PROCEEDINGS OF THE
EPA/INDUSTRY
QUALITY CONTROL SYMPOSIUM
LABORATORY CORRELATION AND
PAIRED DATA ANALYSIS PROGRAMS
SEPTEMBER 7, 1977
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PROCEEDINGS OF THE
epa/industry
QUALITY CONTROL SYMPOSIUM
LABORATORY CORRELATION AND
PAIRED DATA ANALYSIS PROGRAMS
SEPTEMBER 7, 1977
HELD AT:
ENVIRONMENTAL PROTECTION AGENCY
2565 PLYMOUTH ROAD
ANN ARBOR, MICHIGAN
48105
SYMPOSIUM CHAIRMAN t
BRUCE R. GARDNER
EMISSION TEST LABORATORY
FORD MOTOR COMPANY
21500 OAKWOOD BLVD.
DEARBORN, MI 1+8121
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SUMMARY REPORT
EPA/INDUSTRY QUALITY CONTROL SYMPOSIUM
LABORATORY CORRELATION AND
PAIRED DATA ANALYSIS PROGRAMS
I. Introduction
This report is a narrative synopsis of the proceedings, discussion and
presentations made at the Quality Control Symposium at the Environmental
Protection Agency (EPA) Laboratory, Ann Arbor, Michigan on September 7>
1977. The symposium was a joint effort by the EPA and the automotive
industry to discuss emission testing laboratory correlation and analysis
of test results from paired testing in independent laboratories. Approx-
imately forty representatives from industry and government attended the
proceedings.
The proceedings generally followed the agenda in the appendix with infor-
mal presentations and discussions for each major topic. Questions may be
directed to the Chairman or identified participants.
SYNOPSIS OF SYMPOSIUM
II. EPA/Manufacturers Paired Data Analysis Techniques
A. Frank Johnson of Chrysler gave a review of the Motor Vehicle Manu-
facturers of America (MVMA) program for analysis of the paired data
of the various manufacturers with EPA. The data from paired testing
of Certification vehicles is reduced by each manufacturer to paired
percent differences and exchanged among the participants on the MVMA
Exhaust Emission Measurement Panel (EEMP).
Basically, the data are combined into a single data base by Chrysler
and various reports are generated by them as a service to MVMA. The
nature of the reports and analyses is specified by the EEMP. The
major report is presented monthly and consists of plotting the percent
differences of each manufacturer on a ten (10) day moving average
basis. On these plots, EPA is also represented by being plotted as
the reversed sign average of all manufacturers' paired test results.
The sign reversal enables the plots to reveal a trend in correlation
with EPA which is consistent for all manufacturers. The EEMP had
agreed that any paired test with a single constituent paired dif-
ference in excess of 1 kQfjo was atypical and not considered in the
analysis. Furthermore, for plotting purposes, all running averages
greater than 20$ are plotted as 20$.
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In the ensuing discussions several limitations were explored:
1. The ten day running average does not take into account the
fact that no tests are recorded on a particular day. This
could bias results when testing is infrequent. However, the
concept of a ten (10) test moving average was riot suitable
given the requirement for synchronization of manufacturers
data to maintain plotting consistency.
2. The percent difference representation would have a tendancy
toward skewness as the actual levels of the constituent were
reduced in comparison to the variability of the constituent.
The resultant skewness would tend to invalidate statistical
treatments based on "normal" distributions. This is par-
ticularly evident with carbon monoxide results.
3* High variability makes the plots difficult to analyze by
observation.
The consensus was that a difference presented as a % of
applicable standard would be useful.
Another report generated from the MVMA data base was a basic sum-
marization of statistics by quarter for each manufacturer.
Finally, it was stated that the program was being reviewed by the
EEMP to see if it would be possible to improve the usefulness of
the reports.
As an alternative, Mr. Johnson displayed regression plots of
Chrysler data. However, it was suggested that it might be inap-
propriate for the MVMA members to exchange actual test data of
current Certification programs and this would be required to gen-
erate such plots.
B. Dave Buist discussed the approach to correlation taken by his Lab-
oratory Correlation Group at General Motors. The most important
reason for analysis of correlation is to keep track of trends and
to be able to understand large differences and/or emission failures.
To monitor correlation between the GM Vehicle Emissions Laboratory
(VEL) and EPA they publish a variety of reports at various frequencies:
Daily:
Continuous plots of individual tests percent differences
including date and vehicle number. These plots are left
to individual interpretation. However, it was implicit
in these reports that any difference on a specific vehicle
could be judged unacceptable.
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Tbe ten (10) test running average was overlayed on
the individual difference charts as a solid line.
Weekly:
In addition to the individual difference charts a test
summary sheet of individual vehicle paired data i3
published. These sheets give individual bag data
comparisons.
A four page data summary is generated.
Summary plots of the monthly averages were published.
Additionally, various reviews were made of the data to
determine if observed differences could be related to
barometer, humidity, distance travelled, emission
level, etc.
A four page summary for the month and year-to-date.
During the questions and answer discussion, Mr. Buist stated that
they considered correlation to be suspect when a test result at
their lab differed relative to EPA by more than the following
limits:
If the results are outside these limits(with greater than 1 gram
difference) they request a retest of the vehicle in their lab for
confirmation upon return from EPA.
He felt that no general effect could be assigned for barometer and
humidity differences because the variation of individual vehicle
responses to these factors was too great.
