CRC Report No. E-90 

IMPACT OF E15/E20 BLENDS ON 

OBDII SYSTEMS -- PILOT STUDY 

March 2010 

COORDINATING RESEARCH COUNCIL, INC. 

3650 MANSELL ROAD·SUITE 140·ALPHARETTA, GA 30022
The Coordinating Research Council, Inc. (CRC) is a non‐profit corporation

supported by the petroleum and automotive equipment industries.    CRC

operates through the committees made up of technical experts from

industry and government who voluntarily participate.  The four main areas

of research within CRC are :    air pollution (atmospheric and engineering

studies); aviation fuels, lubricants, and equipment performance, heavy‐duty

vehicle fuels, lubricants, and equipment performance (e.g., diesel trucks);

and light‐duty vehicle fuels, lubricants, and equipment performance (e.g.,

passenger cars).    CRC’s function is to provide the mechanism for joint

research conducted by the two industries that will help in determining the

optimum combination of petroleum products and automotive equipment.  

CRC’s work is limited to research that is mutually beneficial to the two

industries involved, and all information is available to the public.

CRC makes no warranty expressed or implied on the application of

information contained in this report.  In formulating and approving reports,

the appropriate committee of the Coordinating Research Council, Inc. has

not investigated or considered patents which may apply to the subject

matter.    Prospective users of the report are responsible for protecting

themselves against liability for infringement of patents.
1

dKC de la Torre Klausmeier Consulting 

 _____________________________________ 1401 Foxtail Cove 

Austin, TX 78704 

(512) 447-3077 

E-mail: delaklaus@aol.com

CRC E-90 PROJECT 

IMPACT OF E15/E20 BLENDS ON 

OBDII SYSTEMS – PILOT STUDY 

Final Report 

Prepared by: 

Rob Klausmeier 

de la Torre Klausmeier Consulting, Inc. 

March 9, 2010 
2

TABLE OF CONTENTS 

EXECUTIVE SUMMARY ................................................................................................ 4 

1.0 INTRODUCTION.................................................................................................. 5 

2.0 TEST PROCEDURES. ......................................................................................... 8 

 2.1 Inspection/Maintenance (I/M) Sites Selected for Testing ..................... 8 

 2.2 Fuel Samples............................................................................................ 8 

 2.3 Site Test Plan ........................................................................................... 9 

 

3.0 DATA ANALYSIS .............................................................................................. 15 

 3.1 Data Compilation ................................................................................... 15 

 3.2 Representativeness of Test Samples................................................... 18 

 3.3 Long-Term Fuel Trim (LTFT) Trends.................................................... 27 

 3.4 Projection of MIL Illumination Events.................................................. 43 

 3.5 Analysis of Texas Inspection/Maintenance Data ................................ 50 

4.0 CONCLUSIONS................................................................................................. 55 
3

ACKNOWLEGEMENTS 

de la Torre Klausmeier Consulting, Inc. (dKC) would like to acknowledge the 

cooperation and support we received from the following government agencies and 

organizations: 

1. Illinois Environmental Protection Agency (IEPA) 

2. The Texas Commission on Environmental Quality (TCEQ) 

3. Applus Technologies, Inc. 

4. Dekra Emission Test, Inc. 

5. The Sticker Store 

This project would not have been possible without their support. Finally, dKC would like 

to acknowledge the skill and determination of Graham Waak who collected most of the 

data and the CRC E-90 Committee for their guidance on this project. 
4

                                                           

EXECUTIVE SUMMARY 

de la Torre Klausmeier Consulting, Inc. (dKC) was contracted by the Coordinating 

Research Council (CRC) to study the potential impact of 15% and 20% ethanol/gasoline 

blends (E15/E20) on the onboard diagnostic (OBDII) system of in-use vehicles. The 

goal of this study was to collect and analyze OBDII and related data from in-use 

vehicles to determine the potential for more frequent malfunction indicator light (MIL) 

illuminations when a vehicle is fueled with E15 or E20. To meet this goal, dKC 

identified inspection/maintenance (I/M) programs that were operated in areas where 

gasoline with no ethanol (E0) and 10% ethanol (E10) was dispensed. dKC then set-up a 

test program where long-term fuel trim (LTFT) and other parameters were recorded 

over a 10 minute period after vehicles received their periodic I/M test. 

Findings and conclusions from this study are listed below: 

• Operation on 10% ethanol/gasoline blends (E10) increases LTFT over E0 levels 

for most vehicles. The sensitivity varies by original equipment manufacturer 

(OEM), but all OEMs show the trend.

• The tests conducted in this study provide evidence that operation on 15% or 

20% ethanol/gasoline blends (E15 or E20) may cause a subset of problem-free 

vehicles to illuminate their malfunction indicator light (MIL) due to excessively 

lean1 operation. The fraction depends on the assumed LTFT threshold2 and the 

fuel ethanol content and is roughly estimated to be of the order of a percent or 

so. A more precise estimate of this fraction cannot be made with the available 

data. 

• There is also evidence that operation on E15 and E20 may cause some vehicles 

that currently have illuminated MILs due to rich3 operation to appear to be 

problem free, but no vehicles with this type of illuminated MIL were detected in 

this program. 

• Additional study is needed to better quantify potential ethanol-related issues with 

OBD MIL. Vehicle testing on E15 or E20 is needed to confirm that false positive 

or negative MIL illumination will occur. Further analysis of MIL status from I&M 

data and more detailed MIL illumination thresholds for different OEMs will also 

help to better define the scope of this problem.

• Not ready rates4

 for the evap monitor in Texas were higher in the E10 area than 

in the E0 area. More data would also be required to determine if ethanol was 

affecting this parameter. 

1

 Lean: More air than required for optimum combustion. 

2

 LTFT threshold: The LTFT value at which the OBD system illuminates the MIL. 3

 Rich: More fuel than required for optimum combustion. 

4

 OBDII systems have up to 11 diagnostic monitors, which run periodic tests on specific systems and 

components to ensure that they are performing within their prescribed range. OBDII systems must 

indicate whether or not the onboard diagnostic system has monitored each component. Components that 

have been diagnosed are termed “ready”, meaning they were tested by the OBDII system. 
5

1.0 INTRODUCTION 

Due to state and federal encouragement of increased ethanol production and use, by 

2013 the supply of ethanol will likely exceed the amount required to blend into the 

national motor gasoline fuel pool at the current maximum permissible per gallon limit of 

10% by volume (E10). One suggested solution for the disposition of this “extra” ethanol 

is to introduce an intermediate blend; e.g. a gasoline containing either 15% ethanol by 

volume (E15) or 20% ethanol by volume (E20). There have recently been attempts to 

expedite the introduction of these fuels, even before the 10% blend wall is reached. 

de la Torre Klausmeier Consulting, Inc. (dKC) was contracted by the Coordinating 

Research Council (CRC) to study the potential impact of 15% and 20% ethanol/gasoline 

blends (E15/E20) on the onboard diagnostic (OBDII) system of in-use vehicles. 

