cannot be reached until the
additional data requested by EPA 4 have been collected and analyzed
from both a technical feasibility and cost-benefits point of view.

4.9 Summary

The CVS-CH exhaust-emission test procedure plays an important role
in the federal certification process for 1975 and subsequent model. year
LDOMV, and, hence, it is important to develop an understanding of the
statistical variability of exhaust-emission tests that can be expected
for vehicles designed to meet these standards. Due to both random and
systematic errors, measurements of exhaust emission from a given LDMV
have poor repeatability. Various factors including vehicle variability,
emission collection and measurement variability and environmental test
variables contribute to the. poor test reproducibility. In addition to
these variations associated with a given vehicle, variations in
emissions from a group of similar production vehicles are also
encountered.

The results of programs designed to isolate important, sources of
variability in CVS-CH exhaust-emission tests, other than vehicle
variability, have indicated that local ambient test conditions, driver
skill, dynamometer design; ro4l spacing and calibration method, and
systematic errors associated with CVS sampling.and gas analysis
techniques all have an effect on laboratory-to-laboratory exhaust-
emission variability. It has been shown that. variations in: barometric
pressure, humidity and test-cell temperature can have a significant
effect on HC, CO and NO, Oy. corrected) exhaust emissions. It has also
been shown that vehicle soak temperature, within the allowed range of
60 °F to 86 oF, can influence HC and CO exhaust emissions.

Tests on 1975 type vehicles equipped with oxidation catalysts have
shown that the cold transient phase of the CVS-CH test is a major


53

An analysis of work done (measured at drive shaft) by each vehicle
during testing suggests that it may explain the effect of roll spacing
changes on emissions. The total work (measured by drive shaft torque)
during the CVS-H test using the 10 in, roll spacing versus the 17 in.
roll spacing on all inertia-weight vehicles was higher py an average
of 1.3%. The largest increase in emissions with the roll.spacing change
(17% in. to 20 in.) was on the medium inertia weight where HC, CO and
No, increased 3.3%, 4.5% and 2.8%, respectively, and where total work
increased 2.4%. On the small inertia-weight vehicle, however, changing
the roll spacing from 17% in. to 20 in. caused CO emissions to decrease
3.2%. From these results, it can be concluded that all engine calibra-
tions do not react the same to increased dynamometer loading.

During the Ford correlation program, the combined CVS sampling
and gas analytical systems were evaluated by means of a very precisely
regulated vehicle gas simulator once each day of vehicle testing. The
data from these studies showed that although measurement variability
for any one facility may be within acceptable limits, systematic dif-
ferences in these systems may exist between facilities‘of magnitudes
ranging from 2.2% to 8.0%.

General Motors Corporation’? reported the results of 18 CVS-CH
tests, carried out in an environmental chamber, designed to evaluate
the sensitivity of exhaust emissions to barometric pressure and
humidity variations. The test vehicle was equipped with a 350 CID
engine, EGR, and early fuel evaporation manifold, integrated fuel con-
trol with altitude compensation and dual-mode’ emission-control system.
All tests were carried out with the same driver and three levels of
ambient pressure ranging from 26 in. Hg to 30 in.:Hg-.and thrée values
of humidity ranging from 30 to 100 gr/lb dry air were studied. The
results of this study based on a linear regression analysis are listed
in Table .4.10. Inspection of these results indicates that a one-
inch increase of barometric pressure resulted in reduced HC and CO
emissions of 10% and 30%, respectively, and an increase of No, and


49

Driver
[Ambient Conditions

Dynamometer

RELATIVE CONTRIBUTION
Vehicle
CVS Test

_] Operator
0 Computer

5
8
2
3
€
[]

FIGURE 4,3 Sources of Variability and Probable Relative Contribution
for Mass Emissions Errors on the CVS-CH Test at 1975-76 California
Levels

] Calibration Gas

REF, 23


Distribution of Trips 1
ssp 7
2e
aa st
ct
BS E
o5 5 ab
Be
5S z
< Ls
zé = TP
OR a
he . . 2H
oor Distribution of VMT
c
2 '
2
a
- L pe or oe 1 n )
7 10 20 30 40 50 60 70 «80
TRIP LENGTH (mile)
1 | = i t — + i J
10 20 30 40 50 60 70 80
TRIP LENGTH (mile)
FIGURE 3.1 Distribution of LDMV Trips and Vehicle Miles Travelled

I


40

A vehicle equipped with an oxidizing catalyst has been tested
several times over the CVS-CH cycle in various cells at Chrysler
Corporation and three times in one test cell at EPA in Ann Arbor, The
results of these data are summarized in Table 4.7.78 Inspection of
these data indicates that the mean values obtained at the two labora-
tories vary by approximately 25% for HC and CO, are equal for No, and
within 3% for co,.

Honda2> has reported the results of CVS-CH tests on 38 production
vehicles equipped with 1.5 liter CVCC stratified-charge engines. The
mean values and standard deviation as percent of mean for HC, CO and
No, were reported to be 0.23 + 21.8%, 2.24 + 8.9% and 1.15 + 10.4% g/mi,
respectively.

General Motors Corporation has developed REPCA I, a vehicle with
emissions near the 1974 standards ,that is designed to minimize vehicle
variability during CVS-H tests. This vehicle has been subsequently
utilized in hot tests to obtain information concerning cell-to-cell
variability at one laboratory and for round-robin testing between
laboratories. Emission data obtained from CVS-H tests on REPCA I in
five test cells at General Mctors during May 19749 indicate that the
standard deviation of cell-to-cell variation of emissions measured on
CVS-H tests on this specially designed stable-emission vehicle is of
the order of 4.5% for HC and NO, 8% for CO and 1.8% for co,.

The Motor Vehicle Manufacturers Association (MVMA) conducted a
lab-to-lab cross-correlation program using CVS-H tests on REPCA I
during 1974.23 These tests were carried out at General Motors, EPA in
Ann Arbor, Chrysler, American Motors, Ford and International Harvester
during March and April 1974. Most of these CVS-H test results for HC,
CO and NO,» except for one laboratory, fell within plus or minus two
Standard deviations of the mean values. Standard deviations as percent
of the mean for these pollutants were approximately 4.5%, 8.0% and
1.8%, respectively, The co, test results indicated that a number of


44

the estimated 1975 test variability is considered to be a conservative
measure of the test variability which will be encountered during the
1975 Certification Program.

This analysis estimates the test-to-test variability of a 1975-

type emission-reduction system based on the back-to-back test data,
The before and after-maintenance data were treated as two separate
populations in order to prevent emission-level differences due to
maintenance from affecting standard deviation calculations. By pooling
the standard deviations for mileages, vehicles and families, this
analysis separates test-to-test variability from the influences due to
mileage, vehicle, family and maintenance. The results of the Riverside
test program by engine family are summarized in Table 4.8.78

The MVMA carried out a 1973 Certification Program as part of the
MVMA Correlation Cross Check Program. This program compared emission
results of respective member-company tests to emission results obtained
at EPA laboratories. Data were collected from over 300 vehicles from
four member companies which indicated that the standard deviation of
CVS-C tests as percent of mean emission values were approximately 17%,
23% and 14% for HC, CO and NO.» respectively. Since these variabilities
were in the same range as the Riverside fleet-data variabilities pre-
sented in Table 4.8, MVMA concluded that statistical variability of the
CVS-CH test for vehicles designed to meet the 1975 standards would. be
approximately equal to that experienced on the CVS-C test during the
course of the 1973 certification testing.

Data provided by one manufacturer”? summarizing the results of
recent CVS-C quality audit tests of 1974 California production vehicles
as a function of engine family are summarized in Table 4.9. Inspection
of these results indicates that the variability expressed as the stand-
ard deviation as a percent of the mean for these production vehicles is
in the range of 15% to 30%, 20% to 40% and 15% to 25% for HC, CO and
NO,» respectively.


73

penalize durability vehicles with relatively low 4,000 mile extrapolated
emissions.>”

As described previously, a deterioration factor (DF) for each
pollutant is determined by fitting a least squares best fit straight

line to all durability emission data and defining DF in terms of

exhaust emissions of pollutant i

QF), = at 50,000 miles ql)
exhaust emissions of pollutant i
at 4,000 miles

where the exhaust emissions at both 4,000 miles and 50,000 miles are

obtained from the least squares fit line. To facilitate discussion
and introduce appropriate nomenclature, a least-squares line repre-
senting a "typical" deterioration-factor test result is shown in
Figure 4.8. The least-squares line obtained from the data is '‘repre-
sented by E(x) =m x + by where E(x). is the emissions at x miles and
m and b are the least mean square values of the slope and intercept,
respectively. The equation for the least squares line can be ‘readily
rewritten in terms of the slope m and the interpolated value of the
emissions at 4,000 miles (I).

E(x) =m (x-4,000) + I (2)
The deterioration factor as computed by EPA for the data in Figure 4.8
would be given by

DF = E(50,000) _
E(4,000) = m(50,000 4,000) +1 (3)
or simplifying
DF = 1 + 46,000 m (4)
I

Inspection of Equation (4) indicates that the DF, as computed by EPA,
is dependent on both the slope of the deterioration line and the extrap-
olated value of the line at 4,000 miles.

The vehicle under consideration is checked for certification by
testing a corresponding emission-data car at.4,000 miles and multi-
plying the numerical value (X) of each pollutant measured during this
test by the DF.


135

carrying out exhaust emission measurements on the CVS-CH test
could significantly reduce these errors, These correlation
programs should include CVS-CH tests of relatively stable vehi-
cles and tests of the CVS sampling and gas analysis systems
using either exhaust-gas generators or premixed-gas cylinders
as the gas source, Once systematic measurement errors are iso-
lated at a given facility, they can be corrected or the mea-
surements can be adjusted to take them into account.
Fluctuations in test-cell temperature and humidity, within the
ranges specified in the CVS-CH test method, and variations in
barometric pressure have been shown to significantly affect
measured exhaust emissions. Presently. no controls are placed
on humidity and ambient temperature -is allowed to vary between
68°F and 86°F during CVS-CH tests. Modification of the
CVS-CH-test procedure incorporating close control of both ambi-
ent temperature and humidity would decrease the statistical
variation in exhaust-emission measurements, Unfortunately,
barometric pressure cannot be conveniently controlled during
the course of CVS-CH tests. Since both systematic and random
variations of barometric pressure occur between test labora-
tories, appropriate correction factors relating variations. in
barometric pressure to.exhaust emissions should be applied to
CVS-CH tests.

Ambient temperature variations, commonly encountered in large
sections of the nation during winter (e.g., 0° F-32°F), can
significantly increase exhaust emissions of HC and CO, for
both pre-1975 production vehicles and 1975 prototype models
equipped with oxidation catalysts, above the emissions mea-
sured during the course of the CVS-CH test. As an example of
this effect, the HC and CO emissions from four prototype
catalyst-equipped vehicles were shown to increase by. 160% and
and 409%, respectively, when the vehicles were tested at 20°F


FUEL ECONOMY, CVS-CH TEST: (mpg)

24

20

16

12

128

Stratified Charge (Proco’
e--
-— -—

Om
_a- oo”

Pe

——-O — ~~~

- 20 Production Cars 1969-1971
— a
—o
4 Prototype Advanced Emission Cars-(all catalyst)
| it i BI 1 J
20 “40 60 80 100 120

TEST AMBIENT-TEMPERATURE (°F)

FIGURE 5.10 Effect of Ambient Temperature on Fuel: Economy for Various
Types of .Vehicles on the CVS-CH Test Cycle

REF, 33


2.2 Scope

The reliability and reproducibility of any experimental measurement
is defined by the test methods and procedures utilized to obtain the
measurement, This fact is particularly applicable to the measurement
of emissions and fuel ecnomy, since the tests in a test cell or ona
test track attempt to measure quantities that only really exist as
the composite averages taken over a large group of similar vehicles
being driven by all drivers on all streets and roads. An ideal set of
test methods and procedures would duplicate these real-life conditions
and determine the average emissions and fuel economy for a group of
vehicles. This ideal is impossible to attain in a test cell or test
track and, hence, it is necessary to carefully define tests which
provide reasonable approximations to the real-life values. A logical
examination should show that the tests yield results whose reliability,
reproducibility and cost are commensurate with the primary goals of
controlling air pollution and evaluating the relative fuel economics
of various vehicles. This logical examination must include an evalua-
tion of how closely the tests duplicate real-life conditions, the
reproducibility of the results and whether viable alternatives give
significantly better results.

In order to address these questions, this consultant report is organized
into four main sections dealing with: Vehicle Use Patterns and Driving
Cycles; Emission Test Methods and Procedures; Fuel Economy Test
Methods and Procedures; and, Evaluation of the Data. Vehicle use
patterns and driving cycles are discussed first since it has been
established that both emissions and fuel economy are dependent upon
the driving cycle.

The CVS-CH exhaust-emission test procedure plays an important
role in the certification process for LDMV and, hence, the statisti-
cal variability of the exhaust-emission test for 1975 and subsequent
model-year vehicles is considered in Section4.0. The relative


130

The critical elemetits in any standardized fuel economy test method
and procedure include: a-representative standard driving cycle or
cycles; a method to determine the mass or volume of fuel consumed and
the distance traveled during ‘the test; and a procedure for simulating
vehicular loads encountered during the course of the driving cycle.

Since: the driving cycle associated with the CVS-CH test: method
meets the criteria for an appropriate urban fuel economy driving cycle
and a significant data base of urban fuel economies has been collected
with this cycle, it is concluded that’ the CVS-CH driving cycle .can be
used as the standard urban fuel. economy driving cycle. In addition, it
is ‘suggested that.either the EPA’ highway cycle or a combination of the
SAE suburban and interstate cycles can be employed as the standard:
highway: fuel economy, cyclé.