If a correlation problem is suspected, they will run a test program
to isolate the casual conditions. Mr. Buist stated that they have
found differences in conditions, equipment and procedures between
two laboratories can cause differences in emission results even
though both laboratories are in compliance with the specifications
set; forth in the Federal Register. In analyzing the correlation
problem of a particular vehicle, one would want to verify that any
barometric pressure difference showed up as an effect by causing
Monthly:
Hydrocarbons:
Carbon Monoxide:
Oxides of Nitrogen:
Carbon Dioxide:
Evaporative (SHED):
± 1556
± 20g
t 15*
± %
t 1556
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-In-
differences in all bags. If not, then it was more likely that
some other cause was more significant. If equipment differences
are suspected, it should be possible to run a hot start test
program for verification. However, if the problem is a cold
start problem which may be related to variables such as soak time
and temperature, then a cold start test program is required.
In terms of continuing correlation programs, GM uses both Hot
Start vehicles and Gold Start vehicles. The Hot Start vehicles
are modified to remove sensitivity and variability of operation.
The variability of these vehicles is approximately 6% for HC,
6% for CO, h% for NOx and 2% for fuel economy. However, even
these vehicles have a tendency to drift in emission levels "over a
long time period. Therefore, only data from approximately two
weeks of testing can be compared at any one time. The Cold Start
vehicles are being used in California in a correlation program
with the CARB laboratory using the Quality Audit testing procedure.
Mr. Buist also expressed GM's desire for an active EPA/Industry
Correlation program.
C. Doug Berg of the EPA Quality Control Development Staff presented
information concerning EPA use of paired data. He stated that
EPA pairs valid Certification tests for comparison in three (3)
ways: 1) Manufacturers to EPA, 2) Repeat tests at EPA,
3) Repeat tests at the manufacturer's lab. While the data avail-
able from the EPA tests includes all pertinent information such
as ambient conditions, emission results by bag and final weighted
values and test site identification, the data received for the
manufacturer's test does not contain the bag results.
To determine whether or not the results of test pairing was unusual
enough to be called an outlier, the Quality Control Staff has
several criteria: 1) Engineering judgement, 2) Distribution
effects which may vary significantly from normality, 3) Limits
established as three standard deviations, and k) Trend analysis
using Quality Control charting techniques.
In their summary statistics, QCDS tries to avoid elaborate analyses
in order to improve understandability. Another factor is the avail-
ability of various standard statistical analysis computer packages
on the Michigan Timesharing System (MTS) where their data bases
reside. As a result, their summary statistics basically take the
form of tabulations of means, standard deviations, minimum and
maximum, graphical analyses, and parametric and non-parametric
analyses.
For analysis of trends, they use weekly and monthly summaries,
seasonal comparisons, time series analyses using moving average
and auto correlation, and cumulative sum (CUSUM) plots in batch
applications.
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Mr. Berg also discussed various measures with which to evaluate
the significance of observed paired differences. Various percent
difference and actual difference assessments can be compared to
the EPA result, the standard, or a more subjective measure might
be derived which assesses the impact of the differences on the
Certification efforts of the manufacturer.
Finally, Mr. Berg briefly discussed the action taken by the Quality
Control area when they suspect a correlation problem based on
their analyses. First, they contact the Laboratory Branch to do
in-house checks before making a decision on the problem. If
further investigation is deemed to be warranted, they will contact
the Certification team of the specific manufacturer(s) involved
and give them the QC investigation results. If the Certification
team feels it is necessary to pursue the problem, they will
contact the manufacturer(s).
Bruce Gardner of Ford Motor Company gave the final presentation
on this subject. Due to limited time, only a brief discussion
period was possible.
Mr. Gardner showed the deviation from normality of a population of
CO paired percent differences. He noted that several of the other
speakers had expressed concern for the validity of assumption of
normality for populations with high variability compared to mean
level (coefficient of variance). Both HC and CO significantly
deviate from normality.
Since trend analyses based on Quality Control techniques are typically
based on assumptions of the underlying normality of the population
being charted, control charting o£ non-normal distributions can
result in false conclusions. To overcome this problem, Ford uses
a transformation technique to convert the non-normal distributions
into normal distributions for charting purposes. The technique
involves the use of three parameter Weibull distributions fitted to
observed data. Once the distribution is described by the Weibull
fit, the cumulative probabilities which correspond to the one, two
and three standard deviation points on a normal distribution are used
to establish the control chart limits on the non-normal distribution.
Thus the control chart limits are actually defined as cumulative
distribution probabilities. This means that the plus (+) 3-Sigma
value instead of being the mean plus 3 standard deviations is defined
as the cumulative probability of 99•!%• Similarly, the mean for
the normal is also the median of 50$ cumulative probability. But
for the Weibull, the mean and the median do not have the same
cumulative probabilities if the population is non-normal. The
Weibull transformation converts a given percent difference on a
paired test comparison into a cumulative probability value. When
these probability values are charted they can be analyzed using
standard control chart analysis techniques.
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A second innovation to the charts is to rescale the various standard
deviation lines so that those test points which fall within t. one
(1) standard deviation (15-87% to 8U.13% cumulative probability) are
plotted closer to the median line than a linear scale of all points
from 0 to 100% cumulative probability would indicate. Similarly,
the points falling in the I one (1) to two (2) standard deviations
areas are plotted on a wider scale than the 1 one (1) standard
deviation values, and so on for those points outside + two (2)
standard deviations. This rescaling provides the emphasis on most
deviant points by increasing their distance from the median point
in increasing proportion to their deviancy and thus improves visual
impact. A sample of this process is illustrated in the Appendix.
III. Intra-Company Laboratory Correlation
Mr. Gardner described the program which is being planned to provide
correlation among the various end-of-line and Certification facil-
ities within Ford. Basically, the program will be a fleet of twenty
(20) vehicles which will represent a wide range of emission systems
and engine families. These vehicles will rotate in groups of five
(5) vehicles among the various Company facilities and be cold start
tested. The goal is to obtain forty (^0) cold start tests a month
in each of four (U) facilities. The data from these tests will be
analyzed and will provide assurance that correlation remains stable
among those labs. Test-to-test repeatability on cold start testing,
defined as coefficient of variance, has been observed to be 10% for HC,
20% for CO, 1% for NOx and 1% for fuel economy for typical stabilized
cold start vehicles. The vehicles would be replaced periodically to
reflect new emission systems and product line.