Automobile manufacturers have expressed concern that vehicles running on E15 or E20 

may experience more frequent malfunction indicator light (MIL) illuminations than 

vehicles running on E10 and below. They have identified the need for a study of how 

ethanol blends will impact OBDII system performance, particularly on high mileage 

vehicles. 

How Ethanol Could Affect MIL Illumination 

Automobile manufacturers have expressed concerns over two types of events that 

could affect MIL illumination: 

1. A vehicle operating close to an OBD-II threshold level when consuming E0 or 

E10 might exceed the MIL-on criterion when fueled with E15 or E20, thereby 

causing the MIL to illuminate when nothing is wrong with the vehicle. 

2. In the case of vehicles running too rich, ethanol-induced enleanment might move 

the vehicle back from beyond the OBD threshold and create a “false negative” 

situation where the MIL does not illuminate when it should. 

The OBDII threshold of most interest with respect to ethanol effects is long-term fuel 

trim (LTFT). Fuel trim refers to dynamic adjustments to algorithms stored in the 

powertrain control module PCM) that determine the fuel injector pulse for the proper 

fuel/ air ratio applicable to the engine operating conditions. Short term fuel trim refers to 

adjustments being made in response to temporary conditions. Long term fuel trim is 

used to compensate for issues that seem to be present over a much longer period5. 

The picture below highlights the concern over the 1st problem – false MIL illumination. In 

this case, a vehicle is operating correctly on E10 but is close to the fuel trim limit. 

Operation on fuels containing 15% or 20% ethanol could push this vehicle over the limit 

and illuminate the MIL when in fact nothing is wrong with the vehicle. 

                                                           

5

 Description provided by http://www.obd2crazy.com/techdata.html. 
The picture below highlights the concern over the 2nd problem – failure to properly 

illuminate the MIL when a vehicle is running too rich because ethanol-induced 

enleanment can move the vehicle back from beyond the OBD threshold. 

6
Objectives and Strategy 

The goal of this study was to collect and analyze OBDII and related data from in-use 

vehicles to determine the potential for MIL illumination when a vehicle is fueled with an 

intermediate ethanol blend. Vehicles were tested after they received their periodic 

inspection/maintenance (I/M) test. Target data included long-term fuel trim (LTFT) and 

OBD diagnostic trouble codes (DTCs) related to enleanment. To ensure that data were 

collected in a consistent manner and under the conditions of interest, a specific test 

protocol was followed. To facilitate data interpretation, vehicle testing was performed in 

regions where E10 was marketed exclusively, and also in a region where E0 was 

marketed exclusively. 

Report Organization 

This report is organized as follows: 

• Test procedures are described below. 

• Analysis of data collected in the program is presented in Section 3.0. 

• Conclusions are presented in section 4.0. 

7
8

2.0 TEST PROCEDURES 

In this project, vehicles were tested after they received their periodic 

inspection/maintenance (I/M) test. The text below describes the test procedures for this 

project. 

2.1 Inspection/Maintenance (I/M) Sites for Testing 

Table 1 presents the sites selected for testing. All testing was done at stations that were 

licensed to perform state inspection/maintenance (I/M) tests. We tested 140 vehicles in 

an E0 location (Austin, TX) and 443 vehicles in E10 locations (Dallas-Ft. Worth and 

Chicago). Tests were conducted in high volume centralized and decentralized facilities. 

We initiated testing at the end of April 2009 and completed testing in the end of July 

2009. We tested about the same number of vehicles in Chicago and Dallas-Ft. Worth to 

avoid overweighting the sample with tests conducted during hot weather conditions. 

Exhibits 1-3 show pictures of the testing sites. These exhibits are presented at the end 

of the section. 

Table 1-- I /M Sites for Testing 

Site Type of I/M Facility Expected Ethanol 

Content 

# of vehicles 

tested 

Austin TX Decentralized E0 140 

Chicago IL Centralized E10 218 

Plano (DFW) TX Decentralized E10 225 

2.2 Fuel Samples 

We collected 20 fuel samples at different gasoline stations in the Austin area and sent 

them to Southwest Research Institute for analysis. As shown on Table 2, none of the 

samples had significant amounts of ethanol. Confidential information from an oil 

industry representative indicated that the Dallas-Ft Worth and Chicago areas only 

dispense E10. 

Table2—Results of Fuel Sampling in the Austin Area 

Sample API@60F SPGr@60F EtOH Vol%

1 57.7 0.7478 <0.1

2 57.8 0.7474 <0.1

3 57.5 0.7488 <0.1

4 58.2 0.746 <0.1
9

Sample API@60F SPGr@60F EtOH Vol%

5 57.1 0.7501 <0.1

6 57.2 0.75 <0.1

7 57.3 0.7496 <0.1

8 57.9 0.7472 <0.1

9 57.8 0.7475 <0.1

10 58.3 0.7457 <0.1

11 58.1 0.7465 <0.1

12 58.1 0.7465 <0.1

13 57.7 0.7479 <0.1

14 58.2 0.7459 <0.1

15 57.7 0.7479 <0.1

16 57.5 0.7486 <0.1

17 57.3 0.7495 <0.1

18 57.7 0.7481 <0.1

19 58.4 0.7451 <0.1

20 56.9 0.7509 <0.1

2.3 Site Test Plan 

The following vehicle solicitation and test procedures were used: 

1. Vehicle Solicitation: 

a. Vehicle Mix: 1996 and newer model vehicles were picked at random 

when they showed up for their state emissions test. The following vehicles 

were not tested: 

i. Flexible Fuel Vehicles (FFVs) – FFVs were not included, because 

they are already designed for intermediate ethanol/gasoline blends. 

ii. Hybrids – Hybrids were not included, because some of them turn 

the engine off at idle. 
10

                                                           

b. Motorist Participation: 

i. Centralized Lanes: In centralized test lanes, motorists driving 

1996 and newer vehicles6 were approached while they were 

waiting in line in their vehicles and were asked if they wanted to 

participate in the study. At the beginning of the day, the motorist at 

the front of the line was asked to participate. If that person declined, 

then the next motorist was asked to participate, and so forth. 

Motorists were provided with the flyer shown in Appendix A-1 to 

introduce them to the program. After the vehicle was tested, we 

repeated the process described above. 

ii. Decentralized Facilities: The poster shown on Appendix A-1 was 

set up in the lobby of decentralized test facilities to provide an 

introduction to the program. Motorists driving 1996 and newer 

models were asked to participate when they came into the office. 

The tester followed the same selection protocol as described above 

for centralized facilities. 

iii. Incentive: The tester offered motorists $20 in cash to participate. 

c. Questionnaire: Motorists agreeing to participate were asked to fill out the 

questionnaire shown on Appendix A-2. The tester entered the VIN and 

odometer information and recorded the ambient temperature. 

d. Log of vehicles whose owner declines to participate: The tester 

maintained a log of the following information on vehicles whose owner 

declined to participate: 

i. Year, Make, Model

ii. Reason for not participating

e. List of all other vehicles undergoing I/M procedures at the site during 

the test days of this study: A list of all vehicles tested at the Plano and 

Chicago I/M stations during the days in which this study was conducted 

was obtained from the station manager. This type of list was not available 

for the Austin station. 