Two methods have been utilized to measure fuel consumption, The
first method is based on the direct measurement of mass or volume of
fuel consumed ‘during the course of the test, The second method, .the
Carbon Mass Balance Method, is based on the collection.and measurement
of carbon containing compounds in. the ‘vehicle's ,exhaust.. .Since the
mass of carbon per gallon of fuel is known, the mass of carbon in the
exhaust can be readily employed to compute the mass or volume of. fuel
consumed during the-test. ‘When applying either method, the distance
traveled during the test: is measured by.alternate satisfactory tech-
niques and fuel economy is readily computed. Both of these test meth-
ods -for fuel consumption measurements have advantages and disadvantages
and are subject to significant errors if careful experimental tech-
niques and procedures are not followed. However, under-.conditions
where both techniques can be simultaneously employed, either method
can be used to obtain.accurate measurements of fuel consumption. .

Two procedures ‘have -been proposed . for simulating vehicular loads
encountered during the course of the driving cycle. One method is
based on driving the vehicle over a suitable road or test.track, and


Calibration Gas

Analyzer

Sampling

Computer Processing
and Interface

48

Uncertainty of
Concentration
Measurement

Driver

Dynamometer

Ambient Temperature

Atmospheric Pressure

Absolute Humidity

Votume per Pump Revolution

Revolutions of Pump

Exhaust Gas Temperature

‘Vacuum Pressure

ui,

Overall Uncertainty
of Concentration
Values

Uncertainty of
Concentration
Values in
Sample Bags

‘Uncertainty of
Diluted Exhaust

FIGURE 4,2 Factors Affecting Uncertainty in Exhaust Emission Mass

Measurements

REF, 23, 27


CONTENTS

1.0 Summary and Conclusions........sssscccccccceccecsccscccees

2.0

3.0

4.0

1.1

1.2

CONCLUSLONS. .. cee eeccccccccneccccccccccccscreesereees

Introduction... ...ccccececsccccccccccccsccccceccecceseseees

2.1

2.2

Purpose and Panel Organization... .cccsssscessccoveees

SCOPE. cresvecvcvcccccsnccesccerccsessssscessssssseees

Vehicle Use Patterns and Driving Cycles....ecesseccsescees

3.1
3.2
3.3
3.4

3.5

Introduction. .eccecccsecccccccsccccscccssccsceccenees
Vehicle Use Patterns..ecssccseseccccccscscecccccseres
Development of Driving Cycles for Emissions..........
Development of Driving Cycles for Fuel Economy.......

SUMMALY..ceccccr ees crccccsscsesscensseccsscsevesesees

Emission Test Methods and Procedures....sssecssoeseccecece

4.1
4.2

4.3

4.4

4.5
4.6
4.7

4.8

4.9

IMtroduction...scsscsccecrcccccccerccccsceeececscsece
Certification Procedure......ssessecccccsscccccenoves

Statistical Variability of Exhaust-Emission
Measurements ..ssescsseccsccvcccccrvccccvsccccscscsces

Factors Affecting Statistical Variability of Exhaust
Emission Measurements in CVS-CH TestsS.....ssessesseee

Effect of Ambient Temperature on Exhaust Emissions...
Durability Test Methods and Procedures.........+.+.+6
Evaporative HC EmissionS.....csccccsccccccccscscevees

Consideration of Non-Reactive HC Exhaust Emission
Standards. ...scscccecccscscccccecscvcsscveccccecccsee

iv

12
13
21
24
24

25

31

47
62
66
75

82

85


65

TABLE 4.15

Effect of Ambient Temperature on Exhaust Emissions of
Various Vehicles on the CVS-CH Test

Test Temperature, °F .,, | Tests with and without
, 4 Air Cond:, 110° F 2/
20 so! 75 110 With [Without
Production vehicles?!
Hydrocarbon....sseeeseee 7.44 5.63 4.66 4.67 4.56 3.98
Carbon monoxide.........| 81.6 65.4 53.8 63.5 72.3 57.8
Nitrogen oxides......... 6.40 5.25 5.06 4.13 5.94 4.44
Aldehydes....sssseeeeees 23 20 +18 17 ll | 14
Hydrocarbon”!
Total.....cececeeeeeee 8.51 5.90 5.01 4.95 4.28 3.61
Non-methane .........- 7.76 5.44 4.71 4.67 3.98 3.35
Reactive....... oe 6.55 4.70 4.01 4.33 3.33 2.80
Fuel economy, mpg.. 10.8 10.9 11.4 11.5 10.34 11.58
Catalyst equippe 3/
Hydrocarbon, 1.31 81 49 50 54 50
Carbon monox: 28.0 15.8 5.5 6.1 11.9 6.1
Nitrogen oxides......... 3.14 3.05 2.33 2,35 2.66 2.35
Aldehydes..........eee0 -035 -035 .040 2021 .010 -020
Hydrocarbon!
Total.....sseeeee 1.31 81 49 50 | 652 49
Non-methane.... 1.03 -66 |. .40 +38 |. .40 38
Reactive....... +90 57 +35 34 235 233
Fuel economy, mpg.. 9.6 10.3 10.8 11.4 10.2 11.4
Stratified charge, proco®!
Hydrocarbon. eeecveee 255 28 20 14 - -
Carbon monoxide...... 1.8 6 7 4 - -
Nitrogen oxides. 1.37 1.25 1.05 1.07 a ~
Aldehydes............00- 204 03 01 01 - -
Hydrocarbon
Total...ccccceceseeece 255 28 20 14 - -
Non-methane. 46 +22 15 ell - -
Reactive......... -40 20 13 +10 - -
Fuel economy, mpg . 19.3 20.4 21.2 20.5 - -
Diesel equipped”
Hydrocarbon ....... 60 30 49 .40 - -
Carbon monoxide... 1.9 1.4 1.4 1.2 - -
Nitrogen oxides.... . 2.06 1.99 1.78 1.88 - -
Aldehydes........eeeeees 05 04 05 05 - -
Fuel economy, mpg.......| 17.1 18.6 19.7 20.1 - -
1/ Five 1973 vehicles not tested at 50° F.
2/ Thirteen production cars.
3/ Twenty cars--duplicate tests.
4/ Six cars,
5/ Four cars--duplicate tests.
6/ Single car--duplicate tests. REF. 33


TABLE 3.3

Comparison of Currert and Ptopospd Fuel Economy Driving Cycles

EPA DRIVING CYCLES SAE DRIVING CYCLES
Ccys-C CVS-CH HIGHWAY URBAN SUBURBAN INTERSTATE INTERSTATE
START comp COLD HOT HOT HOT (55 mph) (70 mph)
(1972-FTP) (1975-FTP) HOT HOT
TEST CHASSIS CHASSIS CHASSIS TRACK TRACK TRACK TRACK
LOCATION ROLLS ROLLS. ROLLS
Length
(miles) 7.45 11.04 10.25 2.0 5.2 4.7 4,7
Driving
Time
(min) 22.87 31.3 12.7 7.7 7.6 5.1 4.0
Avg. Speed
(MPH) 19.5 21.18 48.8 15.5 41.1 55.3 70.5
Max. Speed
(MPH) 56.5 56.5 59.9 30 60 60 75
Max. Accel.
(res?) 4.84 4.84 4.69 7.0 7.0 1.0 1.0
Time Cruise
% 7.9 77 16.5 58.3 75.2 61.8 51.5
Time Accel,
% 39.6 39.3 44.4 11.3 11.3 19.2 24.3
Time Decel.
% 34.6 34.9 38.7 17.4 10.5 19.1 24.2
Time Idle
tb 17.8 18.1 0.4 13.0 3.0 9 i)
No. of stops
per mile 2.3 2.0 0.1 4.0 0.4 0 1)

02

NOTE: Accelerations and decelerations are defined as changes in velocity greater than 0.1 ft/: sec?

REF. 17


63

greater for both vehicles, with and without oxidation catalysts, than
the emissions for the same vehicles when they were soaked in accordance
with the CVS-CH test (e.g., 60°F to 86°F). The Emission Testing Lab-
oratory of Environment Canada studied the effect of ambient temperature
on exhaust emissions.>* The test procedure used during the course of
the tests was very similar to the CVS-C test procedure, and tests were
conducted on five 1972 and 1973 vehicles. Each vehicle was tested 30
to 40 times under cold conditions and 15 to 20 times under baseline
conditions (e.g., 60°F-86°F).

Linear correlations of present emission changes as referenced to
emissions measured at 60°F were found to correlate the data better
than parabolic fits. The average of the emissions from the five
vehicles tested for HC and CO are plotted in Figure 4.4 as a function
of percent deviation from the average emissions at 60°F. The average
HC curve yields a 100% increase in HC emissions at 8°F as compared to
the 60°F emissions. The correlation lines for all five vehicles had
different slopes ranging from approximately 0.62 to 1.5 times the
average slope. The CO average curve yields an increase of 100% in CO
emissions at 20°F as compared to the 60°F emissions. The slopes of
the lines for the five cars were all different with slopes ranging
from approximately 0.3 to 1.6 times the average slope. The average
NO, emissions from the five vehicles showed a slight decrease in emis-
sions (less than 3%) at O°F as compared to emissions at 60°F.

The Bartlesville Energy Research Center of the U.S. Department
of Interior has recently completed a series of tests designed to
determine the effect of ambient temperature on exhaust emissions and
fuel economy for twenty production cars from 1967-1973, four prototype
1975 emission cars with oxidation catalysts, one vehicle equipped with
a diesel engine and one vehicle equipped with a PROCO-type stratified-
charge engine. >?

The experiments were carried out using the CVS-CH test procedure
and the results are summarized in Table 4.15. The effect of ambient


139

is in the range of 2% to 8%. The limited data obtained for
reproducibility studies on the EPA highway cycle have indi-
cated a similar variability. However, due to the potential
significance that may be attached to reported fuel economies
of individual vehicles, reported fuel economies should be

based on the results of several tests.


56

TABLE 4,11

Average Emissions for Six 1973 Vehicles as a Function of Cold Soak Temperature

Soak Temperature HC co NOx
(°F) (g/mt)  (g/mi) — (g/mi)
60 2.16 26.23 2.80
73 2.12 25.40 2.78
86 1.84 21.20 2.78

REF. 30


13

periods with 0-39 second durations. This schedule covers 7.45 miles in
1372 seconds for an average speed of 19.5 miles per hour (mph). The
speed versus time trace for the UDDS is listed in Reference 7 and the
UDDS is graphically represented in Figure 3.2.

More recent studies of urban driving patterns in various metro-
politan areas have been carried out to determine if the UDDS is an
adequate representation of urban driving. The CAPE-10 project (see
References 8 to 11) was designed to determine the average driving cycles
in the following 5 major metropolitan areas: Los Angeles, Houston,
Cincinnati, Chicago and New York City. The average speed, percent of
time in each mode and percent occurrence in each mode as obtained by
the CAPE-10 project are presented in Table 3.2. The UDDS and the
original L.A.-4 cycle data are also presented in Table 3.2 for the sake
of comparison.

Comparison of the CAPE-10 L.A.-4 data designed to represent Los
Angeles morning rush-hour traffic (line 8 in Table 3.2) with the
original L.A.-4 data (line LI in Table 3.2) indicates excellent agree-
ment between the two studies. Based on this observation and the good
correlation between the UDDS and the original L.A.-4 cycle, it can be
concluded that the UDDS is a good representation of morning rush-hour
driving patterns for central Los Angeles. Inspection of Table 3.2 also
indicates that the UDDS has a lower average speed and more percentage
of time in the idle mode than the CAPE-10 five-city composite cycle, It
has been reported}? that there are not significant differences in ex-
haust emissions of vehicles tested on the five-city composite cycle when
compared to the UDDS.

3.4 Development of Driving Cycles for Fuel Economy

Historically, individual automobile manufacturers and other.
interested parties have developed fuel economy driving cycles to test
the effects of vehicle-design changes, fuels and lubricants and other
factors on automotive fuel economy. In most cases, fuel economy was


P(e
P,(2)%

5
10
15

50
75
100
150

*
P(2,3,1)%

3
P(2,3,4)%

50

75.0

55
79.8

TABLE 4. la

Table of Ratio of True Adjusted Mean Emission to Standard in Percent,

x/A%, as a Function of s/x in Percent and Probability in Percent.
ii

60
84.0

65
87.8

70

91.0

aa

80

96.0

85

97.8

90
99.0

95.0

99.8

97.5
99.9

100
100
100
100
100
100
100
100

100

99.4
98.8
98.2
97.6
96.4
94.1
91.4
88.9

84.2

98.8
97.5
96.3
95.2
92.9
88.8
84.1
79.8
72.5

98.1
96.3
94.5
92.9
89.6
83.9
77.6
72.2

63.4

97.4
95.0
92.7
90.5
86.4
79.2
71.8
65.6
56.0

96.0
92.2

88.8-

85.6
79.8
70.4
61.3
54.3

44.2

95.1
90.6
86.5
82.8
76.3
65.9
56.3
49.1

39.1

94.0
88.6
83.9
79.6
72.2
60.9
51.0
43.8

34,2

92.4
85.9
80.2
75.2
67.0
54.9
44.8
37.8
28.8

91.L
83.6
77.3
71.8
63.0
50.5
40.5
33.8

25.4

23.4

3

30.5

38.5

2.2

47.4

5.0

56.8

10.4

76.2
33.7

85.1

52.5

92.7

73.7

98.0
92.1

for a normal distribution

P,()

t 2
vv tV/2 ay

ty = (Azx)/s,

2
P,(2) 21 ~ [1-P,ayy

(a) for independent
emission types

P(2,3,1) = 1- fi-PayPayPayy?
“Hc 6CcO NO,

(b) if each emission type
has the same values of
s/x and x/A

Li ii
Pa3.p =1- Bea)?

