# 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 30022The 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/E 20 BLENDS ON

OBDII SYSTEMS – PILOT STUDY

Final Report

Prepared by:

Rob Klausmeier de la Torre Klausmeier Consulting, Inc.

March 9, 20102 

## TABLE OF CONTENTS

EXECUTIVE SU MMARY ................................................................................................ 4

1.0 INTROD UCTION.................................................................................................. 5

2.0 TEST PR OCEDURES. ......................................................................................... 8 2.1 Inspection/Maintenance (I/M) Sites Selected for Testing ..................... 8 2.2 Fuel Sa mples............................................................................................ 8 2.3 Site T est Plan ........................................................................................... 9

3.0 DATA ANAL YSIS .............................................................................................. 15 3.1 Data Co mpilation ................................................................................... 15 3.2 Representativeness of Test Samp les................................................... 18 3.3 Long-Term Fuel Trim (LTFT) Tr ends.................................................... 27 3.4 Projection of MIL Illumination Events.................................................. 43 3.5 Analysis of Texas Insp ection/Maintena nce Data ................................ 50

4.0 CONCLUS IONS................................................................................................. 553 

### 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 En vironmental Quality (TCEQ) 3. Applus Technologies, Inc. 4. Dekra Emission Test, Inc.
5. The Sticker Store This project would not have been possible wi thout their support. Finally, dKC would like to acknowledge the skill and determination of Graham Waak who colle cted most of the data and the CRC E-90 Committee for t heir 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 potent ial impact of 15% and 20% ethanol/gasoline blends (E15/E20) on the onboard diagnostic (OBD II) 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 m eet 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 vari es by original equipment manufacturer (OEM), but all OEMs show the trend.

• The tests conducted in this study prov ide evidence that operation on 15% or 20% ethanol/gasoline blends (E15 or E20) may cause a subset of problem-free vehicles to illuminate thei r malfunction indicator light (MIL) due to excessively lean 1 

### operation. The fraction depends on the assumed LTFT threshold 2 

### and the fuel ethanol content and is roughly estimat ed 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 rich 3 

### 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 quant ify 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. Fu rther 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 rates 4 

### for the evap monitor in Texas we re 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 whic h 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 ar e 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 encour agement of increased ethanol production and use, by 2013 the supply of ethanol will likely exce ed the amount required to blend into the national motor gasoline fuel poo l 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 potent ial impact of 15% and 20% ethanol/gasoline blends (E15/E20) on the onboard diagnostic (O BDII) system of in-use vehicles. Automobile manufacturers have expressed c oncern that vehicles running on E15 or E20 may experience more frequent malfunction i ndicator light (MIL) illuminations than vehicles running on E10 and below. They have identified the need for a study of how ethanol blends will impact OB DII system performance, par ticularly on high mileage vehicles.
How Ethanol Could Affect MIL Illumination Automobile manufacturers have expressed c oncerns over two types of events that could affect MIL illumination: 1. A vehicle operating clos e to an OBD-II threshold le vel when consuming E0 or E10 might exceed the MIL-on criterion when fueled wit h 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 enl eanment might move the vehicle back from beyond the OBD th reshold and create a “false negative” situation where the MIL does not illuminate when it should.
The OBDII threshold of most interest with respect to eth anol effects is long-term fuel trim (LTFT). Fuel trim refers to dynamic adjustments to algor ithms stored in the powertrain control module PCM) that determine the fuel inje ctor pulse for the proper fuel/ air ratio applicable to the engine operating conditions. Short term f uel trim refers to adjustments being made in response to tempor ary conditions. Long term fuel trim is used to compensate for issues that seem to be present over a much longer period 5



### . The picture below highlight s the concern over the 1 st 

### 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 th is 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 highlight s the concern over the 2 nd 

### problem – failure to properly illuminate the MIL when a vehicle is r unning too rich because ethanol-induced enleanment can move the vehicle ba ck 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 m anner and under the conditions of interest, a specific test protocol was followed. To facilitate data in terpretation, 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 pr ogram is presented in Section 3.0.