2. Vehicle Testing: The test procedure was as follows: 

a. The tester followed the checklist shown on Appendix A-3 to ensure that all 

required data recording and vehicle prep tasks were done. 

b. The motorist or state inspector was instructed to park the vehicle in a 

designated area. 

c. The motorist or state inspector was instructed to turn off the engine. 

d. The tester took the following pictures of the vehicle: 

i. Overall vehicle: Front, back, left side, right side 

6

 Illinois only tests 1996 and newer vehicles. 
11

ii. Underhood Emissions Label (see Appendix A-4) 

iii. VIN (see Appendix A-5) 

e. Test equipment was hooked-up while the vehicle engine was off. The test 

equipment consisted of a laptop with OBDII connector. Details can be 

found at http://www.autoenginuity.com. 

f. The vehicle was placed in the key-on engine off position to establish 

communication with the test equipment. 

i. The tester selected the “Generic Test” mode. 

ii. The tester first checked if any Diagnostic Trouble Codes (DTCs) 

were recorded. If they were, the tester recorded a screen print of 

the DTC screen. 

iii. The tester then went to the OBD Status screen and made a screen 

print of the readiness status. 

iv. The tester then went to the data logging page and initiated data 

logging. Table 2 lists the data that are recorded on most vehicles in 

“Generic Test” mode. 

g. The vehicle remained off for about 10 minutes. At the end of the soak 

period, the vehicle was started and about five minutes of additional data 

was logged. If possible, the tester tested for a longer period, especially if 

long-term fuel trim had not stabilized.

h. At the completion of the test, the vehicle was turned off, test equipment 

was removed and the motorist was paid the incentive. 

3. Data Compilation: Data were compiled after each day of testing. Copies were 

sent to the study project officer and dKC project manager. After field tests were 

completed, dKC distributed individual test results to the appropriate manufacturer 

for analysis. 
12

Table 2 – Typical OBDII Generic Data Parameters Recorded on a Second-bySecond Basis ((Note DTCs, MIL Status and Readiness Status were recorded on all 

vehicles) 

Parameter Example Value 

Time 02:28:11 

 Calculated Load (%) [0 - 100] 14 

 Coolant Temperature (F) [-40 - 419] 194 

 Short Term FT B1 (%) [-100.00 - 99.22] -0.78 

 Long Term FT B1 (%) [-100.00 - 99.22] -2.34 

 Engine RPM (r/min) [0 - 9000] 660 

 Vehicle Speed (MPH) [0 - 158] 0 

 Ign. Timing Adv. C1 (deg) [-64.0 - 63.5] 13.5 

 Intake Air Temp. (F) [-40 - 419] 124 

 MAF Air Flow Rate (lb/min) [0.00 - 86.70] 0.28 

 Abs. Throttle Pos. (%) [0 - 100] 15 

 B1S2 O2 Voltage (V) [0.000 - 1.275] 0.095 

 B1S2 O2 Fuel Trim (%) [-100.00 - 99.22] 99.06 
Exhibit 1 – Austin TX Site 

Exhibit 2 – Chicago (Addison) Illinois Site 

13
Exhibit 3 – Dallas Ft. Worth (Plano) Texas Site 

14
15

 

3.0 DATA ANALYSIS 

3.1 Data Compilation 

Prior to analyzing results, dKC developed spreadsheets that summarized test results for 

each vehicle. Table 3 presents information that was summarized for each vehicle that 

was tested. The long-term fuel trim (LTFT) values recorded in the summary database 

were based on the second-by-second results recorded on each vehicle. To facilitate a 

systematic analysis, dKC categorized the following parameters: 

• Assumed Ethanol Content (E0 or E10) 

• Odometer (<100,000 miles, >100,000 miles) 

• Ambient Temperature (<90 deg F, >90 deg F) 

• Max, Min, and Last LTFT value 

• MIL-Command status 

• Readiness status 

Table 3 – Data Analyzed for E-90 Study 

Field Description 

Site Austin, Chicago, Plano 

Ethanol E0, E10 

Date 

Plate 

Year 

Make 

MFR Groups of Makes manufactured by same company, e.g. Honda: Honda 

+ Acura 

Model 

Odometer 

Odometer Category <100,000, >100,000 

VIN 

Temperature 

Temp_Category <90 deg F, >90 deg F 

Engine Family From Label if available 

Evap Family From Label if available 

COM Was system able to communicate? (0=no, 1=yes) 

LTFT B1 Min Min Long-Term Fuel Trim (LTFT) value for Bank 1 

LTFT B1 Min Category Grouped in 2% increments: e.g., (1) -1=0, 1-3= 2, (1)-(3)=-2, ... 

Note, values>13=14, values<(13)=-14 

LTFT B1 Max Max LTFT value for Bank 1 
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Field Description 

LTFT B1 Max_Category Grouped in 2% increments: e.g., (1) -1=0, 1-3= 2, (1)-(3)=-2, ... 

Note, values>13=14, values<(13)=-14 

LTFT B1 Last Last LTFT value for Bank 1 

LTFT B1 Last Category Grouped in 2% increments: e.g., (1) -1=0, 1-3= 2, (1)-(3)=-2, ... 

Note, values>13=14, values<(13)=-14 

LTFT B2 Min Min LTFT value for Bank 2 

LTFT B2 Max Max LTFT value for Bank 2 

LTFT B2 Last Last LTFT value for Bank 2 

Diagnostic Trouble 

Codes 1 

1st DTC 

Diagnostic Trouble 

Codes 2 

2nd DTC 

Diagnostic Trouble 

Codes 3 

3rd DTC 

Diagnostic Trouble 

Codes 4 

4th DTC 

MIL-On Is MIL commanded-on? 0=no, 1=yes 

Unset Monitors What non-continuous monitors were not ready 

Not Ready Any monitors not ready? 0=no, 1=yes 

Fail EPA Ready Fail EPA readiness criteria for I/M programs: 

1996-2000 models: >2 monitors not ready 

2001+ models: >1 monitor not ready 

dKC developed a spreadsheet summarizing information on vehicles whose owners 

declined our request for participation in the study. Data on this spreadsheet is presented 

on Table 4. 

Table 4 – Data Recorded on Vehicles Whose Owners Rejected Test Request 

Date 

Year 

Make 

Model 

Reason for Rejection 

Site 

dKC also provided each manufacturer with second-by-second test results and summary 

spreadsheets on their vehicles. 

3.1.1 Analyzer Issues 

Below is a discussion of analyzer issues that impacted test results for some of the 

vehicles. 
17

No Communication 

The testing system could not communicate with 8% of the vehicles. Table 5 shows the 

communication rates by model year. Table 6 shows rates by manufacturer. Rates were 

fairly uniform by model year and manufacturer, so it does not appear that lack of 

communication between the test system and the analyzer biased the results. Included in 

the no communication category are test results on two vehicles that had errors 

recording long-term fuel trim (LTFT), even though the test system accurately reported 

other parameters from these vehicles. 