This Pt2,3,1) is given in the
table.

(c) if each_vehicle has the
same s/x and x/A with
ii ii
assumptions (a) and (b)

P@2,3,4) = LP2,3,.n]"

0€


e.

150

Data on HC evaporative emissions as obtained in SHED tests.
Comparison of total HC evaporative emissions as obtained in
SHED tests versus "cannister" tests,

Fuel Economy

a.

b.

Data on any inner-lab and intra-lab reproducibility and/or
correlation testing programs on vehicular fuel economy.

Data on statistical variability of fuel economy from a
single vehicle undergoing many tests and/or from a group of
similar production model vehicles.

Data detailing the effect of ambient conditions (special
consideration to temperature) on fuel economy.

Data on fuel economy versus trip length and any data
relating to the relative fuel economies of a specified trip
when the trip is initiated from a "cold start" versus a
“hot start."

Data on fuel economy penalties associated with vehicle
accessories, transmission type, etc.

General Considerations

a.

b.

Data on road load on vehicles versus vehicle speed.

i. Rolling resistance versus speed
ii. Aerodynamic drag versus speed

Data on relative importance of inertia forces and road
load as a function of vehicle speed and acceleration.


50

Three vehicles in the 3,000 1b, 4,500 1b and 5,500 1b inertia-
weight classes with HC, CO and No. emissions in the range 1.35, 16.5
and 2.4 g/mi, respectively, were employed during the course of the
correlation testing. Most of the emission tests were run on a CVS-H
cycle in order to minimize vehicle-variability effects on the study.
The relative magnitudes of the important sources of variability as
reported by the Ford task force are summarized below.

Driver variability, within the specified federal tolerances, was
found to significantly affect mass emissions, Based on the average
of studies carried out on the three vehicles, it was found that "bad"
drivers increased emissions of HC, CO and No, by 3.2%, 8.0% and 0.4%,
respectively, over results obtained by "good' drivers. The analysis
further indicated that the effect of driver skill on emissions is in-
fluenced by vehicle inertia weight, dynamometer calibration and driver
aid chart speed. As an example, CO increased from 2.5% to 18% on the
3,000-1b and 4,500-1b inertia-weight vehicles, respectively. Results
obtained using the controlled measurements showed the increased roll
spacing from 17% in. to 20 in. significantly changed the effect of
good to bad drivers on HC and CO emissions at 90% confidence. Dyna-
mometer calibration procedure changes from multiple to single inertia
weight also significantly change the effect of good to bad drivers on
HC, CO and NO, emissions at 90% confidence. Furthermore, driver aid
chart speed changes from 4 to 6 in./min changes the effect of good
to bad drivers on HC and CO emissions at 90% confidence. Thus, these
results show that the magnitude of the driver effect on emissions is
large but influenced by the vehicle and the equipment at the facility
where the tests are conducted.

The study also considered the effects of environmental variables
including specific humidity, barometric pressure, vehicle soak-area
temperature, test-cell ambient temperature and ambient bag-air concen-
trations on the variability of exhaust emissions. The effects of


16

determined for a series of steady-state cruise modes at various speeds
and for vehicle operation over a number of driving cycles designed to
simulate consumer driving patterns in the urban, suburban and inter-
state driving modes. Until recently, a standardized fuel economy
driving cycle that might serve as the basis for the accumulation of data
on fuel economy of cars for comparison purposes was not available.

The EPA suggested that the UDDS can be utilized as a standardized
driving cycle to evaluate urban fuel economy. EPA has published fuel

13 ond 1974 model-year!*

economy data for selected 1973 model-year
LDMV based on the UDDS (see Figure 3.2 for a speed versus time trace
of the UDDS). Significant data have been accumulated for urban fuel
economies of LDMV on this cycle.

Since highway travel accounts for approximately 50%, of the total
vehicle miles traveled, the EPA has recently proposed a highway driving
cycle for fuel economy measurements. > This cycle was derived by
instrumenting a car and driving on four classes of roads in the
vicinity of Ann Arbor, Michigan. The velocity time traces obtained as
a result of driving these four types of roads were then combined in
such a way as to approximate the mileage composition as specified for
such roads by the Department of Transportation. For certain belt-driven
dynamometers, the initial acceleration and final deceleration proved to
be too large. Therefore, EPA reduced these accelerations in a revised
driving schedule. 6 The speed versus time trace of the EPA highway
driving cycle is presented in Figure 3.3.

The velocity composition of both the EPA urban driving cycle and
the proposed highway driving cycle are shown in Figure 3.4.27
Inspection of Figure 3.4 indicates that both cycles have velocity
distributions that are approximately bimodal. That is, during the CVS-
CH cycle, most of the cycle distance is traveled at speeds in the
vicinity of either 25 or 55 mph, and in the highway driving cycle, most
of the distance is traveled at speeds in the vicinity of either 47 or
57 mph.


ll.

12,

13.

14,

15.

137

The CVS-CH driving cycle is a sufficiently accurate represen-
tation of urban driving patterns to be used as the urban fuel
economy driving cycle.

A fuel economy driving cycle similar to the EPA highway .cycle
or a combination of the SAE suburban and interstate cycles may
be appropriate’ for measurements of highway driving fuel econo-
mies.

Either the Carbon Mass Balance Method or the direct measure-
ment of the mass or volume of fuel consumed can be employed to
obtain accurate measurements of fuel consumption if careful
experimental techniques and procedures are developed and fol-
lowed. Both of these test methods for fuel-consumption mea-
surements have disadvantages and advantages and are subject to
significant errors if careful experimental techniques and pro-
cedures are not followed.

_ Two procedures have been proposed for simulating vehicular

loads encountered during the course of the driving cycle. One
method is based on-driving the vehicle over a suitable road or
test track, and the second method is based on driving the cycle
on a chassis dynamometer. Both of these procedures have dis-
tinct advantages and disadvantages. :

There is no inherent technical reason for eliminating the use
of chassis dynamometers from fuel economy testing if it can be
shown that they adequately simulate the actual inertial, aero-
dynamic, rolling resistance and accessory loads experienced by
a vehicle as it traverses the driving cycle, Unfortunately,
the results of definitive studies designed to evaluate the
ability of chassis dynamometers to accurately simulate vehicle
loads under a:wide variety of conditions and ‘to evaluate any
errors in fuel economy.measurements associated with specified

errors in dynamometer load simulation have not been reported.


83

Ford“? has recently petitioned EPA to amend the motor-vehicle and
motor-vehicle-engine-exhaust-emission test procedures to permit ex-
clusion of methane in determining compliance with federal motor-
vehicle-emission standards. The petition includes: (1) information
relating to the non-photochemical reactivity of methane; (2) data
relating the quantities of methane contained in the exhaust of LDMV
equipped with various types of control systems, including oxidation
catalysts; and (3) information concerning the availability of instru-
mentation methods for the measurement of both total and non-methane
HC's in automotive exhaust.

Ford's data®> indicate that methane may represent approximately
10% to 40% of the total HC in the exhaust of catalyst-equipped
vehicles. In addition, a good correlation was shown between total HC
measured with the standard FID technique and a modified FID technique
which has been designed to measure both total HC and methane.

Other laboratries have also reported large concentrations of
methane in automotive exhaust from LDMV equipped with oxidizing
catalysts. chrysler?® has reported data which indicate that mass
fractions of unreactive hydrocarbons, including methane and ethane,
are increased as the exhaust passes through an oxidation catalyst.

In addition, data presented in Table 4.1593
methane fraction of total hydrocarbons in automotive exhaust is ap-

indicate that the non-

proximately 94% and 81% for six pre-1974, noncatalyst-equipped

vehicles and six catalyst-equipped vehicles, respectively. Data in

Table 4.15 also indicate that the fraction of reactive hydrocarbons

in the same group of vehicles is approximately 80% and 70% for noncatalyst-
equipped and catalyst-equipped vehicles, respectively. In these data,
nonreactive HC's were assumed to include methane, ethane, propane,
acetylene and benzene. It is important to note that the mass fraction

of aldehydes to total hydrocarbons was not significantly different for
catalyst-equipped and noncatalyst-equipped vehicles.


TABLE 4.4

Summary of Emissions Test Variability for Three Experimental Vehicles
with 1975 Control Systems in a Single Test Cell

Vehicle Serial No. No. of Tests = HE 3 = co 3 = NOx 3

x = x = x =

x x x
1 10 0.27 11.1 3.65 26.3 2.72 8.5
2 11 0.34 11.8 0.82 24.4 1.79 5.6
4 11 0.36 16.7 1.97 40.6 1.42 14.1

1 X — mean emission value on CVS-CH test, g/mi
2 - standard deviation as percent of mean

REF, 24

Le


78

shown in Table 4.16.4?

It was shown that 60% of the tests reported
as less than 0.1 g were actually reported as 0.0 g, and that in
general, most of the tests reported as 0.0 g corresponded to negative
canister-weight changes. Comparison of the evaporative-emissions data
shown in Table 4.16 with the estimated precontrolled evaporative emis-
sions of 37 g/test seems to indicate that present evaporative-control
systems are very effective, and that evaporative emissions have been
essentially completely controlled.

The evaporative HC emissions results obtained in two recent EPA

surveillance programs *?>43

for both precontrolled and controlled
evaporative-emissions systems indicate that this conclusion is not
correct. The surveillance program carried out in 1972 measured
evaporative emissions from both controlled and uncontrolled vehicles

employing the SHED method. “3

The SHED method was employed during these
tests rather than the carbon-canister-trap method since it takes into
account evaporative emissions from the entire fuel system including
gasket and throttel shaft leakages. In addition, vehicles manufac-
tured prior to the implementation of evaporative controls are not
readily amenable to measurement by the carbon-canister method.
Evaporative-emission measurements were made in Los Angeles for 136
vehicles ranging from 1957 to 1971 model year and twenty-two 1971
model-year vehicles were tested in Denver to assess the effect of
high altitude. The results of these tests are summarized in Table 4.17.
The weighted values of these HC emissions in grams per mile as computed
from Equation (7) are also listed in Table 4.17. Results from the
1972 fiscal year surveillance program included evaporative-emission
tests on twenty-two 1972 model-year vehicles in both Los Angeles and
Denver. These results were also based on the SHED method and the data
as reported in Reference 42 are also listed in Table 4.17.

Inspection of these results indicates that the weighted value of
the uncontrolled vehicles of 2.7 g/mi is in good agreement with the
previously estimated value of 3.0 g/mi. The significant difference in


55

co, of 5% and 2.2%, respectively. An increase in the absolute humid-
ity of the air by 50 gr/lb resulted in a 10% and 25% increase of HC
and CO emissions, respectively, had no apparent effect on No, (results
computed taking Ki correction factor into account) and resulted in a
1.5% decrease in co,. During the course of these tests, CO emissions
were in the range of approximately 1.5 to 5.0 g/mi. Data relating the
effect of cell-ambient temperature on exhaust emissions were not
reported.

The data averaged over three vehicles, previously reported by
Ford,7? detailing the effect of ambient pressure on exhaust emissions
are also listed in Table 4.10. The GM and Ford data relating barometric
pressure effects on emissions are in reasonable agreement. Ford?? also
reported that both HC and CO increased with increasing humidity for two
of the three vehicles tested and that the third vehicle's HC and CO
emissions were not affected by humidity. In contrast to the GM data,
the Ford data indicated that the No, humidity correction factor «Dp
did not adequately account for variation of NO, with humidity. Ford
reported that humidity changes did not affect CO, emissions while GM

2

reports a slight decrease in CO, as the humidity increases.

The California Air Resources Board?° reported the results of a
study designed to determine the dependence of exhaust emissions on
vehicle cold-soak temperature, encompassing the range allowed in the
federal test procedure prior to initiation of the CVS-C test. Six
1973 vehicles from various foreign and U.S. manufacturers were studied
and the averages for HC, CO and No, at 60, 73 and 86°F cold-soak
temperatures are shown in Table 4.11. These data indicate a trend of
decreasing HC and CO emissions with increasing cold-soak temperature,
which might be expected due to shorter warm-up time at higher temper-
ature. The result of little variation in NO, emissions with soak
temperature is also expected.

The CVS sample collection method involves dilution of the exhaust
gases by approximately a factor of 10. This factor when combined with


TABLE 4.16

Summary of Evaporative HC Emission Test Resylts
for 1971-1974 Certification Test Results

MODEL: YEAR NO. OF PERCENT OF TESTS PERCENT OF TESTS MAX. VALUE AVERAGE VALUE FED. STD.

TESTS LESS THAN 0.1 ¢ LESS THAN 1.0 g (gitest) (g/test) (g/test)
71 131 32 82 3.65 0.545 6.0
72 370 45 91 1.90 0.307 2.0
73 351 56 94 1.90 0.251 2.0
74 399 45 98 1.90 0.258 2.0

rest based on carbon canister trap method

REF. 42

62


114

An automobile manufacturer”? has reported that the test-to-test
fuel economy standard deviation of a single vehicle tested on a track
procedure as 1.1% of the mean. This variability may be due to the fact’
that road fuel economy data are often rejected as part of the standard-
ized test procedures if the average fuel economy for two runs up and
down the track is not within specified close tolerances.