Mr. Buist reviewed the current GM program for lab-to-lab correlation.
It consists of two loops, one in the midwest and the other in the
west, in which instrumented vehicles are rotated. Two vehicles are
rotated in both loops and are cold start tested at each laboratory.
In addition the vehicles are tested in the CAHB laboratory in both
loops. The current timing is about thirteen (13) weeks to complete
the midwest loop and nine (9) weeks to complete the western loop.
IV. Correlation Programs with EPA per Advisory Circular #52
A. General Correlation Programs
Dick Lawrence of EPA discussed the various aspects of the AC #52 and
EPA's interpretations of the circular. He is responsible for all
general correlation programs in which EPA is involved.
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For General Correlation Programs, the requirements in the AC #52
should be followed. Mr. Lawrence stated that early contact with
him during the planning stages of a general correlation program
is recommended since he will be responsible for evaluating the
effectiveness of the program and recommending EPA participation.
It is also preferable that data from the programs be supplied to
EPA on punched IBM cards for easier input to computer data bases.
In addition, EPA prefers to be the last facility in the program.
At the present time EPA prefers to have general correlation programs
on new procedures as opposed to established procedures. Consequently,
they had established priorities as follows: 1-SHED, 2-Heavy Duty
Engines, 3-Motorcycles. They also prefer to have multiple manu-
facturers and certification laboratories rather "than development-
only laboratories.
For analysis of the data, the EPA intent would be to provide
primarily the data and summary statistics and leave interpretation
to the individual participants. This would facilitate swift reports
of results for feedback to the participants.
Mr. Lawrence next discussed the issue of ambient condition differences
being a correlation problem. He said that correlation problems
caused by vehicle sensitivity to ambient conditions are the respon-
sibility of the manufacturer and that vehicles should meet emission
requirements over a wide range of environmental conditions. He
cited a recent MVMA. proposal which would call for much tighter
test conditions than are presently allowed by the Federal Register.
He then showed a chart taken from an EPA memorandum presented at an
EPA/Manufacturers Meeting which compared the various ranges of
environmental conditions observed in the Los Angeles area, allowed
by the FTP and proposed by MVMA. The figure on the next page re-
produces the general relationships.
Dave Buist pointed out that the necessity for meeting emission
requirements at all conditions should not be a factor in the
establishment of emission system deterioration through the 50»000
mile durability test procedure. For the 50K vehicles, those
factors unrelated to emission system deterioration should be
eliminated to the greatest extent possible in order to provide
better confidence in the established deterioration factor. This
would include the random influence of fluctuating environmental
conditions.
Mr. Lawrence also described the operation of the correlation activity
at EPA. They are given correlation test slots which they must
utilize the best they can. The correlation vehicles have lower
priority than Certification testing. In response to a question
about allowing a manufacturer to substitute a correlation vehicle
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RANGE OF ENVIRONMENTAL CONDITIONS
Temperature
for one of the manufacturers certification slots, Dick said that
the slots are assigned to Certification testing rather than to
a particular manufacturer. If a manufacturer did not utilize a
slot for certification vehicle, there was always the potential
to assign that certification vehicle slot to another manufacturer.
To run one manufacturer's correlation vehicle while other manu-
facturers were unable to test certification vehicles would be
unacceptable to EPA.
Heinrich Schlumbohm of Volkswagon presented the VW correlation
program concept and operation. The program is split into separate
loops, one in California and the other in the Midwest. A cor-
relation program is conducted twice a year in both loops. To
eliminate as many variables as possible the program consists of
six (6) Hot Start tests in one laboratory in one day. Only one
mechanic/driver is utilized for all testing. The program only
seeks differences in test equipment which might effect emissions.
However, Mr. Schlumbohm stated that they have observed environmental
effects on test results, especially barometric .pressure. It was
suggested that some indication of the vehicles' sensitivities to
environmental conditions would aid in the evaluation of the test
results.
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Several questions were directed to Mr. Lawrence at this point
about other types of general correlation programs. In response
to a question about programs with non-certification laboratories
from automotive suppliers, he said that EPA would consider each
request on its own merit. Only one vendor had requested such a
program, to date. On application to Heavy Duty testing,
Mr. Lawrence responded that the same considerations as Light
Duty would apply. On a request to have correlation opened up
to the entire year instead of just the present October through
May, it was stated that the interference with certification
testing could not be justified. In response to any inquiry
about Diesel testing, Dick said EPA would be receptive to such
a program.
B. Specific Correlation Programs
Mr. Lawrence continued with the second topic under this Agenda
item, Specific Correlation Programs. These programs were defined
as being conducted with or being related to certification vehicles.
However, some specific correlation programs might be originated
because of the results of a general correlation program.
As to procedures, Mr. Lawrence said that all requests for specific
correlation programs were to be directed to the Certification
Division, usually the particular manufacturers own Certification
Team at EPA - It is up to the Certification Division to decide
when there is a correlation program unless the Certification
Division says there is a specific correlation problem. After the
existence of a correlation problem is established the Emission
Control Technology Division (ECTD), which is responsible for
correlation, will work with the manufacturer, Certification
Division and the Laboratory Branch to design and conduct a
specific correlation program.
For pre-program investigation, EPA will look for the obvious factors
which can be investigated through their current Quality Control
procedures.
