# Ef

fe cts of Fiv e Gasoline Pr operties on Emissions fr om Ligh t - Duty Tier 2 Vehicles Ar on Butler

, James Wa rila, Rafal Sobotowski, Ca y Ya nca, P aul Machiele (USEP A/OTA Q/ ASD) George Hoffman (ISI, Inc.) CRC R eal World Confer ence April 10, 2013 1

# Ov er view of T

es ting (EP Act/V2/E - 89 da ta collection co - sponsor ed by EP A, DOE/NREL, CRC)

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# Back **ground**
• Re sponse to 2005 Energy P olicy Act dir ectiv e to develop an updated fuel effects model cov ering Tier 2 v ehicles • Fir stcomprehensive study to quantify impacts of fuel chang es on emissions since the Auto/Oil AQIRP pr ogr am of early 1990s • Emission lev els now an order of magnitude lower


### • Studied effects of fiv e fuel par ameter s individually and together as they inter act in in - use fuels • Ar omatics, ethanol, RVP , T50, T90 (dis tillation beha vior) • (Separ ate st udy on sulfur)

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# Program **Over vie**  **w** • Optimiz ed matrix of 27 test fuels (plus E85 on FFVs) • Te stfleet of 15 high - sales car s and light trucks fr om 2008 MY • Te st ing performed at 75  F over 3 - bag LA92 cy cle • 2+ r eplicates per v ehicle - fuel combina tion 

### • Measur ed g aseous pollutants and PM for all tests and bags • Sec/sec da ta for THC, CH 4, CO , CO 2 , NO x in all t es ts • Alcohol, carbon yl, and HC speciation for a subset of tests/bags 

### • Ve hicle handling and t es t pr ocedur es wer e highly specified t o bette r isolate fuel effects fr om test - to - te stv ariability and other artifacts that can er ode s tatistical power

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# Fu **el Matrix Over vie**  **w** • Pr operty rang es chosen t o allow models t o pr edict emissions for all in - use fuels found in U .S. • Multiple levels of par ameters t o c apture non - linear relationships between fuel pr operties and emissions • Wo rked with a fuel study design e xpert to optimiz e fuel matrix t o resolve interactions of in te rest while minimizing number of fuels (cost)

5 **Fuel Par**  **ameter Number of Levels**  **Target Values**  **to Be** **Tested** Ethanol (vol%) 4 0, 10, 15, 20 T50 (°F) 5 150, 16 5 (E20 only), 190, 220, 240 T90 (°F) 3 300, 325, 3 40 Aromatics (vol%) 2 15, 3 5 RVP (p si) 2 7, 106 **Fu el No**  **. T**  **50 ,**  **o F**  **T 90** **, o**  **F Et**  **OH, %**  **DV PE,**  **ps i**  **Ar o,**  **%** 1 150 300 10 10 15 2 240 340 0 10 15 3 220 300 10 7 15 4 220 340 10 10 15 5 240 300 0 7 35 6 190 340 10 7 15 7 190 300 0 7 15 8 220 300 0 10 15 9 190 340 0 10 35 10 220 340 10 7 35 11 190 300 10 10 35 12 150 340 10 10 35 13 220 340 0 7 35 14 190 340 0 7 15 15 190 300 0 10 35 16 220 300 10 7 35 20 165 300 20 7 15 21 165 300 20 7 35 22 165 300 20 10 15 23 165 340 20 7 15 24 165 340 20 10 15 25 165 340 20 10 35 26 165 340 15 10 35 27 220 340 15 7 15 28 220 300 15 7 35 30 150 325 10 10 35 31 165 325 20 7 35 

# Fu **el Matrix Summary** T50 2 ET OH 2 ET OH*ARO ET OH*T50 ET OH*T90 ET OH*RVP ET OH ARO T50 T90 RV P

# Te**st V**  **ehicle Flee t Over** **vie w**  • Fleet was siz ed by statistical power analysis consistent with appr oach used in Auto/Oil • Used tes t - to - test and v ehicle - by - fuel uncert ainties taken fr om other re cent datasets 

### • Aft er iter ation considering budget, speciation needs, etc., arriv ed at 15 vehicles • Chose high - sales engine families among MY2008 v ehicles • Cars and light trucks, target Bin 5 a ve ra ge with some Bin 4 and 8 • New vehicles were leased and dyno - aged to >4000 miles befor e start of pr ogr am