Once the cell variation has been established, the cell-to-cell
variation in a given laboratory may be examined. Some REPCA I data for
cell-to-cell variability of fuel economy as measured on the CVS-H cycle
have been obtained, 2° In addition, similar data from another labora-
tory have been obtained for a 1973 model production vehicle on a CVS-H

cycle.7° These data are summarized below:

Total Number Total Number Total Mean Fuel _s_

Laboratory of Tests of Cells Economy X, mpg x
General Motors 70 4 13.61 1.8%
Chrysler 90 6 11.08 4.4%

The next level of complication is to determine a representative
laboratory-to-laboratory variability of fuel economy measurements. The
SAE Fuel Economy Task Force has carried out a round robin fuel economy
program for three vehicles at various laboratories. The tests were
carried out using the CVS-C test procedure and fuel economy was deter-
mined by the Carbon Mass Balance Method.7° The results of this study
are summarized in Table 5.1.

The results of another correlation study”? are listed in Table 5.2.
The tests were carried out on three vehicles operating on the CVS-H
test. The overall results listed in Table 5.2 are based on a simple
pooling of all data, .

Reference 50 has reported data relating to the vehicle-to-vehicle
variation in fuel economy among samples of identical vehicles. A test-
track procedure was used to determine the desired fuel economy and the


117

data for a large number of measurements indicated that the vehicle-to-
vehicle variation in fuel economy, ZS is 3. ‘St. Reference 50 also
reported the results of a study conducted to determine the variability
of results from both test-track and laboratory fuel economy tests. The
study concluded that with a single vehicle the true population mean can
be established within + 6.5% for the Ford City-Suburban cycle (test
track) and + 11.02% for the CVS-C cycle (dynamometer) with 90% confi-
dence, The sample sizes required to predict mean fuel economy for a
given car line within + 3% of the true population mean at 90% confi-
dence was estimated to require testing of five vehicles for the test-
track cycle compared to 14 vehicles for the laboratory dynamometer
cycle, Another source”? has reported that the fuel economy and stan-
dard deviation as percent of mean for CVS-CH tests on 38 different 1.5-
liter, stratified-charge CVCC production vehicles was 25.2 mpg and 3.6%,

respectively.

5.5 Reliability of Fuel Economy Measurements Based on Chassis Dyna-

mometer Tests

The ability of any fuel economy test procedure, incorporating a
chassis dynamometer as one of its elements, to accurately determine the
fuel economy of a vehicle over a specified.driving cycle has been ques-
tioned. It has been previously stated in Section 5.3 that there is no
inherent technical reason for eliminating the use of chassis dynamome-
tere from fuel economy testing if it can be shown that they adequately
simulate the actual inertial, aerodynamic, rolling resistance and
accessory loads experienced by a vehicle as it traverses the driving
cycle, Unfortunately, the results of definitive studies designed to
address this question are not presently available. However, due to the
importance of this issue, the limited data which are presently avail-
able concerning the repeatability and accuracy of fuel, economy test
procedures incorporating a chassis dynamometer as the elements for both
urban and highway driving cycles are discussed below.


4.0 EMISSION TEST METHODS AND PROCEDURES

4.1 Introduction

In order to enforce the provisions of the Clean Air Amendments of
1970, EPA has established emission standards, the official CVS-CH test
method and regulations prescribing requirements a manufacturer must
meet before the EPA will grant a Certificate of Conformity. A Certifi-
cate of Conformity is required before a manufacturer can produce and
sell a specific class of vehicles.

The exhaust-emission standards are summarized below:

MODEL YEAR HC co NOx
(g/mi) (g/mi) (g/mi)

1974 Federal! 3.4 39.0 3.0
1974 catit.t 3.2 39.0 2.0
1975-76 Federal” 1.5 15.0 3.1
1975-76 caliz.? 0.9 9.0 2.0
1977 Nationwide 3 3 4
Standards2 0.41 3.4 2.0
1978 Nationwide

Standards2 0.41 3.4 0.4

The certification procedure for LDMV is based on a combination
of results obtained from exhaust-emission tests at low mileage conducted
on an emission-data fleet and an estimate of exhaust-emission-control-
system-durability data obtained from a durability-data fleet. Both the
low mileage emission data and the durability data or deterioration

Based on CVS-C test.
Based on CVS-CH test.

These standards could be delayed for one year by action of the EPA
Administrator.

California may seek a waiver for a more restrictive standard for
No, for the 1977 model year.

24


149

2. Fuel Economy

a.

b.

c.

Discussion of Carbon Mass Balance Methods versus Weighing
Methods to determine fuel economy.

Discussion of chassis dynamometer ‘versus road/track test
procedures for the determination of fuel economies.

Critical evaluation of the use of chassis dynamometer
facilities to simulate road loads for fuel economy tests.
Items of particular interest include the dynamometer's
ability to accurately.simulate rolling resistance -and
aerodynamic drag. * In addition, problems associated with the
effect of cooling fan characteristics on vehicle warm-up,
etc. should be discussed.

Discussion of the contribution of various factors to the
statistical variability of. fuel economy tests.

Discussion of the relative importance of rolling resistance

and aerodynamic drag as they apply to vehicle road load as a
function of vehicle speed.

3. Vehicle Driveability

a.

b.

Discussion of qualitative test methods to determine vehicle
driveability.

Discussion of quantitative test methods to determine vehicle
driveability.

C. Experimental Results

1. Emissions

a.

b.

Data on any inner-lab and intra-lab reproducibility and/or
correlation testing programs on vehicular emissions.

Data on statistical variability of emissions from a single
vehicle undergoing many tests and/or from a group of similar
production model vehicles.

Data detailing the effect of ambient conditions (special
consideration to temperature) on emissions.

Data summarizing H,

S$, SO. and sulfate emissions from catalyst
equipped vehicles. *

2


5.4

5.5

5.6

5.7

5.8

5.9

Fuel Economy of Vehicles on the CVS-C Cycle as a Function
Of Inertia Weight... .csscscccceccccccccescscvscercvccceceesevsseees

Tire Rolling Resistance as a Function of Speed... ..ccccccseccecccecs

Horsepower Required to Overcome Inertia, Aerodynamic and
Rolling Loads as a Function of Speed for a Specific Vehicle........

Energy Balance for a Typical Spark-Ignition Engine as a
Function of Cruise Speed. .cccccccccccccccvcnccccccsccccscecesccesss

Fuel Economy for EPA Highway Cycle as Measured on Both a
Track and a Dynamometer...cccccscccecsccces

Effect of Trip Length on Cold-Start Fuel Economy Penalty
for an Urban Driving Cycle... .ccccccccccccccccccccccccccesccceccces

5.10 Effect of Ambient Temperature on Fuel Economy for Various

Types of Vehicles on the CVS-CH Test Cycle..sccccccecccccscccccsses

ix

97

100

101

103

123

125

128


132

economies than are actually warranted on the EPA highway cycle using
present EPA fuel economy test methods and procedures.

Fuel.economy measurements are, considerably more reproducible than
emissions measurements, Data’ obtained during the course of this study
indicate that fuel economy measurements employing chassis: dynamometers
for an urban driving cycle (e.g., CVS-H, CVS-C and CVS-CH tests) are
xeasonably repeatable., In:fact, the data indicate that the variability
of measured fuel economy in terms of the standard.deviation. as a per-
cent of the mean in a given cell, from cell to cell at a given labora-
tory and from laboratory,to laboratory, is in-the range of 2% to 8%Z..
The limited.data obtained for-reproducibility studies on the EPA high-
way cycle have indicated.a similar variability.

It has been reported that a large number of fuel economy measure- .
ments, carried out on test tracks, have indicated that vehicle-to-vehicle
variation ‘in fuel economy for identical vehicles is, of the order of
3.5% of the .mean fuel economy. The results of a,study designed to
determine the variability’of results from both’ test-track and chassis-
dynamometer fuel’ economy tests have also- been reported, The> study con-
cluded that. with'a single vehicle the true population mean. can, be -
established. within approximately 7%‘for a city/suburban driving cycle
on a test track and approximately 11% for the urban CVS-C test.cycle on
a chassis dynamometer with 90%. confidence. The sample,sizes required
to predict mean fuel economy for a given car. line within 3% of the true
population mean at 90% confidence were estimated to, require testing of
5 vehicles for the test- track cycle compared to 14. vehicles for the
laboratory chassis-dynamometer cycle.

Due to the potential "significance that may be attached to reported
fuel economies, of individual vehicles, it is suggested that reported
fuel economies be based on:,the results of several tests.


5.

6.

7.

ce

10.

ll.

12,

13.

14,

REFERENCES

Federal Highway Admin., "Nationwide Personal Transportation Study,"
Report Nos. 1-9, U.S. Department of Transportation, April 1972 to
November 1973.

Austin, T.C., and K.H, Hellman, "Passenger‘Car Fuel Economy Trends
and Influencing Factors," SAE Paper No. 730790, September 1973.

Teague; D.M; “Los Angeles Traffic Pattern Survey."" Vehicle Emis-
sions, SAE Progress in Technology Series, VI (New York, 1964)
pp. 17-38, 44..

Haas,.G.C., M.P. Sweeney, and J.N. Pattison "Laboratory Simulation
of Driving Conditions in the Los Angeles Area." Vehicle Emissions,
SAE ,Progress in Technology Series, XII (New York, 1968) pp. 317-324.

Kearm, D.H., and R.L.’ Lamoureux, "A survey of average driving pat-
terns in the Los Angeles urban area." TM-(L)-4119/000/01, Feb-
ruary 28, 1969.

Kruse, R.E. and T.A. Huls, "Development of the federal urban driv-
ing cycle," SAE Paper No. 730553, May 1973.

. The Federal Register, XXXV, 136 (July 15, 1970).

APRAC Project CAPE-10 Final Report, Coordinating Research Council,

" New York.

Lamureux, R.L., "Driving and vehicle use patterns in major metro-
politan cities - Phase I," APCA Paper No. 72-173, June 1972.

‘Smith, M. and M.J. Manos, "Determination and evaluation of urban
vehicle operating ‘patterns ," APCA Paper No. 72-177, June 1972.

Smith, M., and D.M. Weston, "A technique for generating representa-
tive chassis dynamometer test cycles," APCA Paper No. 72-165,
June 1972.

"Feasibility of Meeting the‘1975-76 Exhaust Emission Standards in
Actual Use," Panel on Testing, Inspection and Maintenance for the
Committee on Motor Vehicle Emissions of the National Academy of
Sciences, June 1973.

The Federal Register, XXXVIII, 84 (May 2, 1973).

"New Motor Vehicles and Engines; Air Pollution Control - 1974 Model
Year Test Results," Federal Register, XXXIX, 40 (February 27, 1974),
7664.

140


13.

14.

15.

16.

17.

18.

19,

20.

21.

22.

23.

2h.

146

Olsen Laboratories, Inc.
Anaheim, California

Emission Development
American Motors
Detroit, Michigan

Vehicle Emissions Planning
Chrysler Corporation
Detroit, Michigan

World - Headquarters
Ford Motor Company
Dearborn, “Michigan

Proving Ground
General Motors Corporation
Melford, Michigan

Bartlesville Energy Research Center
Bureau of Mines |

Bartlesville, Oklahoma

(Interview in Denver, Colorado)

Department of the Environment
London, England

Ministere.de 1'Amenagement du Territoire
Paris, France

Vereinigung Deutscher’ Automobilhersteller
Frankfurt, West’ Germany
(Interview in Geneva, Switzerland)

Advance Engineering Department

. Saab-Scania Aktiebolag

Trollhattan, Sweden

Ministero dei Transporti e dell
Aviazione Civile
Roma,. Italia

Environmental Activities Staff’

General Motors Corporation

Warren, Michigan

(Interview in Philadelphia, Pennsylvania)

May 14, 1974

June 5, 1974

June

June

June

June

June

June

June

June

June

September 5, 1974

5, 1974

6, 1974

7, 1974

11, 1974

17, 1974

18, 1974

19, 1974

24," 1974

25, 1974


Test Cell

wu PF w&

TABLE 4.6

Summary of Emission Test Variability for a 1973 Model Year
Production Vehicle in Various Test Cells at a Single Laboratory!

No, of Tests

14
13
18
18
14

mt

Me

mean emission value on CVS-H test in

1.7
1.5
1.45
1.45

1.43

HC

Ea)

8.9
14.7
12.6
12.9

13.9

11.6
10.1
11.8
11.0

12.7

co

Io

20.9
33.0
28.1
32.0

23.5

g/mi

standard deviation as percent of mean

NOx

me

2.5
2.1
2.3
2.1

2.2

Me

17.4
8.6
8.9

13.7

5.0

002

x
776
751
797
768
790

ito

2.8
3.9
3.0
4.0
6.7

REF. 26

6€


3.1
3.2
3.3

3.4

3.5

4.1

4.2

4.3

4.4

4.5

4.6

4.7

4.8

5.1

5.2

5.3

FIGURES

Distribution of LDMV Trips and Vehicle Miles Travelled...........66
Speed Versus Time Trace for the UDDS.......cccceecceccccccccacecnce

Comparison of Various Fuel Economy Driving Cycles.........

EPA Urban and Highway Fuel Economy Driving Cycle Velocity

Distributions. .cecccccccccccccccscevesccesscnseessseessssesseresese

Proposed Correlation for Fuel Economy Driving Cycles.....cescseeees

Lab-to-Lab Emissions Correlation Test for a Relatively
Stable Vehicle... ..cceccsccccsccccccsccccsccnccerssescssescrecseeses

Factors Affecting Uncertainty in Exhaust Emission Mass

Measurement ...sesececccvccccvcccccsccccrccavcvcessssesssvceesesees

Sources of Variability and Probable Relative Contribution
for Mass Emissions Errors on the CVS-CH Test at 1975-76
California Levels...cscccccccccccccccececescccceccecceseseseesesees

Effect of Ambient Temperature on Exhaust Emissions......