In the discussion, it was suggested that an ongoing correlation
program which provided information during the certification testing
season, May to October, would reduce the uncertainty associated
with the correlation between labs and eliminate the need for special
correlation programs, in many cases. Another suggestion requested
that the timing for specific correlation requests be shortened. As
it;is now, by the time a manufacturer goes through the paperwork,
the vehicles are in production. A request for the individual
manufacturers to be allowed to access the EPA analysis programs on
the MTS was held to have doubtful chances by Mr. Lawrence because
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he believes the information doesn't fall under the Freedom of
Information Act. This could be further pursued by contacting
the Cljlef of the Data Branch.
V. Summary Discussion
In the final discussion, it was suggested by Doug Berg of EPA
that a follow up workshop should be set up to set up Standard
Test Programs for specific correlation problems. The program
would set up guidelines for what data must be evaluated prior
to the initiation of a test program. The test programs might
be structured according to the specific problem. An overall
outline of the investigation procedure could be laid out. Dick
Lawrence felt that any program structure would need to maintain
flexibility as the specific problems could be specific to a
manufacturer's emission system's sensitivity and the manufacturer
would be in the best position to suggest the investigation.
The Chairman concluded the symposium discussion by remarking that
the task of correlation was not a science and that it required
considerable engineering judgement and knowledge of emission
systems to draw reasonable conclusions from analysis of correlation
data. Statistics, as used in correlation, are just a tool to
help measure the validity of the data available for analysis.
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APPENDICES
Agenda
Attendance
Chrysler Presentation
General Motors Presentation
EPA Presentation
Ford Presentation
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AGENDA
EPA/INDUSTRY QUALITY CONTROL SYMPOSIUM
LABORATORY CORRELATION AND PAIRED
DATA ANALYSIS PROGRAMS
September 7, 1977
9:00 a.m. - 4:00 p.m.
I Introduction
II EPA/Manufacturers Paired Data Analysis Techniques
Basic Assumptions
Outlier Identification
Summary Statistics
Trend Analysis
LUNCH 11:00 a.m. - 1:00 p.m.
Ill Intra Company Laboratory Correlation
Test Program Structure
Analysis Techniques
CARB Laboratory Cross Check Proposal
IV Correlation Programs with EPA per Advisory Circular #52
A. General Correlation Programs
MVMA Programs
Volkswagon Program
JAMA Program
B-. Specific Correlation Programs
Appropriateness of Advisory Circular Provisions
.1 Prior Preparation-Verification of Problem
t
General Plan of Attack
•I Standard Test Program Designs for Specific Problems
V Summary Discussion
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ATTENDEES
R. H. Gower
Chrysler Corporation
12500 Lynn Townsend Drive
Highland Park, MI
956-4959
Lary Koch
Chrysler Corporation
Jos Campau
Hamtramck, MI
876-8066
G. F. McCaskey
Chrysler Corporation
12500 Lynn Townsend Drive
¦Highland Park, MI
956-4959
F. E. Johnson
-Chrysler Corporation
12800 Lynn Townsend Drive
Highland Park, MI
956-3135
:R. Fleming
ERDA
P. 0. Box 1398
Bartlesville, OK 74003
(918) 336-2400
N. E. March
Chrysler Corporation
P. 0. Box 1118
Detroit, MI 48288
956-4892
A. C. Bodeau
-Ford Motor - AADGO
17000 Oakwood Blvd.
Allen Park, MI 48124
323-3221
R. E. Rice
Chrysler Proving Grounds
Chelsea Proving Grounds
Chelsea, MI
475-8651 ext. 381
P. Colandrea
Ford Motor Company
Dearborn Emission; Lab
Dearborn, MI 48121
323-3727
J. L. Tichy
Chrysler Corporation
12800 Lynn Townsend Drive
Highland Park, MI"- 48207
956-2419
A. A. Farjo
Ford Motor Company
Emissions Testing Department
Dearborn, MI 48121
322-5229
G. L. Green - 50235
Cumming Engine Company
1900 McKinley Avenue
Columbus, Ind '47201
(812) 379-6910
T. Tupaj
EPA
668-4427
J. P. Marshall
EPA
668-4424
J. P. Cheng
EPA
668-431(8
P. T. Polonkey
Detroit Diesel Allison Division
13400 W. Outer Drive L-4
Detroit, MI 48228
592-5661
J. P. Steiger
Ford Motor Company
21500 Oakwood Blvd Room G028
Dearborn, MI 48121
323-0434
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ATTENDEES
P. J. Arquin
U.S.T.R. Corporation
33 Garland Way
Lyndhurst, N.J. 07071
(201) 438-1113
D. R. Wamboldt
American Motors Corporation
5626 25th Avenue
Kenosha, Wise. 53140
(in4) 658-6332
D. A. Reis
Jeep Corporation (AMC)
940 N. Cove Blvd.
Toledo, OH
(in 9) 14.70-7^53
M. Shiobara
Nissan Motor Company LTD
560 Sylvan Avenue
Englewood Cliffs, N.J. 07632
(201) 871-3555
C. R. Case
EPA
MSED (EN-3^0)
401 M Street S.W.
Washington, D.C.
(202) 755-257^
F. Parks
EG&G Automotive Research Inc.
5*4-04 Bandera Road
San Antonio, TX 78238
(512) 684-2310
E. F. Arndt
EPA
MSED (EN 340)
401 M Street, S. W.
Washington, D.C. 20022
(202) 755-2574
B. J. Hillyer
Mobil R&D Corporation
Paulsboro Laboratory
Paulsboro, N.J. 08066
(609) 423-1040
R. G. Leiendecker
American Motors Corporation
14250 Plymouth Road
Detroit, MI 43232
493-2462
J. Baty
Airco Ind. Gases
1715 E. Michigan Avenue
Albion, MI 49224
(517) 629-9161
G. Gruska
General Motors - Envir. Act. Staff
GM Technical Center
Warren' MI 48090
575-1409
A. Papay
Mercedes-Benz
One Mercedes Drive
Montvale, N.J. 07645
(201) 573-2642
H. Schlumbohm
Volkswagon
818 Sylvan Avenue
Englewood Cliffs, N.J. 07632
(201) 894-6522
F. R. Nader
American Motors Corporation
Emissions Laboratory
14250 Plymouth Road
Detroit, MI 48232
493-2959
B. R. Gardner
Ford Motor Company
21500 Oakvood Blvd. Room G028
Dearborn, MI 48121
(313) 322-5227
H. E. Jackson
NHTSA
400 7th Street S.W.