• Conclusions are presen ted in section 4.0.

78 

### 2.0 TEST PROCEDURES In this project, vehicles were test ed after they received their periodic inspection/maintenance (I/M) test. The text bel ow 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/maintenanc e (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 volu me 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 Chica go and Dallas-Ft. Worth to avoid overweighting the sample with test s conducted during hot weather conditions. Exhibits 1-3 show pictures of the testing si tes. 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 gaso line stations in the Au stin area and sent them to Southwest Research Institute for analysis. As shown on Ta ble 2, none of the samples had significant amounts of ethanol. Confidential information from an oil industry representative indi cated that the Dallas-Ft Worth and Chicago areas only dispense E10.
Table2—Results of Fuel Sa mpling 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 <0.19 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 em issions test. The following vehicles were not tested: i. Flexible Fuel Vehicles (FFVs) – FFVs were not included, because they are already designed for inte rmediate ethanol/gasoline blends. ii. Hybrids – Hybrids were not incl uded, because some of them turn the engine off at idle.10 

### b. Motorist Participation:
i. Centralized Lanes: In centralized test l anes, motorists driving 1996 and newer vehicles 6 

### were approached while they were waiting in line in their vehicles and were asked if they wanted to participate in the study. At the beginn ing 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. A fter the vehicle was tested, we repeated the proce ss 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 w hen they came into the office. The tester followed the same sele ction 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 st ation 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 s hown on Appendix A-3 to ensure that all required data recording and vehicle prep tasks were done. b. The motorist or state inspector wa s instructed to park the vehicle in a designated area. c. The motorist or state inspector wa s instructed to turn off the engine.
d. The tester took the followin g 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, t he 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 l onger 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 dK C project manager. After field tests were completed, dKC distributed individual test results to the appropr iate 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)

Paramete r Exam p le Value
Time 02:28:11
Calculated Load ( % ) [ 0 - 100 ] 14
Coolant Tem p erature ( F ) [ -40 - 419 ] 194
Short Term FT B1 ( % ) [ -100.00 - 99.22 ] -0.78
Lon g Term FT B1 ( % ) [ -100.00 - 99.22 ] -2.34
En g ine RPM ( r/min ) [ 0 - 9000 ] 660
Vehicle S p eed ( MPH ) [ 0 - 158 ] 0
I g n. Timin g Adv. C1 ( de g) [ -64.0 - 63.5 ] 13.5
Intake Air Tem p

. ( F ) [ -40 - 419 ] 124
MAF Air Flow Rate ( lb/min ) [ 0.00 - 86.70 ] 0.28
Abs. Throttle Pos. ( % ) [ 0 - 100 ] 15
B1S2 O2 Volta g e ( 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. Wo rth (Plano) Texas Site

1415 

### 3.0 DATA ANALYSIS 3.1 Data Compilation Prior to analyzing results, dKC developed spr eadsheets 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 categoriz ed the following parameters:

• Assumed Ethanol Content (E0 or E10)

• Odometer (<100,000 m iles, >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 116 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 participat ion in the study. Data on this spreadsheet is presented on Table 4.
Table 4 – Data Recorded on Vehicles W hose 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 wit h 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 manufacture r, 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 re sults 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 Ra tes 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 in itiated data logging while the vehicle was in the key-on engine-off position. When the engine was start ed, 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 th e 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 t he first week of testing we started to record additional data, including the following:

• Engine Family (f rom Emissions Label)

• Evap Family (from Emissions Label)

• Ambient Temperature We used ambient temperature to group tests into two cat egories: < 90 deg F, > 90 deg F. The maximum temperature dur ing the first week of testi ng was less than 90 deg F, so we grouped all the test result s 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 o dometers, so we were not ab le 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 te sted 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 si te. Figure 2 compares the distribution of model years for E0 and E10 samples. The odd even variation for the Chicago sample reflects t he fact that Chicago’s progr am is biennial and more oddmodel year vehicles are tested in odd year s, and vice versa. Overall as shown on Figure 2, there is good agreement between the E0 and E10 samples. Figure 1

Figure 2

1920 

### Table 7 shows a tabular breakdown of test counts by model year for E0 and E10 samples. Table 8 shows a breakdown of test c ounts by model year for the three sites.
Table 7 -- Test Vehicle Count s 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 Vehicl e 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 compar es the model year distribution of the Austin samp le 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 lo wer 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 vehicl es 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 distribut ion of the Chicago study sample with the model year distribution of all vehicles test ed at the Chicago stati on (Addison) during the days that our tests were done. The tw o distributions agree extremely well.