Effect of Ambient Temperature on HC Exhaust Emissions
During the CVS-CH Test.ccccccecccccccccccccrccccsecccscesscesceesece

Effect of Ambient Temperature on CO Exhaust Emissions
During the CVS-CH Test. .ccccccccccccccvvccvccccccscvccsvcccccsceces

Effect of Ambient Temperature on NO| Emissions During
the CVS-CH Test....ssseccsscsececcsrtecseescesensesceecsenseseeees

Alternate Methods for Evaluating the Deterioration of
Emission-Control Systems........cceeceeceeceee

Cruise Road Load Fuel Economy Versus Speed for Three
Vehicles.......04

Fuel Economy Ranges for Three Vehicles on Different
Driving Cycles. ....cccccccc ccc cccc cece cc ecccceccsecececcesseceeces

Vehicle Weight Versus Model Year for Two Standard-Size

Vehicles... ccocsccccccccccsccscccccccccecsscecsssessscesesssessssees

vili

11
14

17

18

22

43

48

49

64

67

68

69

14

92

93

96


33

are designed to minimize the importance of vehicle variability on the
total emissions variability in order to evaluate cell-to-cell and
laboratory-to-laboratory variability. In general, these tests have
been carried out by measuring the exhaust emissions of a "hot" or
fully warmed-up vehicle on the federal driving cycle. Data obtained
in this manner, subsequently referred to as CVS-H data, are compared
to data obtained on the CVS-C and CVS-CH cycles whenever possible.
Data obtained during the course of the present study, designed to
assess exhaust-emission variability, are presented below.

During early 1972, EpaZ? carried out 30 CVS-CH tests on a 1971
Ford Ranch Wagon with a 429 CID V-8 automatic transmission, air
conditioning, evaporative-emission control and a 4-bbl carburetor to
determine the exhaust-emission variability of a single vehicle tested
in the same test cell. The same CVS system and analytical equipment
were used throughout the project. The mean and standard deviation for bag
Py and No, of
all 30 tests are presented in Table 4.2. The environmental conditions

1, bag 2, bag 3 and the composite value for HC, CO, CO.

in the test cell during the course of the test program are also sum-
marized in Table 4,2.

Inspection of these results indicates that the standard deviation
of the composite value for 30 tests ranged from a low of approximately
2% of the mean for co,
mean for HC, (It should be noted that this vehicle has mean emissions
higher than the 1975-76 emission standards.)

to a maximum value of approximately 14% of the

The emissions were correlated with relative humidity, ambient
temperature and barometric pressure. It was reported that a strong
correlation was found between all CO mass emissions, except for the
cold-start phase, and barometric pressure. No, cold-start and
stabilized mass emissions correlated with ambient temperature and No,
stabilized and hot-start emissions were found to correlate with relative

humidity.


113

fuel economy and standard deviation as percent of the mean of 10,31 mpg
and 2.6%, respectively. Since the CVS-CH procedure has a cold start
and a hot start, the emission data for this vehicle in a given cell can
be used to calculate both hot-start and cold-start fuel economy. Emis-
sions from bag 1 were used to calculate a cold-start fuel economy while
emissions from bag 3 were used to compute the hot-start fuel economy.
The hot-start fuel economy and standard deviation as percent of the
mean were computed to be 11.85 mpg and 2.5%, respectively, as compared
to the cold-start values of 10.03 mpg and 2.6%.

Another study, previously discussed in Section 4,3, reported co,
emissions for 16 CVS-CH tests of a Chevrolet Impala equipped with an
oxidizing catalyst in a single test ceil.?9 As shown in Table 4.3, the
co, standard deviation as percent of the mean was reported to be 1.2%.
As previously stated, this indicates that the fuel economy variation as
percent of the mean was also approximately 1.2%.

The fuel economy variation of a 1973 model-year production vehicle
has been reported for a number of different cells at the same labora-
tory.26 A CVS-H test procedure was followed and the fuel economy was
computed based on the Carbon Mass Balance Method, The range of data
obtained in five different test cells is given by

Mean Fuel Economy
Number of Tests For_Each Cell Ss

at Each Cell X, mpg x
13-18 10.83-11.51 2.8%-5 5%

A vehicle equipped with an oxidizing catalyst has been tested sev-
eral times over the CVS-CH cycle in various cells at Chrysler Corpora-
tion and three times in one test cell at EPA in Ann Arbor.7° Fuel
economy was not reported, but the co, standard deviation as percent of
mean (see Table 4.6) was 10.6% and 2.1% at Chrysler ‘and EPA, respec-
tively.


12

for trips that were close to 5 miles (4 to 7 miles) or close to 10
miles (9 to 13 miles). Inspection of the VMT distribution indicates
that more miles are driven for trips within 0.5 miles of 4.5 miles than
trips over any other one-mile interval.

It has been reported, based on data from the Federal Highway
Administration, that the ratio of rural miles driven to urban miles
driven has varied historically due to increased urbanization from 1.1
to approximately 0.82 at the present time.”

3.3 Development of Driving Cycles for Emissions

Early work in the 1950's culminated in the development of the
California seven-mode cycle. The seven-mode cycle? was intended to
represent average driving conditions throughout Los Angeles County
during both peak and off-peak traffic conditions. Subsequent studies
concluded that an emissions driving cycle should not represent twenty-
four-hour, county-wide vehicle operation but that it should concentrate
on the type of driving that contributed to peak primary pollutant
levels in the Los Angeles basin. It was also determined that the
major contributor to Los Angeles smog was the morning home-to-work
trip, and it was proposed that prevalent operating modes during this
trip could be identified and subsequently reproduced on a chassis
dynamometer. Once the various driving modes in urban Los Angeles were
classified, a continuous road route, which contained segments such that
the total route represented the Los Angeles morning trip to work, was
developed. A 12-mile-road route, called the "L.A.-4 route," centered
on the downtown Los Angeles area, was chosen to simulate weekday
morning peak driving conditions. Typical speed profiles of a drive
over the L.A.-4 were obtained with a series of test vehicles. Since
the average trip length in the Los Angeles area was reported to be 7.5
miles,” EPA undertook the development of a 7.5-mile urban dynamometer
driving schedule (UDDS) based upon the full L.A.-4 driving cycle. The
upps® is a speed trace consisting of 18 profiles separated by idle


magnitudes of the various factors affecting both systematic and random
errors encountered during CVS-CH tests are considered, and potential
changes in the test method designed to improve the statistical repro-
ducibility of exhaust-emission tests are discussed. Other important
factors such as the effect of ambient conditions on exhaust emis-
sions, the effectiveness of the test methods and procedures employed
to obtain durability data, test methods and aprocedures associated
with LDMV evaporative-HC emissions and other related emission infor-
mation are included in Section4.0.

Due to the present and projected energy shortages, considerable
national attention has been recently focused on the fuel economy of
LDMV. Unfortunately, at the present time generally accepted stan-
dardized fuel economy test methods and procedures are not available.
Section5.0 summarizes and evaluates information presently available
concerning the important factors affecting fuel economy, the advantages
and disadvantages of alternate fuel economy test methods and procedures,
the statistical variability of fuel economy measurements and the effect
of cold-start and ambient temperature on LDMV fuel economy. Finally,
Section 6,0 summarizes the conclusions reached during the course of

the present study.


5.0 Fuel Economy Test Methods and Procedures..

S.L Introduction....cceccccscceccccccccccccecsccesssceses
5.2 Factors Affecting Fuel Ecomomy.......scossceccseccece
5.3 Test Methods and Procedures.....sseseesserscseseceoee
5.4 Statistical Variation of Fuel Economy Measurements...

5.5 Reliability of Fuel Economy Measurements Based on
Chassis Dynamometer TeStsS........secccscccccvesecsecs

5.6 The Effect of Cold-Start and Ambient Temperature on
Fuel ECOnomy.....cceescccccccccece

5.7 SUMMALY....cccccsecccccc cece cenecesesecessesesseseere
6.0 Evaluation of the Data....csccccesccscecccccccccencreceece
6.2 Conclusions......cerecceccccccnceccvcccsesssssssorees

References...

Append1xeS...cececccccnccccccccncrecesceccccnccerecsseeeseceees
A. Organizations Site-Visited or Interviewed...........+.

B. General Questions from the Consultant on Testing......

GLOSSATY. ccc c cre ec rece eee eee eee cece ese est eee ess easeseesenere

90
90
91
106
112

117

124
129
133
133
133
140
145
145
148
151


100 - - - —

90

80r

60-

50- © Pre-Emissions

Controlled Vehicles (Ref. 54)
40- xO 4 1973 Vehicles

SAE Task Force Data (Ref. 50)
30F,

20

FULLY WARMED-UP FUEL ECONOMY (%)

10
| |__| | { 1 on oe 1 {ot { J

i
1 23 4 5 6 7 8 9 10 11°12 °13 14 15 16
TRIP LENGTH (mile)

FIGURE 5.9 Effect of Trip Length on Cold-Start Fuel Economy Penalty
for an Urban Driving Cycle

17

i
18

S2T


103

Cooling Water

Heat Rejected

HEAT SUPPLIED (%)

Heat Available to
Propel Vehicle
and Accessories

30 40 50 60 £ /
SPEED (mph)

FIGURE 5.7 Energy Balance for a Typical Spark-Ignition Engine as a
Function of Cruise Speed *(Pumping losses occur during the intake
stroke and partial throttle setting and result from the piston pushing
against the atmospheric pressure in the crankcase offset by partial
vacuum in the combustion chamber.)

REF, 49


62

vehicles. 1? The data listed in Table 4.3 indicate that the cold
transient phase of the CVS-CH test accounted for 87% and 94% of the
total mass of HC and CO, respectively, for a vehicle equipped with an
oxidation catalyst.?? In addition, these data indicate that the varia-
tion in HC and CO during the cold transient phase accounted for 99% of
the total variation in HC and CO during the CVS-CH test.

Data reported by Reference 33 can also be employed to investigate
the effect of ambient temperature on the total mass of HC, CO and No,
produced during each of the three phases of the CVS-CH test for four
prototype 1975 vehicles equipped with oxidation catalysts, At an
ambient temperature of 75°R, the average value, taken over all four
vehicles, of the total mass of HC and CO collected in the cold transient
bag accounted for approximately 64% and 73% by mass of the pollutants
collected in the three bags, respectively. Under these conditions,
the average composite CVS-CH emissions for these vehicles were 0.49,
5.5 and 2.32 g/mi for HC, CO and No, respectively.

In addition to the composite emissions presented in Table 4.5,
modal emission data are also available for the vehicles equipped with
2.0 liter CVCC stratified-charge engines.”> In these vehicles, the
cold transient phase account for approximately 50% to 60% and 30% to
40% of the total mass of HC and CO collected during the CVS-CH test,
respectively.

In the present CVS-CH test procedure,the total mass of pollutant
emissions in the cold transient, hot transient and stabilized portions
of the test are weighted by 0.43, 0.57 and 1.0, respectively. There-
fore, the contribution of the cold transient phase to the computed
vehicular composite emissions in grams per mile is not only dependent on
the total mass of pollutant collected but also on the weighting factors.

4.5 Effect of Ambient Temperature on Exhaust Emissions

It has been previously reported that exhaust emissions!” on the
CVS-C test for vehicles soaked at either 20°F or 40°F were significantly


L

SAE Interstate 70

=

7

SAE Urban

TO

[ 4

nome

EPA Highway
ooo SAE Suburban

13

12

11

10

Trieste t | | TT

U

[=)
7

g g = 8

(ydw) GaadS

ELAPSED TEST TIME (min)

FIGURE 3.3 Comparison of Various Fuel Economy Driving Cycles

REF, 16, 18


8.

10.

136

in comparison to 75 °F, The No, emissions for these same vehi-
cles increased by approximately 33% over the same temperature
interval.

Statistical variability associated with the evaluation of dete-
rioration factors, often obtained from tests on a single
durability-data car, may reflect the special circumstances of
the test rather than the capability of the underlying technol-
ogy. An averaging procedure over a larger group of similar
vehicles might be preferable. However, averaging, if used too
extensively, treats all vehicles and systems as equal, and
attractive technologies are counterbalanced by less desirable ;
technologies.

The critical elements in any standardized fuel economy test
method and procedure include: a representative standard driv-
ing cycle or cycles; a method to determine the mass or volume
of fuel consumed and the distance traveled during the test;. and
a procedure for simulating vehicular loads encountered during
the course of the driving cycle.

Significant vehicular miles are driven in both urban and non-
urban environments and fuel economy in these two driving modes
may differ by approximately 50%. Two fuel economies, one ,
designed to represent urban driving and one designed to repre-
sent highway driving, will provide the required basis for eval-
uating the relative fuel economies of various automotive
designs and comparing the relative fuel economies of one vehi-
cle versus another.

It has been shown: that severe fuel economy penalties are
incurred when an LDMV is driven on a short trip that is initi-
ated from a cold-start condition, Since a significant number
of urban trips are very short and initiated from a cold start,
an urban fuel economy driving cycle should include a cold-
start phase.


and exhaust emissions would reduce statistical variations in CVS-CH
exhaust-emission-test results,

F, Ambient temperature variations, commonly encountered in large
sections of the nation during winter, can significantly increase ex-
haust emissions of HC and CO above the emissions measured during the
course of the CVS-CH test.