Table 5 – Communication Rates by Model Year 

Model Year 

# Communicated 

with Test System # Tested % Communication 

1996 16 17 94.12% 

1997 27 28 96.43% 

1998 28 30 93.33% 

1999 57 66 86.36% 

2000 43 45 95.56% 

2001 58 62 93.55% 

2002 44 47 93.62% 

2003 75 82 91.46% 

2004 35 35 100.00% 

2005 83 89 93.26% 

2006 35 38 92.11% 

2007 29 33 87.88% 

2008 7 9 77.78% 

2009 2 2 100.00% 

ALL 539 583 92.45% 

Table 6 – Communication Rates by Manufacturer 

MFR % Communication 

OEM1 91.30% 

OEM2 92.92% 

OEM3 87.50% 

OEM4 89.52% 

OEM5 98.67% 

OEM6 95.83% 

OEM7 88.89% 

OEM8 89.61% 

OEM9 95.59% 

ALL 92.45% 
18

Communication Ceased When Engine Was Started 

As noted in section 2, we initiated data logging while the vehicle was in the key-on 

engine-off position. When the engine was started, the test system lost communication 

with a few vehicles. When this happened, we had to re-start the analyzer and reinitialize communication. In these cases, we were not able to capture data parameters 

for 1-2 minutes after the engine was started. As noted later in this section, the LTFT 

values that were of greatest interest were recorded at the end of the test period, and not 

immediately after the engine was started. 

3.1.2 Missing Information 

Changes in Data Recording Procedures 

Based on feedback from the Committee, after the first week of testing we started to 

record additional data, including the following: 

• Engine Family (from Emissions Label) 

• Evap Family (from Emissions Label) 

• Ambient Temperature 

We used ambient temperature to group tests into two categories: < 90 deg F, > 90 deg 

F. The maximum temperature during the first week of testing was less than 90 deg F, so 

we grouped all the test results for the first week into the less than 90 deg F category. 

Missing Emissions Labels 

Some of the older vehicles had missing or obscured emission control system labels, so 

we were not able to record engine or evap families. 

No Odometer Reading 

Some vehicles had inoperative odometers, so we were not able to record an odometer 

on them. 

3.2 Representativeness of Test Samples 

We evaluated the representativeness of the sample using several metrics: 

• Model year distribution of the sample: 

o E0 vs. E10 sample 

o Tested vehicles vs. Rejects 

o Comparison with all vehicles tested at station or in region. 

• Percent of vehicles with OBD faults 

• Distribution of Makes tested 
3.2.1 Model Year 

Figure 1 shows the distribution of model years by test site. Figure 2 compares the 

distribution of model years for E0 and E10 samples. The odd even variation for the 

Chicago sample reflects the fact that Chicago’s program is biennial and more oddmodel year vehicles are tested in odd years, and vice versa. Overall as shown on 

Figure 2, there is good agreement between the E0 and E10 samples. 

Figure 1 

Figure 2 

19
20

Table 7 shows a tabular breakdown of test counts by model year for E0 and E10 

samples. Table 8 shows a breakdown of test counts by model year for the three sites. 

Table 7 -- Test Vehicle Counts by Assumed Ethanol Content 

Model Year E0 E10 

1996 5 12 

1997 9 19 

1998 6 24 

1999 14 52 

2000 18 27 

2001 11 51 

2002 16 30 

2003 14 68 

2004 8 27 

2005 15 74 

2006 14 24 

2007 5 28 

2008 5 4 

2009 2 

Total 140 443 

Table 8 -- Test Vehicle Counts by Test Site 

Model Year Austin Chicago Area Plano 

1996 5 5 7 

1997 9 18 1 

1998 6 8 16 

1999 14 31 21 

2000 18 5 22 

2001 11 35 16 

2002 16 6 25 

2003 14 54 14 

2004 8 7 20 

2005 15 46 28 

2006 14 24 

2007 5 2 26 

2008 5 1 3 

2009 2 

Total 140 218 225 
Comparison of Study Sample with All Tests In Area or Station 

We were not able to get a list of all vehicles tested at the Austin test site while the tests 

for this study were done, so we compared our sample from the Austin test site with the 

distribution of all tests done in the Austin area. Figure 3 compares the model year 

distribution of the Austin sample with the model year distribution of all vehicles tested in 

Austin in June 2009. The study sample appears to have a higher percentage of older 

models than the overall Austin sample. This could be due to the sampling site being 

located in an area that has lower than average income levels. 

Figure 3 

Figure 4 compares the model year distribution of the Plano study sample with the model 

year distribution of all vehicles tested at the Plano station during the days that our tests 

were done. The two distributions agree well. 

21
Figure 4 

Figure 5 compares the model year distribution of the Chicago study sample with the 

model year distribution of all vehicles tested at the Chicago station (Addison) during the 

days that our tests were done. The two distributions agree extremely well. 

Figure 5 

Comparison of Study Sample with Vehicles Whose Owner Declined Participation 

As part of the vehicle procurement process, dKC maintained a log of vehicles whose 

owners declined the solicitation to participate in our test program. Overall, 73% of the 

22
motorists agreed to participate. Figures 6 to 8 show comparisons by model year of the 

study sample with non-participating vehicles. There do not appear to be significant 

differences between the two groups. 

Figure 6 

Figure 7 

23
Figure 8 

Table 9 presents the reasons why motorists did not participate. The most common 

reason was that they were in a rush. 

Table 9 – Reasons for Not Participating in the CRC Program 

Reason Austin Chicago Plano Grand Total

Couldn't speak English       1 1

Failed Inspection,

Rush       1 1

Not Interested 4 26 26 56

Not Owner    1    1

Rush 12 86 50 148

Skeptical    1 7 8

Other 1       1

Grand Total 18 114 87 219

3.2.2 OBDII Status 

The samples were compared with regard to faults identified by the OBDII system. We 

specifically investigated differences in Malfunction Indicator Light (MIL7

) commanded-on 

                                                           

24

7

 MIL is a term used for the light on the instrument panel, which notifies the vehicle operator of an 

emission related problem. The MIL is required to display the phrase “check engine” or “service 

engine soon” or the ISO engine symbol. The MIL is required to illuminate when a problem has been 

identified that could cause emissions to exceed a specific multiple of the standards the vehicle was 

certified to meet. 
25

rates and not ready rates8. Vehicles with monitors not ready may have had codes 

cleared prior to inspection in an attempt to mask a MIL-on situation9

. 

MIL Command Status 

Table 10 compares the percent of vehicles with MIL commanded on for E0 and E10 

areas. Vehicles that failed to communicate with the test system are excluded from this 

analysis. Figure 9 compares the percent of vehicles with MILs on in the CRC study 

sample with the percent of vehicles with MILs on in the sample area. Unlike Texas 

which tests all vehicles more than one year old, in Chicago the newest 4 years are 

exempted from testing. This explains why MIL command-on rates are higher in Chicago 

than in the two Texas sites. The MIL-command on rates for each site compare 

reasonably well with a sample of all vehicles tested in the area, as shown on Figure 9. 

Note that none of the MIL-command on cases was due to lean operation (as indicated 

by the DTC10 stored). 