Figure 5

Comparison of Study Sample with Vehicl es 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 pr ogram. 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 vehicl es. 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 motorist s 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 f aults identified by the OBDII system. We specifically investigated differences in Malfunction Indicator Light (MIL 7 

### ) commanded-on

24 7 MIL is a term used for the light on the instrum ent panel, which notifies t he 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 rates 8 

### . Vehicles with monitors not ready may have had codes cleared prior to inspection in an a ttempt to mask a MIL-on situation 9



### . MIL Command Status Table 10 compares the percent of vehi cles with MIL commanded on for E0 and E10 areas. Vehicles that failed to communicate with the test system ar e 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 wh y 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 DTC 10 

### 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 compar e 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 ar e 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 te sts by manufacturer for the three sites. The Austin and Chicago sites appear to test more domestic models than the Plano site.

2627 

### 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 year s and OBDII identified faults in all tests at the station or in the area. T he distribution of model years fo r 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. dK C concludes that the CRC study sample is representative of the ov erall vehicle population. 3.3 Long-Term Fuel Trim (LTFT) Trends A major focus of the CRC test program wa s on collecting data on l ong-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 pr oper ratio of fuel to air. S hort term fuel trim refers to adjustments being made in response to tem porary 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 expre ssed in percentages; positive val ues indicate lean (add fuel) and negative values indicate rich (subtract f uel). Fuel trim banks refer to the cylinder banks in a V style engine. Cylinder #1 is a lways 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 positio n (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 minute s 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 sl ightly 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 val ue 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 vehi cle 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 t he engine was started. To facilitate an orderly analysis, the follo wing parameters were binned 11 

### into 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 param eters to determine which param eter best represents the correct LTFT value for the vehicle tested. Figure 13 compares binned values of minimu m, maximum and last LTFT values for the study sample. This figure charts the percent age of observations that fell into the bins based on what parameter was used to descr ibe 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. Exampl e 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 la st LTFT values. Both values are much greater than min LTFT values. However, fo r 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 se ction will be based on last LTFT values. Examination of false MIL illumination ev ents with E15 and E20 (when the MIL comes on but nothing is wrong with t he 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 samp le 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 effect s 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 temperatur e in the E0 and E10 locations. Overall, there’s good agreement in trends for t he less than 90 degree F and greater than 90 degree F groups. Figures 24 and 25 compare the e ffects 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 we re 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 incr ease by OEM, although all OEMs show an increase in LTFT from E10 us e. Figure 28 shows average la st LTFT values for E0 and E10 with 95% confidence intervals. For 3 of the 6 OEMs evaluat ed, 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

4243 

### 3.4 Projection of MIL Illumination Events Using data on ethanol effects by OEM, we projected the im pact 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 clos e to an OBD-II threshold le vel 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 enl eanment might move the vehicle back from beyond the OBD th reshold and create a “false negative” situation where the MIL does not illuminate when it should. We took two general approaches to evaluat e 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 di stribution 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 t hat had both E0 and E10 observations.

o The resultant dataset had 515 observations.