Washington, D.C.
(202) 755-9384
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ATTENDEES
R. J. Dennison, Standards Compliance Engineer
NHTSA, Office of Automotive Fuel Economy, NFE-20
Room 4102, 400 Seventh Street, S.W.
Washington, D.C. 20590
(202) 755-9384
R. Gilkey
EPA
Ann Arbor
D. Lawrence
EPA
313-668-4353/FTS 374-8353
D. Buist
General Motors Corporation
Milford, MI
685-5191
L. Erickson
General Motors Corporation
Milford, MI
685-5610
H. Marschner
Fiat USA - R.D.
Suite 1210
Parklane Towers West, Parklane Blvd.
Dearborn, MI 48126
336-3515
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MVMA PROCEDURE FOR PLOTTING OF PAIRED DATA PERCENTAGES
10 Day Running Average of Paired Data Percentages Man^_~ —A x 100
LPA
Where percentage difference was greater than 4035, the data was removed from
this set because it was considered an outlier.
When running average exceeds 20%, it is plotted as 20%,
Data called EPA is the 10-Day running average for all manufacturers with
sign of the data reversed.
2 3#
^ * §}
{? * 2
%
a
x
VI
0
3 i
I
o
Tl
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PA^e «2 of 12.
CHRYSLER-EPA PAIRED TESTS FOR l'97r8 VEHICLES
EPA
CHRY
% Dif. =
Chrysler-EPA
EPA x
ibo
.EPA
HC
¦CO
NOx
C0o
EVAP .
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TEST
CELL
CELL
2
DATE
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5
0.8
8.6
-6.7
2.3
-2.5
7-1
4
4
-3.0
3.5
5.7
3.9
-50.0
-3.7
-4.2
7-5
2
8
-0.3
14.5
-19.4
1.2
23.7
-1.8
4.6
7-5
4
4
-22.9
-17.9
-0.9
1.7
-10.9
-1.4
-0.5
7-5
3
4
-13.7
^18.8
-3.3
1.3
28.1
-1.1
-30.6
7-11
1-
2
14.1
22.3
-27.3
-0.7
0.3
1.3
7-11
I
3
5
-18.5
17.1
-5.9
4.8
16.4
-4.9
1.4
7-12
5
7
-30.1
-29.-5
10.3
2.4
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-21.2
7-12
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5
-25.5
—8.2
4.8
7.1
-13.5
-6.0
-3.9
7-13
2
5
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3.3
5.2
7-13
4
4
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-15.6
2.8
-2.6
0.8
7-13
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5
-12.3
-19.5
—3.2
1.7
-24.5
-0.9
3.6
7-14
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-14.1
2.8
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-4.3
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0.4
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-0.1
0.9
7-15
2
5
-37.0
-20.1
-9.6
-2.5
11.8
2.9
2.9
7-15
5
4
2.9
22.2
-14.8
11.8
-10.8
-1.7
7-15
3
8
4.2
-4.0
-3.2
3.0
-8.8
-2.7
0.4
7-18
3
4
-14.1
-16.5
-3.0
3.8
12.1
-3.4
3.4
7-18
6
8
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12 .6
-15.7
0.6
-16.9
-0.8
7-19
1
5
-6.3
-1.5
1.6
0.9
-0.8
7.0
7-22
1
5
19.3
30.9
-2.6
9.9
-9.8
7-25
1
5
-20.2
-23.9
-15.8
-4.1
4.3
6.7
7-26
1
2
-10.3
-1.2
-3.2
1.1
-1.0
3.1
7-27
5
4
84.1
39.5
-6.1
-2.6
-3.6
2.1
5.2
7-27
6
4
-9.2
-11.6
-13.5
-8.5
-20.4
9.4
1.8
7-29
5
5
11.3
-14.2
-6.8
1.0
-33.7
-0.8
-0.5
-------
2 Op IX
CALCULATION OF TEN DAY RUNNING AVERAGE
Carbon Monoxide 7-1-77 to 7-29-77
Sum of Data
Date
This D
7-1-77
12.1
7-2-77
0
7-3-77
0
7-4-77
0
7-5-77
-22.2
7-6-77
0
7-7-77
0
7-8-77
0
7-9-77
0
7-10-77
0
7-11-77
39.4
7-12-77
-77.2
7-13-77
-19.6
7-14-77
-15.0
7-15-77
- 1.9
7-16-77
0
7-17-77
0
7-18-77
- 3.9
7-19-77
- 1.5
7-20-77
0
7-21-77
0
7-22-77
30.9
7-23-77
0
7-24-77
0
7-25-77
-23.9
7-26-77
- 1.2
7-27-77
-11.6
7-28-77
0
7-29-77
-14.2
Number
of Points
2
Ten Day
Mean
Number
of Points
5
5
8
10
12
12
12
12
14
15
15
13
11
9
7
5
6
7
5
5
-------
CAR BOM rfONOX IDE
\
\ 3
\
\
\
\
A
f' t xy_
_j i
^—L
ir m i.: 'p n •. s >p it Vr 10
f [¦ i L Nu'MCER /
/
/
i
\ * -A /
e> \ /
U.
^ a> ^
\
\ ;
t
\ /
Chrysler
fit L UNIT = 1.0 DRYC. 0 RT t. [ NTE.'R VflL _ 7/1/77-7/31/77. fIRX OUT - 4,0X
-------
CARBON MONOXIDE
-------
CARBON DIOXIDE
o -
CM
O*
I.