Table 10 – MIL-On Rates in E0 vs E10 Samples 

MIL-On Rates: E10 vs. E0 Sample 

Ethanol Off On % 

E0 132 3 2.2% 

E10 391 13 3.2% 

Readiness Status 

Figure 10 compares the percent of vehicles with at least one monitor not ready. The 

CRC study sample sites are compared with each other and with a sample of tests in the 

area. The not ready rates for each site compare well with a sample of all vehicles tested 

in the area, as shown on Figure 10. 

                                                           

8

 OBDII systems have up to 11 diagnostic monitors, which run periodic tests on specific systems and 

components to ensure that they are performing within their prescribed range. OBDII systems must 

indicate whether or not the onboard diagnostic system has monitored each component. Components that 

have been diagnosed are termed “ready”, meaning they were tested by the OBDII system. 

9

 Readiness status for all non-continuous monitors sets to not ready when codes are cleared to extinguish 

an illuminated MIL. 

10 When a MIL is illuminated a diagnostic trouble codes (DTCs) should be stored. DTCs describe 

problems identified by the OBDII system.
Figure 9 

Figure 10 

3.2.3 Make 

Table 11 ranks the number of tests by manufacturer for the three sites. The Austin and 

Chicago sites appear to test more domestic models than the Plano site. 

26
27

Table 11 Ranking of Manufacturers by Site –Study Sample 

Make Austin Chicago Area Plano 

Ford 1 2 4

GM 2 1 3

Other Japanese 3 4 5

Honda 4 6 1

Chrysler 5 3 6

Toyota 6 5 2

German 7 7 8

Hyundai/Kia 8 9 7

Other European 9 8 9

3.2.4 Conclusions Regarding Representativeness of CRC Study Sample 

The distributions of model years and OBDII identified faults in the CRC study samples 

agree well with the distributions of model years and OBDII identified faults in all tests at 

the station or in the area. The distribution of model years for vehicles that were tested 

also agrees well with the distribution of model years for vehicles that were in the group 

that rejected the offer to participate. dKC concludes that the CRC study sample is 

representative of the overall vehicle population.

3.3 Long-Term Fuel Trim (LTFT) Trends 

A major focus of the CRC test program was on collecting data on long-term fuel trim 

(LTFT) for vehicles in E0 and E10 areas. 

3.3.1 What is Long-Term Fuel Trim? 

Fuel trim refers to adjustments being made dynamically to the fuel metering system 

(termed fuel table) to get the proper ratio of fuel to air. Short term fuel trim refers to 

adjustments being made in response to temporary conditions. Long term fuel trim 

(LTFT) is used to compensate for issues that seem to be present over a much longer 

period. Fuel trims are expressed in percentages; positive values indicate lean (add fuel) 

and negative values indicate rich (subtract fuel). Fuel trim banks refer to the cylinder 

banks in a V style engine. Cylinder #1 is always in bank 1. Fuel trim is generally 

calculated by using a wide set of data values, including front oxygen sensors, intake air 

temperature/pressure sensor, air mass sensor, engine (coolant) temp sensor, antiknock sensors, engine load, throttle position (and change in throttle position) sensor, 

and even battery voltage.

Example Trends for Individual Vehicles 

The test system recorded LTFT and other parameters on a second-by-second basis 

while the engine was off and for 5 to 10 minutes after the engine was started. Figures 
11 and 12 show two examples of LTFT trends before and after engine start-up. Figure 

11 shows trends for a four cylinder engine with only one bank of cylinders (B1). Figure 

12 shows trends for a V-6 so values for bank 1 (B1) and bank 2 (B2) are recorded. In 

both cases, LTFT increased after start-up. In the example shown in Figure 11, LTFT 

increased to a maximum value and then dropped slightly before the test ended. In the 

example shown on Figure 12, LTFT reached a maximum value about mid-way through 

the test and then stayed at this value for the remainder of the test. 

Figure 11 

Engine

Start

Max LTFT

28
Figure 12 

Max LTFT

Engine

Start

What Fuel Trim Parameters are of Interest: Max LTFT vs. Last LTFT 

We compiled summary statistics for each vehicle tested. As stated in Section 2, LTFT 

and other data parameters were collected for about 10 minutes while the vehicle soaked 

with the engine off and about 5 minutes after the engine was started. To facilitate an 

orderly analysis, the following parameters were binned11into positive and negative LTFT 

groups: 

• Min LTFT: The minimum LTFT value observed during the test 

• Max LTFT: The maximum LTFT value observed during the test 

• Last LTFT: The LTFT value at the end of the test 

Below we analyze these parameters to determine which parameter best represents the 

correct LTFT value for the vehicle tested. 

Figure 13 compares binned values of minimum, maximum and last LTFT values for the 

study sample. This figure charts the percentage of observations that fell into the bins 

based on what parameter was used to describe LTFT, i.e., minimum LTFT, maximum 

LTFT, or last LTFT. As Figure 13 shows, max LTFT trends are about the same as last 

                                                           

11 The bins are groups in 2% increments. Example values: <(13)=-14, >13=14, (11)-(13)=-12, 11-

13=12,...Note, <(13)=-14, >13=14 

29
LTFT trends for positive LTFT bins, i.e., the distributions of positive LTFT values are 

nearly identical for the max LTFT value and last LTFT values. Both values are much 

greater than min LTFT values. However, for negative LTFT values, min LTFT trends are 

similar to last LTFT trends; max LTFT trends show much lower incidence of negative 

LTFT values. From this analysis, we conclude that the last LTFT value recorded during 

the test is the best overall indicator of LTFT for the vehicle being tested. 

The summary trends shown in this section will be based on last LTFT values. 

Examination of false MIL illumination events with E15 and E20 (when the MIL comes on 

but nothing is wrong with the vehicle) will be based on max and last LTFT values. 

Examination of false positive MIL illumination events (when the MIL should come on but 

does not) will be based on min and last LTFT values.

Figure 13 

3.3.2 Overall LTFT Trends 

Figures 14 to 17 show overall trends in distributions of LTFT values by site. 95% 

confidence intervals are indicated on Figures 16 and 17. The last LTFT value is used for 

this analysis. As shown, E10 locations have higher LTFT values than the E0 location. 

Overall, as shown on Figure 17 average LTFT values in E10 areas are about 4 absolute 

percent higher than average LTFT values in E0 locations. Tables 12 and 13 shows the 

binned numbers of last LTFT values by site and fuel. 

30
Figure 14 

Figure 15 

31
Figure 16 

Figure 17 

Table 12 Test Counts by Last LTFT Value and Site 

Last LTFT Value

Site ‐14 ‐12 ‐10 ‐8 ‐6 ‐4 ‐2 0 2 4 6 8 10 12 14

Austin 4 0 8 13 17 22 13 32 10 7 1 5 1 1 1

Chicago Area 3 1 9 4 7 19 13 47 13 26 16 20 6 3 10

Plano 0 1 1 5 8 20 26 46 20 46 14 9 7 2 2

32
Table 13 Test Counts by Last LTFT Value and Fuel 

Last LTFT Value

Fuel ‐14 ‐12 ‐10 ‐8 ‐6 ‐4 ‐2 0 2 4 6 8 10 12 14

E0 4 0 8 13 17 22 13 32 10 7 1 5 1 1 1

E10 3 2 10 9 15 39 39 93 33 72 30 29 13 5 12

LTFT Trends By Odometer 

Table 14 provides a breakdown of the sample by odometer reading. Figures 18 and 19 

compare LTFT values by odometer in the E0 and E10 locations. Overall, there’s good 

agreement in trends for the less than 100,000 mile and greater than 100,000 mile 

groups. Figures 20 and 21 compare the effects of ethanol for the less than 100,000 mile 

and greater than 100,000 mile groups. The effects of ethanol appear to be similar for 

both groups. 