G. Statistical variability associated with the evaluation of
deterioration factors, often obtained from tests on a single durability-
data car, may reflect the special circumstances of the test rather than
the capability of the underlying technology. An averaging procedure
over a larger group of similar vehicles might be preferable. However,
a too-extensive use of averaging treats all vehicles and systems as
equal and, hence, attractive technologies are counterbalanced by less
desirable technologies.

H. In order to obtain a reasonably accurate determination of the
fuel economy of a vehicle, two fuel economies, one designed to repre-
sent urban driving and one designed to represent highway driving, are
needed. to provide rational consumer choice.

I. It has been shown that severe fuel economy penalties are in-
curred when a light-duty motor vehicle is driven on a short trip that
is initiated from a cold-start condition. Since a significant number
of urban trips are very short and initiated from a cold start, an
urban fuel economy driving cycle should include a cold-start phase.

J. The CVS-CH driving cycle is a sufficiently accurate represen-
tation of urban driving patterns to be used as the urban fuel economy
driving cycle.

K. Either the Carbon-Mass-Balance Method or the direct measurement
of the mass or volume of fuel consumed can be employed to obtain
accurate (less than 5%) measurements of fuel consumption.

L. There is no inherent technical reason for eliminating the use

of chassis dynamometers in fuel economy testing.


1.

134

Recent data, obtained utilizing the SHED method, indicate that
evaporative HC emissions from vehicles equipped with present-
technology, evaporative-control systems are of the order of

1. 9 g/mi which is larger than the 1975-76 federal HC exhaust
emission standards of 1.5. g/mi. These results were ‘obtained
on systems in which évaporative HC emissions were “reportedly
95% controlled with ¥espect to uncontrolled HC, evaporative
emission levels of approximately 3.0 g/mi. Therefore, an accu-
rate test method and procedure for measuring evaporative HC
emissions must be “developed and ‘implemented as soon as pos-
sible. Careful evaluation ‘of the situation may show that the
SHED method is adequate for this purpose.

The driving cycle associated with the CVS-CH test was found to
represent an average. urban trip "as well as it needs to" for
purposes of determining LDMV exhaust emissions.

Significant consequences should not be attached to a single
CVS-CH exnaust-emissions test since both random and systematic
errors contribute, to poor repeatability of exhaust-emission
test results for a given LDMV. Various ‘factors, including
vehicle variability,’ emission collection and measurement vari-
ability and environmental test variables, contribute to the
poor test reproducibility. Variations in exhaust-emission
measurements specified in terms of the standard deviation as a
percent of the mean for a 1975-76 vehicle in a given cell or
from cell to cell-at. one laboratory’ for most engine-control
system configurations can be expected to range between 10% to
25%, 15% to 30% and 5% to 15% for HC, CO and No, respectively.
Significant systematic errors in, mean emission values of a
given test vehicle of:as much as 20% to 30% have been reported
between various emission-testing laboratories. Establishment
of ‘mandatory correlation ‘test programs among governmental,

automotive manufacturers’ and other test laboratories that are


22

5.0
ojo
4.57
°o
GM Central Business
District Schedule
SAE Urban
3.5
w
z © = Actual Car Data Point
z B = GM Simulated Schedule
W 3.0, @ = SAE Track
2 4 = EPA Dynamometer
fe) oO
&
w 2.5- EPA-Urban
° CVS.C
« o
yw EPA-Urban
2 * CVS.CH
2.0-
3 °
° °
GM Suburban City Schedule
1.5P
1.0-
SAE Suburban
| GM Highway Schedule
0.5 SAE Interstate (55 mph)
| | GM
oe Interstate
0 10 20 30 40 50 60 70
AVERAGE SPEED (mph)

FIGURE 3.5 Proposed Correlation for Fuel Economy Driving Cycles
Test Results, Summer, 1971, Phoenix and Central Arizona

REF, 19


91

5,2 Factors Affecting Fuel Economy

The important factors influencing fuel economy of a LDMV include
the driving cycle, the vehicle characteristics, the installation of
emission-control systems, the driving habits of the consumer and the
ambient conditions, including the effect of cold start. The fuel
economy of a given vehicle is strongly dependent on the driving cycle
employed during the test. The fuel economy tends to be maximized
under steady-state cruise conditions. In general, steady-state cruise
fuel economies tend to increase as the speed is increased from low
values, reach a peak in the range of 30 to 50 mph and then decrease
significantly at higher speeds. The effect of steady cruise speeds on
the fuel economy of a 2,100 1b subcompact, a 3,500 1b intermediate and
a 5,200 1b luxury sedan is shown in Figure 5.1.46 Figure 5.2 compares
the 40 to 70 mph fuel economy of these three vehicles with the fuel
economy obtained over an urban driving cycle used by Chrysler.*°
Inspection of these results indicates that the best fuel economy for
each vehicle (at 40 mph cruise) is higher by more than a factor of
two than its poorest (cold urban cycle) fuel economy, In addition,
the fuel economy of a given vehicle is approximately 50% greater for
a typical highway cycle than for a typical urban cycle.

The design characteristics of a vehicle strongly influence its
fuel economy. In general, the fuel economy of a vehicle on any given
driving cycle is affected by: (1) inertia forces that are dependent
on the vehicle's mass and acceleration; (2) road load that includes
rolling resistance and aerodynamic drag; (3) engine efficiency;

(4) drive-train efficiency, including the effects of vehicle trans-
mission and rear axle ratio; (5) accessories, including air condition-
ing, power steering, etc.; and (6) emission-control devices. Many of
the above factors are interrelated, e.g., heavy vehicles tend to have
larger frontal areas than lighter vehicles, and, hence, both the

inertia forces and aerodynamic drag are often increased on heavy


6.0 EVALUATION OF THE DATA

6.1 Summary

The important aspects of present and projected emission and fuel
economy test methods and procedures for LDMV have been considered.

The CVS-CH exhaust emission test procedure plays an important role in
the certification process for 1975 and subsequent model-year LDMV.
Hence, the statistical variability of CVS-CH exhaust emission tests for
these vehicles and the relative magnitudes of the various factors
affecting both systematic and random errors encountered during CVS-CH
tests were discussed. Additional questions concerning the effect of
ambient temperature on exhaust emissions, the suitability of present
exhaust emission-control durability test methods and procedures and the
possible modifications of the present HC exhaust-emission standards and
measuring: techniques designed to account for only reactive HC were also
addressed. Finally, recent data relating to the effectiveness of pre-
sent evaporative HC emission-test methods and procedures and LDMV
evaporative-control systems were presented and discussed.

At the present time, generally accepted standardized fuel economy
test methods and procedures are not available. Due to the significance
of this issue, it is important that standardized test methods and proce-
dures, based on sound engineering and scientific considerations, be
developed as soon as possible. In the general area of fuel economy,
the important factors affecting LDMV fuel economy, the important ele-
ments in any standardized fuel economy test method and procedure, the
currently proposed test methods and procedures and the statistical
variability of fuel economy measurements were considered in some
detail.

6.2 Conclusions

The major conclusions reached during this study have been summa-
rized in Section 1.2. A more detailed summary of the major conclusions

and the supporting data are given below:

133


84

It is generally agreed that oxidation catalysts in emission-
control systems may preferentially reduce the photochemically reactive
portion of the hydrocarbon exhaust. This then leads to the conclusion
that the current "total" hydrocarbon standard may unnecessarily penalize
vehicles equipped with this type of control system. Thus, the
conversion of motor-vehicle exhaust hydrocarbon standards to a
nonreactive basis may be a technically desirable goal. However, it is
believed that such a change would require significant expenditures of
resources by the EPA, motor-vehicle manufacturers, and other motor-
testing laboratories for modification of existing equipment and
procedures. Furthermore, substantial efforts must also be made to
establish revised testing procedures and to determine the magnitudes
of nonmethane hydrocarbon emission standards equivalent to present
total hydrocarbon standards. In order to obtain information associated
with these questions and in response to the petition by Ford,” the EPA
has recently reported that it is considering changing HC regulations to
include only nonmethane hydrocarbons and has requested that all
interested parties provide information concerning the following points:

(1) Identification of nonreactive hydrocarbon components of

motor-vehicle exhaust which should be excluded in determining
compliance with motor-vehicle emission standards, EPA has
identified ethane, propane, acetylene, and benzene in addition
to methane.

(2) Availability of methods for routine measurement of nonreactive

hydrocarbon components in motor vehicle exhaust,

(3) Quantities of reactive and nonreactive hydrocarbon compounds

in motor vehicle exhaust.

(4) Impact of total versus reactive hydrocarbon standards.

(5) Lead time required for implementation of nonreactive hydro-

carbon testing.

(6) Impact of reactive hydrocarbon standards on other motor

vehicle compliance efforts.


M. Definitive studies designed to evaluate the ability of chassis
dynamometers to accurately simulate vehicular fuel economy for a
variety of driving cycles have not been reported.

N. Fuel economy tests incorporating chassis dynamometers can be
successfully employed to determine fuel economies for urban driving
cycles.

0. Certain vehicles may obtain. higher fuel economies than are
actually warranted on the EPA highway cycle using present EPA fuel
economy test methods and the dynamometer loads specified in the
Federal Register.

~. Reported fuel economies should be based on the results of

several tests even though these tests are relatively reproducible,


5.0 FUEL ECONOMY TEST METHODS AND PROCEDURES

5.1 Introduction

Due to the present and projected energy shortages, considerable
national attention has been focused recently on the fuel economy of
LDMV. The development of a rational energy conservation strategy
for the transportation sector requires, among other things, a detailed
understanding of the factors that influence automotive fuel economy
and the development of standardized fuel economy test methods and pro-
cedures. The short-term need is to assess, approximately, the validity
of present fuel economy tests. The medium-term need is to develop a
standardized fuel economy test method and procedure which are repre-
sentative of average nationwide driving patterns and mileage accumula-
tion, The long-term need is for a more accurate data base which can be
employed to make projections of the effects of changes in vehicle tech-
nology and use patterns on total U.S. fuel consumption.

Until recently, automotive fuel economy has been primarily the
concern of the automotive manufacturers. However, in the past few
years, both the public and the government have taken a much more
active interest in this area due to the general unavailability and
increasing costs of automotive fuel. Unfortunately, at the present
time, generally accepted standardized fuel economy test methods and
procedures are not available. Due to the significance of this issue,
it is important that standardized fuel economy test methods and pro-
cedures, based on sound engineering and scientific considerations, be
developed as soon as possible.

The present section has been written in an effort to summarize
and evaluate information presently available concerning the important
factors affecting fuel economy, advantages and disadvantages of alter-
nate fuel economy test methods and procedures, statistical variability
of fuel economy measurements and to discuss the effect of cold-start

and ambient temperature of LDMV fuel economy.

90


95

2. The intermediate-class car of 1974 weighs about the same as the
standard size car of 1970 (approximately 4,200 1b curb weight).
Similarly, the compact car of 1974 has about the same curb weight
as the intermediate car of 1966 to 1970 (approximately 3,300 to
3,600 1b).

3. The overall sales-weighted curb weights of U.S. passenger cars
dropped sharply from the 1958 level (approximately 3,700 1b) to
approximately 3,450 1b in the 1960 to 1964 period. This was due
to the introduction.of compacts in 1960 and high sales of both
compacts and intermediates in that period. Since 1964, sales-
weighted curb weights have risen steadily, reaching approximately
3,650 1b in 1973,

4, The overall U.S. sales-weighted inertia test-weight average
(including domestic and foreign cars) has the same general pattern
as curb-weight variation with time. It dropped sharply from the
1958 level (3,967; 1b) to its lowest value of 3,712 1b in 1961.
Since 1961, there has been a steadily rising sales-weighted iner-
tia test-weight’ trend, reaching a new high value of 3,968 1b in
1973.

5. Curb and inertia test-weight values for domestic passenger cars
surpassed their 1958 levels in 1970 and appear to be ona still-
rising trend, For example, the sales-weighted inertia test-
weight average, for domestic cars only, was 4,223 1b in 1973, com-
pared with 4,096 lb in 1958.

Figure 5.3, which was taken from Reference 47, clearly indicates
the general pattern of these weight trends.

The influence of inertia weight on vehicle fuel economy measured
on a cold urban driving cycle for 1973 model-year vehicles and an
average of pre-emission-controlled (1957-1967) vehicles was also
reported in Reference 47. These results are listed in Figure 5.4.
Inspection of Figure 5.4 indicates that the fuel economy penalty of a
heavy car, from all causes, is very large when compared to light vehi-
cles. It should be noted that although this graph shows a general
trend with higher fuel economy at lower inertia weights, the trend is
increased by other external factors, such as the consideration that
lighter cars tend to have smaller engines, manual transmissions and
fewer accessories. These external factors also tend to increase the
fuel economy of the lighter cars with respect to heavier cars. Also,


ill

EPA has simultaneously measured the fuel economy and emissions of
LDMV operating on both the CVS-C and CVS-CH test cycles, The test
cycles have been driven on a chassis dynamometer and the test methods
and procedures have been similar to the one utilized during the course
of emission testing. The fuel consumed during the test has been gener-
ally measured by the Carbon Mass Balance Method, and the fuel economy
has been computed by dividing the eycle distance by the volume of fuel
consumed, during the course of the test, Data obtained in this manner
have taken into account effects due to both cold-start and hot-start
conditions, and the results have been reported as representative of
urban fuel economy.

In addition to measuring and reporting urban fuel economy as
determined during the CVS-CH test, EPA plans to measure and report
highway fuel economies for 1975 model-year vehicles. The EPA highway
cycle (see Section 3.4) will be employed for these tests. As in the
case of the urban fuel economy data, the cycle will be driven on a
chassis dynamometer, the fuel consumed will be measured by the Carbon
Mass Balance Method, and the vehicle's highway fuel economy will be
computed by dividing the length of the highway cycle by the fuel con-
sumed, These results will correspond to a hot-start highway driving
cycle since the highway cycle will be driven after the CVS-CH cycle is
completed,

The SAE
fuel economy measurements based on a road and track test procedure. .