CO -
1
a
i
N _
i
O
a.
.4-
X
CHRYSLER
FORD
&M
"EFfl
a> ^
r
o
es» —
5
jn
*
o
_T\
'k\ "NT
IT" IN ?V
~ '1 '0,
FF 4'
-------
1976 PAIRED DATA PERCENT* DIFFERENCES (75 FTP)
HC
CO
NOx
C02
Quarter
# Tests
Mean
Std. Dev.
Mean
Std. Dev.
Mean
Std. Dev.
Mean
Std. Dev.
1st
AMC
17
4.7
13.0
2.7
21 .4
7.2
13.1
3.7
6.3
2nd
38
5.9
12.6
-4.6
19.4
3.5
9.8
3.7
4.8
3rd
20
2.9
10.2
-0.8
15.5
9.9
7.6
2.0
5.5
4th
16
1.2
14.4
-7.5
20.3
6.6
17.2
2.3
8.4
1st
CHRYSLER 34
-5.9
16.8
-4.0
19.8
-4.8
9.1
-0.9
3.4
2nd
52
4.5
14.5
5.8
16.6
-2.9
7.9
2.5
3.5
3rd
12
-0.1
10.8
3.0
13.6
-2.7
9.4
-1.4
3.5
4th
30
0.5
10.2
1.1
19.3
0.4
9.3
0.6
1.4
1st
FORD
71
1.5
15.0
-10.7
16.6
3.4
11.4
1. 9
5.3
2nd
110
-1.9
17.2
-5.7
20.2
5.9
13.2
3.6
4.0
3rd
103
2.1
15.8
-1.7
20. 9
6.3
11.9
2.1
3.8
4th
20
-4.2
11.2
-13.5
18.2
7.8
12.0
1 . 5
3.2
1st
GM
60
-1.9
14.0
-2.2
17.1
-3.6
7.6
0.9
3.7
2nd
79
-2.3
11.3
-0.4
16.0
-3.3
7.2
1.8
2.3
3rd
81
1.1
15 .0
2 . 9
18.3
-6.1
9.4
2.2
2.9
4th
29
-0.4
11 .4
6.6
16.2
-3.9
5.9
2 . 5
2.0
1st
EPA
182
0.7
15.1
5.4
18.3
0.1
10.8
-1.2
4.7
2nd
279
-0.3
15.0
1.9
18.7
-1.3
11.2
-2 . 9
3.7
3rd
216
-1.7
14.8
-0.4
19.2
-1 .5
12.3
-1.9
3.7
4th
95
0.7
11.6
1.8
19.6
-1.7
11.6
-1. 6
4.0
*
Percent
Dif. Over
40.0
Deleted From
i Data
FUEL ECONOMY PLANNING
6/24/77
§
NJ
•s
-------
1977 PAIRED DATA PERCENT* DIFFERENCES (75 FTP)
Quarter
HC
CO
# Tests Mean Std. Dev. Mean Std. Dev.
NOx
COa.
Mean Std. Dev. Mean Std. Dev.
1st
2nd
3rd
4th
AMC
2
14
15.5
-0.6
1.9
12.7
-21.9
-17.6
7.6
10.5
-3.3
12 .0
10.4
12.1
-1.3
0.6
0.2
3.0
1st
2nd
3rd
4 th
CHRYSLER
7
36
-3.8 11.4
-3.1 16.3
-8.9
-5.4
17.8
15.2
¦2 .O
7.3
6.3
12 .2
¦1.2
1.7
1. 5
4.4
1st
2nd
3rd
4 th
FORD
21
40
1.0
-1.6
15.9
11.9
-12 . 9
•*5.7
17.6
16.2
10.7
2.3'
13. 9
13.8
O. 8
2.0
3.5
4.5
1st,
2nd
3rd
4 th
1st
2nd
3rd
4 th
GM
EPA
5
81
35
171
• 11.4
- 6. 5
0.9
4.1
10.3
14.8
14.8
14.4
12.4
-3.4
12.6
5.5
18.4
15.7
16.9
15.7
1.7
r-4.3
-6.1
-1.0
8.9
8.7
12.9
12.4
2.4
1 .6
-0.5
¦1.6
2.1
3.2
3.1
3.8
* Percent Dlf. Over 40.0 Deleted From Data
0\
Q>
a
•s
ISJ
FUEL ECONOMY PLANNING
9/6/77
-------
f op tx
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CO
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MAY-AUG 75 BACK TO BACK
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0 .30 0 .60 0.90 I "20
CHRYSLER HC VALUE
1 .50
I .80
-------
PA$e >o op it.
o
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MflY-RUG 75 BACK TO 5RCK
o
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CHRYSLER CO VRLUE
15.00
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¦ 3 (5 '
-------
Pteje It oF
MRY-RUG BACK TD BRCK
m
u
/
E
E
«n
/ ZfD
m /
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1.30 1.90 2.50 3-.10
CHRYSLER NOX VALUE
3.70
- 5 V5 5
-------
IS. op 13.