Table 14 – Test Counts by Odometer (Tests that Successfully Communicated) 

Odometer Group E0 Count E10 Count 

<100,000 miles 72 271 

>100,000 miles 57 130 

Odometer Not Avail. 6 3 

Figure 18 

33
Figure 19 

Figure 20 

34
Figure 21 

3.3.3 LTFT Trends By Ambient Temperature 

Table 15 presents a breakdown of the sample by ambient temperature. Figures 22 and 

23 compare LTFT values by ambient temperature in the E0 and E10 locations. Overall, 

there’s good agreement in trends for the less than 90 degree F and greater than 90 

degree F groups. Figures 24 and 25 compare the effects of ethanol for the less than 90 

degree F and greater than 90 degree F groups. The effects of ethanol appear to be 

similar for both groups. 

Table 15 – Test Counts by Ambient Temperature 

Ambient Temperature Group E0 Count E10 Count 

<90 deg F 95 330 

>90 deg F 40 74 

35
Figure 22 

Figure 23 

36
Figure 24 

Figure 25 

37
3.3.4 LTFT Trends By Model Year (Age) 

Figure 26 shows average LTFT values for E0 and E10 areas broken down by model 

year. All the averages for the E0 sample were negative, while all the averages for E10 

areas were positive. There does not appear to be a clear trend by model year. 

Figure 26 

3.3.5 LTFT Trends By Make 

Figure 27 compares the average increase in LTFT levels from E10 by original 

equipment manufacturer (OEM). Comparisons are shown for OEMs that had a minimum 

of 10 observations in E0 areas; 6 OEMs had enough observations for comparisons. The 

increase is defined as the average E10 level by OEM minus the average E0 level by 

OEM. The last and max LTFT were used to calculate the increase. As shown, there’s 

considerable variation in the calculated increase by OEM, although all OEMs show an 

increase in LTFT from E10 use. Figure 28 shows average last LTFT values for E0 and 

E10 with 95% confidence intervals. For 3 of the 6 OEMs evaluated, the error bars do 

not overlap. 

Figures 29 to 34 show the distributions of LTFT values (last LTFT) by OEM. All the 

OEMs show a shift in LTFT from E10. For some of OEMs, e.g. OEM5 and OEM7, the 

E10 distribution has a similar shape to the E0 distribution; it just shifted to the right. 

38
Figure 27 

Figure 28 

 

39
Figure 29 

Figure 30 

40
Figure 31 

Figure 32 

41
Figure 33 

Figure 34 

42
43

3.4 Projection of MIL Illumination Events 

Using data on ethanol effects by OEM, we projected the impact of using gasoline mixed 

with 15% and 20% ethanol on MIL illumination. As previously mentioned, we are 

concerned with two types of ethanol effects: 

1. A vehicle operating close to an OBD-II threshold level might exceed the MIL-on 

criterion when fueled with E15 or E20 when nothing is wrong with the vehicle. 

2. In the case of vehicles running too rich, ethanol-induced enleanment might move 

the vehicle back from beyond the OBD threshold and create a “false negative” 

situation where the MIL does not illuminate when it should. 

We took two general approaches to evaluate how increased ethanol use might affect 

MIL illumination: 

1. Each individual test was subject to hypothetical LTFT increases based on 

observed trends by OEM. The resultant LTFT values were subject to different 

MIL illumination criteria to determine the potential number of vehicles that would 

either falsely illuminate the MIL or fail to correctly illuminate the MIL. 

2. We assumed that LTFT was normally distributed. We then projected whether 

ethanol use would shift the tail of the distribution into a potential MIL illumination 

zone. 

3.4.1 Projections Based on Individual Test Results 

Methodology 

Following is the methodology used to project the possibility based on individual test 

results that vehicles fueled with E15 or higher blends would either falsely illuminate the 

MIL or fail to correctly illuminate the MIL: 

• The dataset was adjusted as follows: 

o All vehicles with MILs already on were removed. 

o The dataset was limited to OEMs that had both E0 and E10 observations. 

o The resultant dataset had 515 observations. 

• LTFT values (last and max) for E0 observations were converted to E10 values by 

adding the observed impact of E10 (by OEM) to the E0 LTFT value. 

• E15 projections were made by adding 50% of the observed impact of E10 to the 

E10 levels12. 

                                                            12Based on consultations with OEMs, the impact of ethanol was assumed to be proportional to 

ethanol content. Therefore, E15 is assumed to increase LTFT by 50% of the observed increase 

from E10. E20 is assumed to double the observed impact of E10. 
44

• E20 projections were made by adding 100% of the observed impact of E10 to the 

E10 levels. 

• The percent of vehicles exceeding specific LTFT illumination thresholds were 

calculated two ways: 

o A range of thresholds were applied to the complete dataset. 

o Manufacturer specific thresholds were applied to results for OEMs that 

provided thresholds. 

Reported LTFT Thresholds 

Four OEMs provided information on LTFT thresholds that would trigger MIL illumination. 

Two of the OEMs provided a range of LTFTs that would trigger MIL illumination. Two 

provided one value that would trigger MIL illumination. The minimum LTFT threshold 

was 17%; the maximum threshold was 30%. 

Percent Exceeding Hypothetical Thresholds 

We applied five different hypothetical thresholds to the LTFTs projected for E10, E15 

and E20: 17%, 20%, 23%, 25% and 30%. Table 16 shows the percent of vehicles 

exceeding the different LTFT thresholds. Table 16 is based on last and max LTFT. The 

projected percentages of vehicles that exceed thresholds are about the same for both 

LTFT parameters, last or max LTFT. None of the projected LTFTs exceeded the high 

value of 30%. When hypothetical thresholds of 17% to 25% are applied to last LTFT 

values, E15 is projected to increase MIL illumination rates by 0.39% to 0.77%; E20 is 

projected to increase MIL illumination rates by 0.78% to 2.13%13. When these same 

thresholds are applied to max LTFT values, E15 is projected to increase MIL 

illumination rates by 0.39% to 0.77%; E20 is projected to increase MIL illumination rates 

by 0.78% to 1.75%. Figure 35 charts the analysis results based on last LTFT values. 