• LTFT values (last and max) for E0 observa tions 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 levels 12



### .

12 Based on consultations with OEMs, the impact of ethanol was assumed to be proportional to ethanol content. Therefore, E15 is assumed to in crease 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 appl ied to the complete dataset.

o Manufacturer specific thresholds we re applied to results for OEMs that provided thresholds. Reported LTFT Thresholds Four OEMs provided informati on on LTFT thresholds that would trigger MIL illumination. Two of the OEMs provided a r ange of LTFTs that would tr igger MIL illumination. Two provided one value that would trigger MI L illumination. The minimum LTFT threshold was 17%; the maximum threshold was 30%. Percent Exceeding Hypot hetical Thresholds We applied five different hypothetical thresh olds 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. Tabl e 16 is based on last and max LTFT. The projected percentages of vehicles that ex ceed 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 illu mination rates by 0.39% to 0.77%; E20 is projected to increase MIL illumi nation 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 Po sitive 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 Manufactur er Specific Thresholds As mentioned, four OEMs provided informa tion 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 scenar ios. Figure 36 shows this information graphically. The low threshold represents the lowest threshold for MIL illumination for a specific OEM. The high threshold repres ents 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 v ehicle 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 diffe rent 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 Project ed 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 fr actions 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 Stat istical 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 Shi ft in LTFT from E15 and E20

The following steps were performed to investi gate 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 bas ed on last LTFT was calculated by OEM.

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

• E10 levels equal the observed av erage 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 dev iations 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 E 20. The region of possible MIL illumination is highlighted on the figures. Two standard deviations above the expected average represent 2.2% of the popul ation, assuming a normal distribution. Three standard deviations represent 0.15% of the population.
4748 

### The two standard deviation tail for one OEM equals or exceeds 20% when fueled with E15 or E20. If you add three standard devia tions 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 stan dard deviations represent only 0.15% of the population, considering that t here are over 50 million OBDII vehicles operating in the US, the number of vehicles impacted could be significant.

Table 19 – Averages and Standard Deviat ions 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 Te xas Commission of Environmental Quality (TCEQ) on OBDII inspections conducted in June 2009 in the Austin and Dallas-Ft. Worth areas. The dataset had the followi ng 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 identif ied 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 awai ting 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 comput er 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 t he E10 area than in the E0 area. On the other hand, the percentage of vehicles with enrichment DTCs were about 60% lower in

5152 

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

### most common DTC in the E10 area, while it was the 5 th 

### most common DTC in the E0 area. P0172 was the 15 th 

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

### most common DTC in the E10 area. Clearly, ethanol reduces the per cent of vehicles wit h 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 monito rs are not ready. Figure 41 shows the percent of vehicles failing for readiness. Rates we re similar for 2001 and newer models, but for the older models, not ready rate s were higher for the E0 sample . Like MIL-on rates, this could be due to the fact that the program in Dallas Ft. Wo rth is more established than the program in Austin. Figure 42 shows not ready rates for key moni tors. 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 ar ea across a range of model years. Not ready rates for the catalyst monitor are slightly hig her in the E10 area, while rates for other key monitors are about the same for both samp les. Even though there were more vehicles in the Dallas Ft. Worth sample than in the Au stin sample, the differences are statistically significant. It’s not clear wh y 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

5455 

### 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 vari es by original equipment manufacturer (OEM), but all OEMs show the trend.

• The tests conducted in this study prov ide evidence that operation on 15% or 20% ethanol/gasoline blends (E15 or E20) may cause a subset of problem-free vehicles to illuminate thei r malfunction indicator light (MIL) due to excessively lean 14 

### operation. The fraction depends on the assumed LTFT threshold 15 

### and the fuel ethanol content and is roughly estimat ed 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 rich 16 

### 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 quant ify 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. Fu rther 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 rates 17 

### for the evap monitor in Texas we re higher in the E10 area than in the E0 area. More data would be r equired to determine if ethanol was affecting this parameter.

14 Lean: More air than required for optimum combustion.
15 LTFT threshold: The LTFT value at whic h 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 ar e 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 Exam ples of Pictures Taken During Test57 

### Appendix A-1 – Flyer/Post er 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, GA58 

### Appendix A-2 – Owner Questionnaire

Participation in CRC Test Program
I agree to accept compensation of $20 to allo w 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 stati on 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 Pict ure of Emissions Label

60

### Appendix A-5– Exampl e Picture of VIN

61