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# Te**st Flee**  **t Summary**

8 Make Brand Model Engine Size Ti er 2 Bin LEVII Std GM Chevrolet Cobalt 2.2L I4 5 NA GM Chevrolet Im pala FFV 3.5L

V 6 5 L2 GM Saturn Outlook 3.6L V 6 5 L2 GM Chevrolet Silverado FFV 5.3L V 8 5 NA To yota To yota Corolla 1.8L I4 5 U2 To yota To yota Cam ry 2.4L

I4 5 U2 To yota To yota Sienna 3.5L V 6 5 U2 Ford Ford Focus 2.0L I4 4 U2 Ford Ford Explorer 4.0L V 6 4 NA Ford Ford F150 FFV 5.4L V 8 8 NA Chrysler Dodge Caliber 2.4L I4 5 NA Chrysler Dodge Caravan FFV* 3.3L V 6 8 NA Chrysler Jeep Liberty 3.7L V 6 5 NA Honda Honda Civic 1.8L I4 5 U2 Honda Honda Odyssey 3.5L V 6 5 U2 Nissan Nissan Altima 2.5L I4 5 L2 *Caravan FFV was used only for E85 testing

# Re**sulting Dat ase**  **t**
• 15 v ehicles x 27 tes t fuels x 2+ r eplicates = 956 tests for ga seous emissions, PM, and FE • Sec/sec CAN/OBD data collected for 15 par ameter s during each test • Lots of detailed speciation data

– Alcohol and carbon yl speciation in bag 1 for 926 tests, bags 2 - 3 fo r subset of v ehicles (71 t es ts)

– Light h ydr ocarbons (C 2 - C 12 ) speciation for a subset of fuels and ve hicles (205 tests fo r bag 1)

– Rigor ous LOQ and QA pr ocedur es were applied to ensure high quality da ta 

### • Fuel pr operty data includes DHA for all fuels

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# Analy sis & R esults (EP A’ s work)

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# Analysis **Approach**
• Natur al log tr ansformation of emissions dat a

– St abiliz e v ariance, obtain linearity between dependent v ariable and fixed and r andom effects, normaliz e dis tribution of r esidual 

## • “St andar diz e” fuel pr operties

– Subtr act mean fr om each measur ement, divide by standard dev

– Puts all fiv e pr operties in “same space”



## • Analy ze d using mixed models by bag , pollut an t

– Fuel pr operties were fixed ef fe cts, v ehicles were random ef fe cts etOH etOH etOH etOH 

## s x x Z  

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# Modeling Process
• Ro und 1

– Iden tify outlier obser vat ions

– Re sult: A few PM points r emov ed 

## • Ro und 2

– Iden tify influen tial v ehicles

– Re sult: T

wo vehicles r emov ed for subsets of NOx, NMOG data 

## • Ro und 3

– Fit final models • Re duced models based on original design term lis t
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# What do the results show?
• Fuel e ffects persis t in new v ehicles • With this large dataset they ar e discernible even fo r hot running emissions • Man y tr ends similar t o those in dat asets for older ve hicles

– E.g., effect of ethanol and ar omatics on NOx, or ar omatics and T90 on PM 

## • Some ar e differ en t

– E.g., effect of R VP on THC

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# NO**x** Model coef

ficients

1415 

### ... Y ou ma y be tempted to take one of the coefficients and run with it ...


## ... but DON’T...16 

## ... Because all the coefficients need to w

or k together as a team ...

# An Ex ample for Bag 1 NOx Pulled fr om an AAMA Surv ey **Fuel Fuel** * EtOH 9.5 0 Aro 23.2 28.8 RVP 7.7 9.0 T50 213 212 T90 331 331

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###   

##    
... Z Z Z Z NO NO ln * 2 * 1 * x x 2 2 1 1 0 0 

                

## Model - o - grams 

# PM

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## Model - o - grams 

# THC

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## Model - o - grams 

# CO

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# Final Thoughts
• Ro bus t dataset for es timating emission impacts of curr en t and futur e in - use fuels nationwide

• Dev eloped a lot of bes t pr actices

• Lots of information her e that hasn’t been fully utiliz ed yet

• Mor e analyses to come

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### The s tudy r eports and data will be a va ilable

soon via the OTA Q w ebsite: htt p://www.epa.gov/otaq/fuelsmodel.htm

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# Fu**rther R eading**