18 has recently adopted a set of recommended practices for

Reference 18 recommends four driving cycles (see Section 3.4), all of
which are to be driven on a road or track, Complete specifications of
the recommended practice may be found in Reference 18. All tests are
to be carried out on a fully warmed-up vehicle. Fuel economy will be
based on the average fuel consumed and distance traveled on two suc~
cessive runs over the course. The test is to be repeated until two
successive tests repeat within 2% for fuel consumption and 1% for
elapsed time, The measured fuel economy is subsequently corrected to


58

TABLE 4.12

Typical Pollutant Concentrations in Exhaust Emissions
Sample Bags at Various Emission Levels

1975 California Standards HC co NOx

Standards, g/mi 0.9 9 2.0
Sample bags, ppm

cold transient 40 600 90
stabilized 18 200 40
hot transient 33 341 90
Typical Ambient Background 5 8 1

Concentrations, ppm

1978 Standards

Standards, g/mi 0.41 3.4 0.4
Sample Bags, ppm

cold transient 22 133 9
stabilized 6 6 4
hot transient 9 12 9
Typical Ambient Background 5 8 1

Concentrations, ppm

REF. 12, 29


64

250/-—

200}—

gq
[=]

°
i=)

a
i=]

J ot | f | 4 a |
-10 0 610 20 30 40 «50 6X70 80 90

ENGINE TEMPERATURE AT START-UP (°F)

-50/- N

i=]

DEVIATION IN EMISSIONS FROM 60 °F (%)

-100L-

FIGURE 4,4 Effect of Ambient Temperature on Exhaust Emissions

REF, 34


3.2 Vehicle-Use Patterns

Probably the most comprehensive study of LDMV-use patterns was
carried out by the Federal Highway Administration during 1969 and 1970.
Selected high-lights from this nine-volume report! “are summarized below.

The average LDMV is driven 11,600 miles per year. Annual vehicle
mileage accumulation is maximum for new vehicles and reduces with
vehicle age. The annual mileage accumulation per vehicle increases as
the number of vehicles per household increases,

The average household was found-to make 3.8 trips per day and the
average trip length was approximately 8.9 miles. Trips to work
represented approximately one third of all trips made and represented
approximately one third of all miles driven by LDMV. The average
trip to work is 8.9 miles even though 52% are 5 miles or less.

The percentage of vehicle trips of various lengths as a function of
season of the year was also reported in Volume 3 of Reference 1. These
results are reproduced in Table 3.1 and the annual distribution of the
percent of trips as a function of trip length is graphically represent-
ed in Figure 3.1. Inspection of Figure 3.1 indicates that most
frequently made trips are less than one mile long.

Since the length of the most frequent trips is very short, most of
the vehicle miles traveled (VMI) are accumulated during trips of longer
duration. A VMI distribution as a function of trip length may be
computed from a knowledge of the frequency of trips as a function of
trip length. The distribution of the percent of VMT as a function of
trip length is also plotted in Figure 3,1. Direct utilization of the
data in Table 3,1, for the computation of the VMT distribution, would
result in the noncontinuous plot shown in the insert in Figure 3.1. The
WMT distribution represented in Figure 3.1 is based on a smooth curve
drawn through the data. The noncontinuous distribution of VMT shown in
the insert apparently results from many of the individuals sampled
responding with either "5 miles" or "10 miles" as the distance

*References are listed at the end of the report (page 140).


FUEL ECONOMY (mpg)

40,

30)

20)

10)

=}

92

Subcompact,
4cyl Engine,
Manual Transmission

Intermediate,
V8 Engine, Automatic
Transmission

ry Sedan,
V8 Engine, Automatic

Transmission

lek | |
20 30 40 50 60 70

SPEED (mph)

FIGURE 5.1 Cruise Road Load Fuel Economy Versus Speed for Three

Vehicles

REF. 46


1975 Hot Run ———_—__——»

SPEED (mph)
ssssss

1 i
1 2 3 4 5 6 7 8 9 10 11 12

ELAPSED TEST TIME (min)

i=]

SPEED (mph)

13 14 15 16 17 18 19 20 21 22 23
ELAPSED TEST TIME (min)

FIGURE 3.2 Speed Versus Time Trace for the UDDS

REF, 7

41


43

o +2s:
z NX ff
Si. NA
¢ "4 Y
J -2—
305
1
257
1 ox Lah |

4

CO (g/mile)
a 8
oro on oo on
x
He

“| -2s

a5]
4, A =
Bs 204 aren ot +

E J |

2 4 1 c lw
co hl ol vw. eta aA \w
Z 45-4 vw. |son| EPA] EPA | Mob- ww. rk lo
‘ wos | Lab} R c ta. |r lc LA. a le
n=13 | n=2] n=3 n=3 n=4 n=2_ n=2) np n=3 | n=6

FIGURE 4,1 Lab-to-Lab Emissions Correlation Test for a Relatively
Stable Vehicle

REF. 27


88

It has been shown that ambient temperature variations, commonly
encountered in large sections of the nation, can significantly
increase exhaust emissions of HC and CO for both pre-1975 production
vehicles and 1975 prototype models equipped with oxidation catalysts.
As an example of this effect, the HC and CO emission from four
prototype catalyst-equipped vehicles were shown to increase by 160%
and 409%, respectively, over the temperature range 75 °F to 20 OF.

The NO, emissions for these same vehicles increased by approximately
33% over the same temperature interval. Therefore, it can be
anticipated that starting a vehicle at temperatures commonly
encountered during winter in large sections of the nation, e.g., 0 oF -
32 °F, would cause large increases in exhaust emissions.

Until recently, it had been assumed that evaporative HC emissions
had been 95% controlled with respect to uncontrolled evaporative
emissions. This conclusion was based on evaporative-emission tests
employing the carbon-canister trap method. Evaporative HC emissions
measured in two recent surveillance programs, employing the SHED
method for both precontrolled and controlled evaporative emissions
systems, indicate that this conclusion is not correct.

These data indicate that vehicles which are supposed to have 95%-
effective evaporative-emission controls, have evaporative HC emissions
that are larger than the 1975-76 exhaust emission standards when both
are compared on a grams per mile basis.

In light of these results, an accurate test method and procedure
for measuring evaporative HC emissions must be developed, which
corresponds closely to "real life." It is possible that a careful
evaluation of the situation may show that the SHED method is adequate
for this purpose, Also, an extensive study should be undertaken to
determine the relative importance and effectiveness of control
strategies designed to control automotive HC emissions based on both

exhaust and evaporative-emissions standards.


26

Scheduled maintenance of durability vehicles may be performed at the
same mileage intervals as specified to the consumer. Scheduled major
tune-ups tomanufacturer's specifications may be performed’nd more
frequently than every 12,500 miles. The replacements and adjustments
allowed are detailed in the Regulations. Emission tests must be run
before and after any vehicle maintenance that may be reasonably expected
to affect emissions. The manufacturer has the option of running more
than one durability-data vehicle in each engine-system combination and
up to three valid CVS-CH tests at each mileage point may also be run
provided that the same number of tests are conducted at each mileage
interval. Once a durability-data vehicle is started in the fleet,

it must continue to operate unless discontinued by written consent of
the EPA Administrator.

All the applicable data generated for each engine-system combina-
tion are used to compute separate deterioration factors for HC, CO
and NOx for each engine-system combination in the durability-data fleet.
The applicable emission data are plotted as a linear function of mile-
age and the best straight lines, fitted by the method of least squares,
are computed for each set of data. The interpolated 4,000 and -50,000-
mile points of the lines must be within the specified emission stand-
ards or the data cannot be used for the calculation of a deterioration
factor. Deterioration factors for each of the three pollutants for
each engine-system combination are subsequently computed by taking the
ratio of the emissions at 50,000 miles to the emissions at 4,000 miles
from the appropriate least-squares fit line.

Each data car in the emission-data fleet: is subsequently tested
for certification by multiplying its exhaust-emission test results,
obtained after it has been driven 4,000 miles, by the appropriate
deterioration factor to obtain the adjusted emissions for the vehicle.
These adjusted emissions are then compared to the standards, and if the.
adjusted emissions for all pollutants are below the appropriate stand-
ards, the car passes; if not, it fails. In the event that the car


126

indicates that trip length and necessary warm-up have significant
effects on fuel economy.

The original data in Figure 5.9, in terms of percent of fully
warmed-up fuel economy versus trip lengths, were obtained from Refer-
ence 54. These data were obtained for a fleet of pre-emission-control
vehicles which were equipped with .automatic transmissions and automatic
chokes, The vehicles were operated on a simulated city-traffic sched-
ule with a cold start under varying weather conditions. From this
graph, it is seen that the average fuel economy for a trip of approxi-
mately four miles is only about 75% ofthe expected fully warmed-up
fuel economy, As is seen, the vehicle's average fuel economy approaches
the fully warmed-up value only if the trip length is relatively long.

Recently, questions have been raised concerning the validity of
these results for vehicles equipped with modern emission controls. In
conjunction with the work of the SAE Fuel Economy Task Force, typical
cold-start fuel economy data were obtained for a 1974 sports compact
and a 1973 intermediate vehicle,>° ‘Two conditions were studied: one
where the vehicle soak temperature was in the range from 25 oP to 45°R
(outdoor soak) and one where the soak range was from 65 °F to 70°F
(indoor soak). ‘The data averaged for a number of urban cycle tests
conducted on two vehicles of each type are also plotted in Figure 5.9.

Inspection of these results indicates that vehicles with advanced
emission-control systems show the same cold-start fuel economy penal-
ties for various trip lengths as vehicles without emission controls.
This result may be due to the fact that the warm-up of many non-emission
control related: components (e.g., water jacket, transmission, rear end,
tires, etc.) may significantly affect cold-start fuel economy,

Since the warm-up effect as discussed is thermal, ambient tempera-
ture could also be expected to’ influence fuel economy. Data reported
in Reference 54 indicate that a vehicle will warm up more quickly as
.the ambient temperature increases. These results indicate that a driver
in a cold climate who drives his vehicle for many short trips can expect


TABLE 3.1

Percentage of Vehicle Trips by Lengths and Season of Year

Season Length of trip (miles)

of the Less than d 100 & Daily number

year one-half 1 2 314 5 | 6} 7 [| 8 | 9 | 10/11-1516-20]2-30B81-404.1-5051-99| over|Totallof trips (000)
mile

Spring y 2/ J

(April) 8.2 16.4=' |13.0] 9.5 }6.4—° (8.8]3.6/2.4/3.5/1.3/5.3] 8.8/4.6 ¢4.1 ]1.7]0.8]0.9] 0.7 |100.0] 254,445

ummer iT 2/
(July-August) 8.4 142° 113.1) 9.7/6.3— |8.8/4.3/3.0]3.311.3|5.5| 8.4]4.5 }4.1 | 1.7]0.9]1.3] 1.2 |100.0] 236,971

Fall

(October) 8.7 15.22/ 14,9/10.0 6.62! 7.813.7/3.8/3.5]1.0/5.9} 7.4] 3.7 13.6 11.5 ]0.9]1.1 | 0.7 |100.0) 237,936
Winter i 2/

(January) 8.8 17,6= 113.0/10.6 ]6.3—' |7.5(3.8/2.8/3.4/1.0]5.4] 7.7] 4.4 [4.0 | 1.3 | 0.8/0.9] 0.7 [100.0] 222,596

1/ Indicates the statistical mode of trip lengths or the most likely length of trip taken.

2/ Indicates the median trip length or where 50% of the trips are longer and 50% are shorter.

Oo

SOURCE: Based upon unpublished table T-5 from the Nationwide Personal Transportation Survey
conducted by the Bureau of the Census for the Federal Highway Administration, 1969-1970.

REF. 1


54

TABLE 4.10

Effect of Barometric Pressure and Humidity on Exhaust Emissions of a Vehicle

Percent Change
Source HC co NOx co2
One In Hg Increase in
Barometric Pressure
GM Environmental -10 -30 +5 +2.2
Chamber Data
Ford Data Based on -13.6 -21 +12.5 +7.7
Multiple Regression
Analysis of Three
Vehicles
50 Grains Increase in
Absolute Humidity
GM Environmental +10 +25 eo -1.5

Chamber Data

REF. 23, 29


24
22)
20)
18
16)
14
12

ROLL TEST—EPA HIGHWAY, CARBON BALANCE (mpg)

123

g

Best Linear 7
Data Fit

7
Oo,
y

%

7

Line of Equality

[| {| | | | |] | | { | | | J

oO nN FS OD @W

|
2

1
4

6 8 10 12 14 16 18 20 22 24 26 28
ROAD TEST-EPA HIGHWAY (mpg)

FIGURE 5,8 Fuel Economy for EPA Highway Cycle as Measured on Both a
Track and a Dynamometer

REF. 26


107

per gallon of gasoline is known, the measurement of the vehicle emis-
sions during the course of the test can be employed in conjunction with
the distance traveled to compute a fuel economy based on the concept
that carbon mass is conserved. The major assumptions required when
using this technique include:

1. The carbon contained in the HC, CO and CO, in the exhaust is
the only carbon in the exhaust, This meafis that other carbon-
containing compounds, such as oxygenated hydrocarbons that are
not detected by a Flame Ionization Detector (FID) and carbo-
naceous particulates, are ignored.

2. All of the carbon that is measured in the exhaust in the form
of HC, CO and CO, came from the fuel; there are no other
sources of carbon.