o
o
1flY-flUG 75 BACK TO BRCK
~
/
2
f*
n y®
J D /
/ c
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f*
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w
3
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w
^0.00 45-00
60.00 75.00 90.00 105.00
CHRYSLER CD2 VALUE *10l
120.00
C - 7 V3 8
-------
?T€o Sy : t>Ave Quisrr
G,ev£OAL. V*OTo1S
1978 CERTIFICATION PAIRED TEST PERCENT DIFFERENCE
EPA CORRELATION)
FVl^e / OF H
1
2
sd CM Ifi 11) ffl II) B © O © B ffl H H H H N N B Tj( ^ « lO m 00 CO 00 00 0»
*3 ca 3S c$ K w n n n n ea cjoooo ooooooo oooooo o
-------
-------
1978 VEL/EPA FTP CORRELATION
TEST INTERVAL > 49000
DIFF s VEL - EPA
TESTED
VEL 6- 2-77
EPA 6- 3-77
DIFF
* DIFF
ODOMETER
49328 MILES
49377 MILES
-49 MILES
BAROMETER
28.54 H6
29.IS HG
-0.64 HG
-2.2
WET - DRY DEW PT
58.0 72.0 F 0.00 F
61.5 73.0 F 0.00 F
-3.5 -1.0 F 0.00 F
-5.7 -1.4 0.00
« DIFF « (VFL - EPA )MOO/EPA
COMPOSITE GM/MI
PHASE 1 GRAMS
SPEC HUM
52.08 GR/LB
64.41 GR/LB
-12.33 GR/LB
*19.14
phase 2 grams
EVAP GMS
0.00
0.00
0.00
0.00
VEL
EPA
* DIFF
VEL
EPA
« DIFF
VEL
EPA
* DIFF
VEL
EPA
DIFF
MC
0.61
0.63
-2.7
7.11
7.04
1.0
0.72
0.83
-13.8
1.32
1.62
-0.017
CO
10.30
11.37
-9.4
140.42
142.51
-1.5
7.14
9.08
-21.4
14.89
27.64
-1.071
NOX
1.13
1.21
-6.7
5.17
5.82
-11.2
3.29
3.63
-9.5
4.99
5.36
-0.081
C02
617.9
608.9
1.5
2215.5
2267.5
-2.3
2477.0
2512.3
-1.4
1978.3
1971.2
8.970
MPG
13.9
14.1
-1.1
12.8
12.8
0.2
13.6
13.8
-1.5
IS.7
16.0
-0.160
MILES
10.934
11.207
-2.4
3.560
3.633
-2.0
3.816
3.936
-3.0
3.558
3.638
-0.273
PHASE 3 GRAMS
« DIFF
-18.2
-46.1
-6.8
0.4
-1.5
-2.2
% CONTRIBUTION*(tVEL -EPA >»100/(SUM OF WGTO EPA GH/Ml))
PHASE
1 WGTD
GMS/MI
PHASE
2 WGTD 1
SMS/MI
PHASE
3 WGTD
GMS/MI
VEL
EPA
« CONT
VEL
EPA
% CONT
VEL
EPA
% CONT
HC - WGTD
0.414
0.400
2.28
0.097
0.110
-2.00
0.102
0.122
-3.09
CO - WGTD
8.186
8.096
0.79
0.968
1.199
-2.03
1.151
2.080
-8.17
NOX - WGTO
0.301
0.331
-2.43
0.446
0.479
-2.78
0.386
0.403
-1.43
C02 - WGTD
129.16
128.82
0.06
335.88
331.80
0.67
152.92
146.35
0.75
COMMENTS t SUM OF WGTD PHASE GRAMS/MILE IS THE COMPOSITE GRAMS/MILE
-------
VEL - EPA CORRELATION
PAIRED TEST DIFFERENCES
9 Of il
1978 FLEET
-------
1970 VEL/EPA FTP CORRELATION
summary or actual differences in grams/miie and grams
—— COMPOSITE
95*
Me a*
RANGE CONF. LIMIT
MEAN
STO OEV
MAX
MIN
MAX
MIN
HC
>0.03
0.15
0.*6
-0.05
0.01
"¦0.07
CO-
-o.**
1 *51
3*70
-*.*3
•0.02
-O.OT
NOK
-0.15
0.1?
0.19
-0.77
-0.11
-0.20
roz
*.69
IT.7?
107.10
-*9.36
13.A6
3.71
MP6
-0.15
0.3?
1.05
-0.90
-0.06
-0.2*
PHASE 1 PHASF 2 — PHASE 3
9S» 9595 95*
MEAN ¦•WEAN-- MEAN-
CONF..
LIMIT
CONF.
LIMIT
COW.
LIMIT
MEAN
STD OEV
MAX
NIN
MEAN
STO OEV
MAX
MIN
MEAN
STO OEV
MAX
MIN
K
-0.32
2.1*
ft. 14
-0.9®
-0.00
0.22
-0.01
-0.1*
-O.OB
0.17
-0.03
-0.13
;o
-6.*1
17.2?
-t.«W
-11.25
-0.56
*.01
0.79
-1*91
-0.03
*.93"
— 0.56-
-tiZl
tox
-0.09
0.07
-0.65
-1.1*
-0.52
0.66
-0.3*
-0.71
-0.62
0.66
-0.*3
•0.00
02
20.42
63.57
*6.?9
Id.54
1.16
00.10
£3.7]
-21.39
1*.?*
01.59
37.10
-0.70
PG
-0.17
n.*2
-0.06
-0.29
-0.1*
0.32
-a.os
-0.23
-0.16
0.50
—O.02
-0.30
CERT WEEKLY UPDATE •••¦••••••••«
I97R CERTIFICATION FLEET PAIRED TEST SUMMARY
NUMBER OF PAIRED TESTS FOR THIS SUMMARY m SI
It 4» iOj u-n
1978 UPDATE SUMMARY
PAGE ONE OF FOUR
-wsiitrr-tee:—
-------
197R VfL/EMA fTP CORRELATION
SUMMARY OF PCPrFNTAftF niFFFBFNCFS CALCULATED FROM CiWAMS/MlLE AMD B»AmS
: COMPOSITE
RANGE
MEAN
CONF. LIMIT
MFAM
STO OFV
MU
MlN
MAX
MJN
MC
-3.76
16.07
65.13
-50.46
0.>5
-8.2*
CO
-6.64
M.Tf
49.44
-66.98
-0.80
-12.48
NOX
-7.S6
T.3R
14.79
-26.27
-5.49
-9.64
CO?