Table 16 – Percent Exceeding Specific Positive LTFT Thresholds Based on Last 

and Max LTFT Value 

LTFT 

Threshold 

% Exceed LTFT 

Threshold E10 

(last/max) 

% Exceed LTFT 

Threshold E15 

(last/max) 

% Exceed LTFT 

Threshold E20 

(last/max) 

>17% 2.14%/2.72% 2.91%/3.11% 3.69%/4.08%

>20% 0.78%/0.97% 1.55%/1.94% 2.91%/2.72%

>23% 0.19%/0.19% 0.78%/0.58% 0.97%/0.97%

>25% 0.00%/0.00% 0.39%/0.39% 0.78%/0.78%

>30% 0.00%/0.00% 0.00%/0.00% 0.00%/0.00%

                                                           

13 The percent increases for E15 and E20 are based on the percent that exceed thresholds with E15 or E20 minus

the percent that exceed thresholds with E10.
Figure 35 

Percent Exceeding Manufacturer Specific Thresholds 

As mentioned, four OEMs provided information on LTFT thresholds. We applied OEM 

specific thresholds to the LTFT results for a specific OEM. Table 17 presents the results 

for different ethanol concentration scenarios. Figure 36 shows this information 

graphically. The low threshold represents the lowest threshold for MIL illumination for a 

specific OEM. The high threshold represents the highest threshold for MIL illumination 

for a specific OEM. Note that we did not have information on thresholds by model, so 

we cannot definitively determine if a vehicle would exceed the LTFT threshold and 

illuminate the MIL. Based on the difference between the percent of vehicles that exceed 

the low thresholds with E10 vs. E15, E15 has potential to increase MIL illumination rates 

by up to 1.0%. E20 has potential to increase MIL illumination rates by up to 1.6%. More 

detailed MIL illumination thresholds for different OEMs will help to better define the 

scope of this problem, but actual testing on E15 or E20 is needed to determine if in-use 

vehicles will experience false MIL illumination. 

Table 17 – Percent of Vehicles Projected Exceed Manufacturer’s Thresholds 

Based on Last and Max LTFT Value 

Thresholds 

% Exceed LTFT 

Threshold E10 

(last/max) 

% Exceed LTFT 

Threshold E15 

(last/max) 

% Exceed LTFT 

Threshold E20 

(last/max) 

Low 0.32%/0.32% 0.97%/1.29% 1.94%/1.94%

High 0.00%/0.00% 0.00%/0.00% 0.32%/0.32%

45
Figure 36 

Evaluation of False Negatives 

We also evaluated the potential for increased fractions of ethanol in gasoline to create a 

“false negative” situation where the MIL does not illuminate when it should be on. In this 

case we looked at negative LTFT thresholds of -17 and -20. No vehicles had LTFT 

values below -20 on E10. Table 18 shows the percent of vehicles that exceeded 

negative LTFT thresholds. There is potential for E15 or E20 to shift a vehicle out of MIL 

illumination conditions. There were no vehicles in the dataset that had MILs on due to 

rich LTFT values, so we cannot definitively evaluate the “false negative” case. 

Table 18 – Percent Exceeding Specific Negative LTFT Thresholds Based on Last 

and Min LTFT Value 

LTFT 

Threshold 

% Exceed LTFT 

Threshold E10 

(last/min) 

% Exceed LTFT 

Threshold E15 

(last/min 

% Exceed LTFT 

Threshold E20 

(last/min 

<-17% 0.19/0.39% 0.00/0.00% 0.00/0.00%

<-20% 0.00/0.00% 0.00/0.00% 0.00/0.00%

3.4.2 Projections Based on Statistical Trends by Manufacturer 

Methodology 

The possibility of exceeding positive LTFT MIL thresholds was also investigated using 

statistical projections of LTFT values, assuming LTFT is normally distributed. The 

example shown on Figure 37 illustrates how this analysis was performed. 

46
Figure 37 – Hypothetical Shift in LTFT from E15 and E20 

The following steps were performed to investigate the possibility that increased ethanol 

content in gasoline will lead to false MIL illumination: 

• The average and standard deviation of the last LTFT was calculated for 

combinations of OEM and fuel. 

• The increase in LTFT from E10 based on last LTFT was calculated by OEM. 

• E0 levels equal the observed average by OEM for the E0 sample. 

• E10 levels equal the observed average by OEM for the E10 sample. 

• E15 projections were made by adding 50% of the observed impact of E10 to the 

E10 levels. 

• E20 projections were made by adding 100% of the observed impact of E10 to the 

E10 levels. 

• The “tail” of the distribution was calculated by adding two and three standard 

deviations to the projected E15 and E20 values. 

Projected LTFT Levels for the Tails of the Distribution 

Table 19 shows the averages and standard deviations for the E0 and E10 samples 

broken down by OEM. Assuming that the standard deviation for E15 and E20 are the 

same as the standard deviation for E10, we projected the two and three standard 

deviation “tails” for E15 and E20. Figure 38 shows projected LTFT values for E15. 

Figure 39 shows projected LTFT values for E20. The region of possible MIL illumination 

is highlighted on the figures. Two standard deviations above the expected average 

represent 2.2% of the population, assuming a normal distribution. Three standard 

deviations represent 0.15% of the population. 

47
48

The two standard deviation tail for one OEM equals or exceeds 20% when fueled with 

E15 or E20. If you add three standard deviations to the expected average, the E15 tail 

for the overall sample is 21% and the E20 tail is 23%. Several OEMs turn MILs on when 

LTFTs are in this range. Although three standard deviations represent only 0.15% of the 

population, considering that there are over 50 million OBDII vehicles operating in the 

US, the number of vehicles impacted could be significant. 

Table 19 – Averages and Standard Deviations by Fuel and Original Equipment 

Manufacturer (OEM)

Fuel/OEM 

Average of Last 

LTFT B1 

Standard Deviation 

of Last LTFT B1 

E0 -2.50 5.38 

OEM1 -1.39 5.68 

OEM2 -0.38 4.41 

OEM4 -1.95 5.06 

OEM5 -6.15 6.38 

OEM7 -3.94 5.21 

OEM8 -2.03 5.29 

E10 1.54 5.81 

OEM1 2.83 5.44 

OEM2 1.56 5.37 

OEM4 0.62 7.24 

OEM5 0.44 4.47 

OEM7 1.18 4.86 

OEM8 3.74 6.65 
Figure 38 

49
Figure 39 

3.5 Analysis of Texas Inspection/Maintenance Data 

dKC requested and received data from the Texas Commission of Environmental Quality 

(TCEQ) on OBDII inspections conducted in June 2009 in the Austin and Dallas-Ft. 

Worth areas. The dataset had the following numbers of initial OBDII tests: 

• Austin: 45,150 initial tests 

• Dallas-Ft. Worth: 187,674 initial tests 

Based on fuel property information collected for the present study, dKC assumes that 

data from Austin represents E0 and data from Dallas-Ft. Worth represents E10. 

MIL-On Rates: E0 vs. E10 Areas 

Figure 40 summarizes overall MIL-On rates by model year for the two samples. Rates 

are slightly higher in the E0 area. This could be due to the fact that OBDII inspections 

commenced in Austin in 2005, while they have been doing them in the Dallas-Ft. Worth 

area since 2002. 