3. All the fuel consumed during the test can be accounted for by
the carbon in the exhaust. This means that all of the fuel
that leaves the tank during the test is assumed to pass
through the engine and that no carbon leaks out of the exhaust
system before being analyzed or evaporates from the vehicle.

Both of these test methods for fuel economy measurements have
advantages and disadvantages and are subject to significant errors if
careful experimental techniques and procedures are not followed. How-
ever, under conditions where both techniques can be simultaneously
employed, either method can be used to obtain accurate measurements of
fuel economy. An.early study designed to examine the correlation
between measured fuel economies based on, the Carbon Mass Balance and
weighing techniques was reported in Reference 2, In this study, eight
CVS-C tests were conducted at the EPA Motor Vehicle Emission Laboratory
in Ann Arbor, Michigan, on three different vehicles. The average dif-
ference in fuel economy (calculated fuel economy minus weighted fuel
economy, divided by weighted fuel economy) was found to be 4,5% with
the calculated fuel economy being higher than the weighed fuel economy,
The individual differences ranged from 2,6% to 8.1%. Another investi-
gation was performed using data from the work reported in Reference 2.
The same calculation was performed on 245 sets of data for which there


109

follow the given velocity versus time cycle. The second technique that
has been proposed is to simulate the actual loading of the vehicle dur-
ing the course of the driving cycle with the aid of a chassis dynamome-
ter, It should be noted that there is no inherent technical reason for
eliminating the use of chassis dynamometers from fuel economy testing
if it can be shown that they accurately represent the actual inertial,
aerodynamic rolling resistance and accessory loads experienced by ‘the
vehicle as it traverses the driving cycle. Both the road or track and
dynamometer procedures have inherent advantages and disadvantages as
outlined below.

The advantages of a road or track test procedure include:

1, The total load, including inertia loads, road loads and the

effects of accessory loading are accurately simulated.

2. Fuel economy tests may be carried out anywhere a suitable
level stretch of pavement can be found.

3. Assuming that an appropriate road or track is available, rela-
tively low expenditure for capital is required.

Disadvantages of road and track ‘testing include:
1. Testing cannot be carried out under adverse weather conditions.

2. Correlation parameters, designed to take into account the
effects of ambient variables on fuel economy measurements,
must be developed and applied to the base data in order to
obtain fuel economy measurements at standard conditions.

3. Some difficulties are encountered with reproducibility of
vehicle speed versus time-especially when complex cycles, such
as the UDDS or proposed EPA highway cycle, are employed.

4, There is a lack of a satisfactory evaluation of the effect of
cold start on fuel economy.

5. Fuel economy and exhaust emissions cannot be simultaneously
measured.


3.1
3.2

3.3

4.la

4.1

4.2

4.3

4.4

4.5

4.6

4.8

4.9

4.10

4.11

‘TABLES

Percentage of Vehicle Trips by Lengths and Season of Year........+-
Comparison of Urban Driving Patterns and Driving Cycles.........00.

Comparison of Current and Proposed Fuel Economy Driving
Cycles. ccccccccacccccucccccces

Table of Ratio of True Adjusted Mean Emission to Standard
in Percent, x/Ah, as a Function of 3/% in Percent and
Probability En PErcent..cecesscccceccteseccccceecseteessccesevsees

Factors Affecting Exhaust Emissions Variability of a Given
Vehicle at Various Levels..cesecccccccecccnsvcccscersccceecevessees

Summary of Emission Results for 30 Tests on a 1971 Ford
Ranch Wagon in a Single Test Cell....cecccececeee

Summary of Emission Results for 16 Tests on a Chevrolet
Impala Equipped with an Oxidizing Catalyst in a Single
Test Cell.sseccossceves

Ome cc cer cer ercerccceccccreseessesecsces

Summary of Emissions Test Variability for Three Experimental
Vehicles with 1975 Control Systems in a Single Test Cell........00.

Summary of Emission Test Variability for Stratified Charge

CVCC Vehicles. .cccceccccccccvcccenccccevscnceccsssscsessescseeseese

Summary of Emission Test Variability for a 1973 Model Year
Production Vehicle in Various Test Cells at a Single

LaDOLatOrysreccecccerccscvccccescccscscesesseasesessseseseenssssess

Summary of Emission Test Variability for a Catalyst Equipped
Vehicle at Two Laboratories... .csscscecesccsovecscscccsscrscenseces

Summary of Emission Test Data for CVS-CH Tests on the
"Riverside" Catalyst Equipped Fleet....ccccceeseees

ee ecececeeces

Summary of General Motors Exhaust Emission Audit Tests in
California for the Period 1/1/74 thru 3/31/74. ...ccvccccerceveccecs

Effect of Barometric Pressure and Humidity on Exhaust
Emissions of a Vehicle..cscescecccccccsccccsccncccscscccncsssccsees

Average Emissions for Six 1973 Vehicles as a Function of
Cold Soak Temperature... ccccoscecccccccccccccvccenccssorecvesssecere

vi

10
15

20

30

32

34

36

37

38

39

41

45

46

54

56


86

contributor to both the total mass of HC and CO emissions collected
during the test and the overall variability of HC and CO exhaust-
emission measurements. This is not the case with No, where approximately
equal masses of No. are collected during the three phases of the test.

Variations in exhaust-emission measurements specified in terms of
the standard deviation as a percent of the mean for:a 1975-76 vehicle
in a given cell or from cell to cell at one laboratory can be expected
to range between 10% to 25%, 15% to 30% and 5% to 15% for HC, CO and
No, respectively. Limited data indicate that the statistical
variability of exhaust-emission tests on CVCC stratified-charge type
vehicles may be lower than that mentioned above. In addition,
systematic errors from laboratory to laboratory of as much as 20% to 30%
of mean emission values have also been reported in certain cases. In
general, exhaust-emission variability tends to increase as exhaust-
emission standards are reduced below 1975-76 levels. Based on these
considerations, it is apparent that significant consequences should not
be attached to a single CVS-CH exhaust-emission test.

It is concluded that exhaust-emission variability from test to test
and laboratory to laboratory can be reduced if the following two
programs are developed and implemented:

(1) Establishment of mandatory correlation test programs among
governmental, automotive manufacturers’ and other test
laboratories that are carrying out exhaust-emission measure-
ments on the CVS-CH test. These correlation programs should
include CVS-CH tests of relatively stable vehicles and tests
of the CVS sampling and gas analysis systems using either
exhaust gas generators or premixed gas cylinders as the gas
source,

(2) Establishment of close tolerances on ambient test-cell
temperature and humidity for the CVS-CH test method and the

development of correction factors relating barometric pressure
and exhaust emissions.


31

such that Pi (1) is 95% if the standard deviation as percent
of the true mean, (6,/%,), is 50%. Inspection of Table 4.la
indicates that the required value of (x,/A,) is 54.9%.
ii. Determine Pi (2) if the standard deviation divided by the mean,
(6,/%,), is 30% and (x,/A,) is 89.6%. In this case P,(2) is
equal to 87.8%.
Numerical examples associated with P* (2,3,1) and P* (2,3,4) can be
obtained from Table 4.la in a similar manner. However, due to the
previously outlined assumptions required to calculate these values,
these quantities are only rough approximations at best. More accurate
predictions of P(2,3,1) and P(2,3,4) can be obtained for a specific
case, assuming independent emissions, by combining the values of P,Q),
(8,/*,) and Gy /A,) for each pollutant with the equations for P(2,3,1)
or P(2,3,4) listed in Table 4.la.

4.3 Statistical Variability of Exhaust-Emission Measurements

Exhaust-emission measurements at 1975-76 levels tend to have poor
reproducibility. Both systematic and random errors associated with
vehicle variability, emissions collection and measurement variability
and environmental variables contribute to the poor test reproducibility.
In addition to these variations associated with a given vehicle, varia-
tions in emissions from a group of similar production vehicles are
encountered, 23

As shown in Table 4.1, there are basically three levels of vari-
ability associated with the measured exhaust emissions for a given
vehicle. These are the variability associated with a given test cell,
cell-to-cell variability within a given laboratory site and the basic
laboratory-to-laboratory variability. The most important factors
affecting exhaust-emissions variability at each of these three levels
are also listed in Table 4.1. Since vehicle variability is an impor-
tant factor at all levels, various programs have been carried out that


A/Poccseaee
AMA... eeeee
AMC... sees
ASTA.....44
AToccseeeee
CCS. .eeeeee

CID. ....ee
CMVE.... eee
CNG... eee ee
CReseceseee
CVCC.......

CVS-CH.....

Cyl......ee
DF. wseeeees
Dual Cat...
EFL.....00-
EGR. «sees
EPA. .seeeee
1 eee
FIP...
GM. cease
g/mi.....
GT. sees
HC.
HCAT... 2005
ICE......

IFC...

GLOSSARY

air/fuel

Automobile Manufacturers Association
American Motors Corporation

Automotive Service Industry Association‘
automatic transmission

direct-fuel-injected, stratified-charge engine such as
the Ford PROCO or Texaco ‘TCCS

cubic inch displacement

Committee on Motor Vehicle Emissions
compressed natural gas

compression (or expansion) ratio

prechamber, dual-carburetor stratified-charge engine such
as the Honda Motor Company Compound Vortex-Controlled
Combustion Engine

constant volume sample emissions test procedure

constant volume sample--cold and hot start emissions test
procedure

cylinder

deterioration factor

a reducing catalyst followed by an oxidizing catalyst
electronic fuel injection

exhaust gas recirculation

U.S. Environmental Protection Agency

fuel injection

Federal Test Procedure

General Motors Corporation

grams/mile of emissions

gas turbine

various hydrocarbon compounds

oxidizing catalyst system for removal of HC and CO
internal combustion engine.

integrated fuel control (carburetor)

Jet Propulsion Laboratory, California Institute of
Technology

151


118

The test results presented in Section 5.4 indicate that fuel econ-
omy measurements employing chassis dynamometers for an urban driving
cycle (e.g., CVS-H, CVS-C and CVS-CH tests) are reasonably repeatable.
In fact, the data indicate that the variability of measured fuel economy
in terms of the standard deviation as a percent of the mean in a given
cell, from cell to cell at a given laboratory and from laboratory to
laboratory is in the range of 2% to 8%. The limited data obtained for
reproducibility studies on the EPA highway cycle have indicated a simi-
lar variability.

Questions relating to the ability of a chassis dynamometer to ade-
quately represent the inertia and road loads as a function of speed for
a given vehicle are also of importance, In addition, it would be desir-
able to have data relating to the importance of variations in loading on
fuel economy measurements, It is generally agreed that dynamometers
with twin small-diameter rolls, such as the Clayton-type units presently
utilized by EPA, do not provide the same tire-roll loading effects as
those found on the road. It is possible to minimize inaccuracies in
dynamometer loading if the load on the dynamometer is set so that vehi-
cle coast-down time on the rolls matches vehicle coast-down times
obtained on the road, In addition, the Clayton-type units are generally
limited in load adjustment and inertia-weight increments. The Federal
Register presently specifies 250 1b inertia-weight increments for low
inertia-weight vehicles in the range 1,500 to 2,750 lb and 500 1b
inertia-weight increments in the range 3,000 to 5,000 1b. The effect
that this test procedure has on dyno versus expected road fuel economy
has been discussed in Section 5.3.

Large-roll electric dynamometers provide independent adjustment of
simulation for aerodynamic drag and rolling resistance plus excellent
vehicle mass simulation. However, these dynamometers are significantly

more expensive than small-roll units.


FUEL ECONOMY (mpg)

40)

wo
oS

n
S

Ss

93

40 mph
Road
Load
Road
70 mph Load
40 mph 22.3 Road
Warm a2 soenh
! . mpl
Cold 74 70 mph die? 17.2
Worm ns 70 mph fd 12.7
Cold J10.0 ‘
Urban ° Warm fF
cod &
Urban
Urban
SUBCOMPACT INTERMEDIATE LUXURY SEDAN
4-CYL ENGINE V-8 ENGINE V-8 ENGINE

MANUAL TRANSMISSION
Approx. 2,100 Ib

AUTOMATIC TRANSMISSION
Approx. 3,500 Ib

AUTOMATIC TRANSMISSION
Approx. 5,200 Ib

FIGURE 5.2 Fuel Economy Ranges (Urban Cycle to Road Load) for Three
Vehicles on Different Driving Cycles

REF, 46


34

TABLE 4.2

Summary of Emissions Results for 30 Tests on a
1971 Ford Ranch Wagon in a Single Test Cell

Standard
Mean Deviation Standard Deviation

Variable g/mi g/mi As % of Mean
Bag 1 (cold transient)

HC 4.74 1.44 30.46
co 35.92 6.62 18.43
co2 813.33 18.92 2.33
NOx 5.72 0.49 8.65
Bag 2 (stabilized)

HC 1.50 0.15 10.25
co 10.24 1.46 14.28
co2 915.43 24.00 2.62
NOx 3.87 0.26 6.86
Bag 3 (hot transient)

HC 2.51 0.13 5.18
co 14.64 1.91 13.02
co2 718.01 18.62 2.59
NOx 5.56 0.41 7.43
Composite (CVS-CH)

HC 2.46 0.35 14.22
co 16.73 1.90 11.34
C02 840.55 17.30 2.06
NOx 4.71 0.31 6.48

Summary of Environmental Conditions

Standard Standard Deviation
Condition Mean Deviation As %_ of Mean
Barometric
Pressure, in. Hg. 29.32 0.32 1.08
Temperature, °F 74.73 2.05 2.74
Relative
Humidity, % 39.93 13.62 34.11

REF. 22