1.33
2.3?
11.14
-7.53
1.98
0.68
MPT,
-1.10
2.3*
7.19
-10.32
-0.44
-1.77
PHASE 1
9S*
WFAV
PHASE 7
95*
mcaut
Phase- 3
9S%
HE AN
COHF .
LIMIT
COHF,
LIMIT
CONF.
LIMIT
MEAN
STO OFV
MAX
MIN
MEAN
STO OCV
MAX
MIN
MEAN
STO OFV
MAX
MIN
HC
-3.27
1A.46
1.92
-8.47
-8.09
J>1.«0
-1.96
-14.22
-6.76
19.14
-1.38
-12.14
CO
•6.76
19.44
-1.-W
-12.23
9.39
118.09
42.60
-23.82
5.21
94.79
31.86
-21.45
MOX
-9.05
7.70
-6.88
-11.21
-8.70
10.67
-5.70
-11.71
-7.43
7.25
-5.39
-9.47
C02
1.33
?.76
?.tl
0.96
-0.11
2.7»
fl.67
-0.90
0.72
3.42
1.68
-0.24
HPS
-1.20
2.69
-0.45
-t.96
-I.11
2.37
-A.44
-1.78
-0.99
3.37
»0.04 •
-1.93
197ft IIPOATE SUMMARY
PAGE TWO OF FOUR
•#/»2/TT--I.CE-
-------
1970 VEL/EPA FTP CORRELATION
SUMMARY OF PERCENT CONTRIBUTIONS CALCULATE* FROM VGTO GMS/Mi
— PHASE t
9S«
MEAN
PHASE ? ~
451
MEAN
eo*)F.
LIMIT
CONF.
LIMIT
MEAN
STD OFV
MAX
HlN
MEAN
STO DEV
MAX
MIN
HC
-1.29
13.57
2.13
-5.10
-1.S3
5.at
-•.10
—2.95
CO
-4.83
14.79
-0 .*7
-B.99
-1.1*
7.95
1.10
-3.37
MOX
-2.35
2.15
-I.7S
-2. 9ft
-3.10
*.11
-1.94
-4.25
C02
0.4a
0.58
0.65
0.3?
0.44
1.32
0.81
0.07
NO. OF
VF|. TFSTS
PeOTESSFO
¦ SI
NO. OF EP*
TESTS
PROCESSED
- It
— PHASe-3-— —
95«
MEAN
CTWr t
¦—fcfMlf
MEAN
STO DEV
MAX
MIN
-0.9S
2.99
-O.lt
-1.79
-0.67
5.39
0.85
-2.19
-2.12
2.26
-1.48
-2.75
0.41
0.80
0.64
0.18
197ft UPOATE SUMMARY
PAGE THREE Of FOUR
-08/12/77 LC€—
-------
SUMMARY or CflNCTtTUrNT LFVF15
•• vrt
••
MTAN
HtM
MAX
HC
COMP
«>0
0.2ft
1.17
PH I
5.36
2.09
16.00
PM 2
0.73
0.24
3.07
PH 3
0.95
0.33
2.53
CO
co*x>
4.06
1.61
12.04
PH 1
77.02
6.11
135.67
<»H 2
6.01
-0.01
30.95
PM 3
9.30
-O.OB
36.76
MOX
CO"P
1.*?
0.06
2.6?
PM 1
4.00
3.57
12.17
PH 2
4.79
2.51
0.45
PM 3
A.67
3.13
11.02
CO?
comp
621.50
319.9*
1018.61
PH 1
2301.06
1097.IS
3m.es
PH 2
2465.47
1305.66
4154.00
PH 3
2060.69
1069.17
3?03.S9
MPO-
COMP
14.8*
8.60
26.38
PH 1
13.92
8.21
25.50
PH -2
14.«ft
- 8.23
25.63
PH 3
16.25
9.74
20.72
HF AN
6.41
03.43
6.57
10.12
MJN
MAS
0.51
0.20
1.69
5.60
2.05
25.11
0.01
0.27
3.51
1.03
0.37
2.56
1.63
6.34
o.oo-
0.59
11.96
153.30
25.06
39.60
1*77
0.96
2.93
8.90
4 . 29
14.39
5.31
2.54
9.07
7.29
3.70
13.70
612.81 319.40 923.59
2273b44 1OBI.71 1749.71
2464.31 1346.9* 3736.31
2046.45 1045.14 3051.57
IS.05
14.10
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13.25
1970
PAGE
update Summary
row or roup
TV
-------
9
VEL-EPA PAIRED TEST
PERCENT DIFFERENCE (%A)
AVERAGE BY MONTH
1978 CERTIFICATION PROGRAM
„ . VEL-EPA
%A EPA ,K)0
—J
-------
?«E
EG. 1*36 MffiE
H. ^V#iDMVE WbE
fa Moment
'6. DISTRI®0tf5^ E#£6TS
C. 3
m m a:2 m
A US - \H
% n & ii ii
Uk . 'N
-------
P%£ Z OF q
VII. SUMMARY STATISTICS
A. UNDERSTANDABILITY
B. AVAILABILITY OF STAT. PACKAGES
C. K, v s. I1IN., MAX.
D. GRAPHICAL ANALYSES
E. PARAMETRIC ANALYSES
F. NON-PARAMETRIC ANALYSES
VIII. TREND ANALYSES
A. WEEKLY, MONTHLY
B. SEASONAL
C. TIME SERIES
D. CUSUM
IX. MEASURES
A. DIFFERENCES
B. PER CENT OF VALUE
C. PER CENT OF STANDARD
D. JEOPARDY INDICIES
E. OTHER OBJECTIVES, OTHER ISSUES, OTHER MEASURES
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