50
Figure 40 

Diagnostic Trouble Codes (DTCs) In E0 vs. E10 Areas 

During OBDII inspections in Texas and other states, diagnostic trouble codes (DTCs) 

are recorded. DTCs describe problems identified by the OBDII system. In most cases 

(99%), when the MIL is on a DTC will be stored. In cases when the MIL is off but a DTC 

is stored, the OBDII system is either awaiting further confirmation from the on-board 

computer that the MIL should be on, or the problem was not seen in three consecutive 

trips, so the on-board computer turned off the MIL. 

dKC identified DTCs that are related to enleanment (running too lean) or enrichment 

(running too rich). DTC related to enleanment are presented below: 

DTC Description 

P0171 System too Lean (Bank 1) 

P0174 System too Lean (Bank 2) 

DTC related to enrichment are presented below: 

DTC Description 

P0172 System too Rich (Bank 1) 

P0175 System too Rich (Bank 2) 

Table 20 shows the percent of vehicles that had DTCs related to either lean or rich 

operation. Results are broken down into E0 and E10 areas. As shown, there were about 

6% more vehicles with enleanment DTCs in the E10 area than in the E0 area. On the 

other hand, the percentage of vehicles with enrichment DTCs were about 60% lower in 

51
52

the E10 area than in the E0 area. In terms of ranking, P0171 was the 3rd most common 

DTC in the E10 area, while it was the 5th most common DTC in the E0 area. P0172 was 

the 15th most common DTC in the E0 area, while it was the 34th most common DTC in 

the E10 area. Clearly, ethanol reduces the percent of vehicles with enrichment related 

DTCs. 

Table 20 – Percent of Tests with DTCs Related to Enleanment (P0171/P0174) or 

Enrichment (P0172/P0175) 

Percent of Initial Tests with DTC 

Area Lean: P0171/P0174 Rich: P0172/P0175 

E0 0.432% 0.206% 

E10 0.459% 0.077% 

% Diff E10 6.2% -62.8% 

dKC investigated two models that had high LTFT values in E10 areas. Both models had 

0% incidence of P0171/P0174 DTCs in the E0 area, while in the E10 area, 0.6% to 2% 

of these models had P0171/P0174 DTCs.

Not Ready Rates 

Vehicles fail inspection if too many monitors are not ready. Figure 41 shows the percent 

of vehicles failing for readiness. Rates were similar for 2001 and newer models, but for 

the older models, not ready rates were higher for the E0 sample. Like MIL-on rates, this 

could be due to the fact that the program in Dallas Ft. Worth is more established than 

the program in Austin. 

Figure 42 shows not ready rates for key monitors. Not ready rates for the evap monitor 

are significantly higher in the E10 area. As shown on Figure 43, evap monitor not ready 

rates are consistently higher in the E10 area across a range of model years. Not ready 

rates for the catalyst monitor are slightly higher in the E10 area, while rates for other key 

monitors are about the same for both samples. Even though there were more vehicles 

in the Dallas Ft. Worth sample than in the Austin sample, the differences are statistically 

significant. It’s not clear why ethanol may cause more evap monitors to be not ready. 

Analysis of data from other I/M programs is needed to confirm that this issue is related 

to the use of E10. 
Figure 41 

Figure 42 

53
Figure 43 

54
55

                                                           

4.0 CONCLUSIONS 

Conclusions from this study are listed below: 

• Operation on 10% ethanol/gasoline blends (E10) increases LTFT over E0 levels 

for most vehicles. The sensitivity varies by original equipment manufacturer 

(OEM), but all OEMs show the trend.

• The tests conducted in this study provide evidence that operation on 15% or 

20% ethanol/gasoline blends (E15 or E20) may cause a subset of problem-free 

vehicles to illuminate their malfunction indicator light (MIL) due to excessively 

lean14 operation. The fraction depends on the assumed LTFT threshold15 and the 

fuel ethanol content and is roughly estimated to be of the order of a percent or 

so. A more precise estimate of this fraction cannot be made with the available 

data. 

• There is also evidence that operation on E15 and E20 may cause some vehicles 

that currently have illuminated MILs due to rich16 operation to appear to be 

problem free, but no vehicles with this type of illuminated MIL were detected in 

this program. 

• Additional study is needed to better quantify potential ethanol-related issues with 

OBD MIL. Vehicle testing on E15 or E20 is needed to confirm that false positive 

or negative MIL illumination will occur. Further analysis of MIL status from I&M 

data and more detailed MIL illumination thresholds for different OEMs will also 

help to better define the scope of this problem.

• Not ready rates17 for the evap monitor in Texas were higher in the E10 area than 

in the E0 area. More data would be required to determine if ethanol was affecting 

this parameter.

14 Lean: More air than required for optimum combustion. 

15 LTFT threshold: The LTFT value at which the OBD system illuminates the MIL. 16 Rich: More fuel than required for optimum combustion. 

17 OBDII systems have up to 11 diagnostic monitors, which run periodic tests on specific systems and 

components to ensure that they are performing within their prescribed range. OBDII systems must 

indicate whether or not the onboard diagnostic system has monitored each component. Components that 

have been diagnosed are termed “ready”, meaning they were tested by the OBDII system. 
56

Appendix A 

Handouts, Posters, Questionnaires and Examples of Pictures Taken During Test 
57

Appendix A-1 – Flyer/Poster At Test Stations 

NOTICE 

Would you like to be paid to participate in an 

environmental study? 

dKC is doing research for the Coordinating Research Council 

on the environmental impact of ethanol in gasoline. 

We‘d like to test your car after your vehicle emissions 

inspection: 

• The test takes 10-15 minutes. It will take place 

immediately after your vehicle inspection. 

• We will pay you $20. 

• Participation is not a requirement of the State inspection 

and results have no impact on the outcome of your 

State inspection. 

Thank you for your support! 

dKC -- de la Torre Klausmeier Consulting, Inc. 

Austin TX 

Coordinating Research Council 

Atlanta, GA
58

Appendix A-2 – Owner Questionnaire 

Participation in CRC Test Program 

I agree to accept compensation of $20 to allow de la Torre Klausmeier Consulting, 

Inc. (dKC) to test my vehicle after it undergoes its normal DPS inspection. 

Owner Signature ______________________________________ 

Print name ___________________________________________ 

Date ________________________________________________ 

Vehicle Plate__________________________________________ 

Year ________________________________________________ 

Make ________________________________________________ 

Model ________________________________________________ 

Pre-Test Questionnaire

How long have you owned this vehicle? _________________________________ 

Where do you normally fill up your 

vehicle?____________________________________________________________ 

Where was the last station that you filled up your 

vehicle?____________________________________________________________ 

The following items will be filled out by the tester: 

Odometer_____________________________________________ 

VIN__________________________________________________ 

Ambient Temperature__________________________________________ 
59

Appendix A-3 

Checklist for CRC E-90 Test Program 

Date 

Vehicle 

Previous Rejects Recorded 

Questionnaire Completed 

Check for FFV/Hybrid 

Vehicle warmed up (look at 

temperature gauge) 

Time engine turned off 

Data recorded correctly 

Underhood Label and VIN 

Pictures 

Ambient Temperature 

Hood Shut? 
Appendix A-4 – Example Picture of Emissions Label 

60
Appendix A-5– Example Picture of VIN 

61