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Research Papers: Fuel Combustion

Predicting the Engine Performance and Exhaust Emissions of a Diesel Engine Fueled With Hazelnut Oil Methyl Ester: The Performance Comparison of Response Surface Methodology and LSSVM

[+] Author and Article Information
Nadir Yilmaz

Department of Mechanical Engineering,
New Mexico Institute of Mining and Technology,
Socorro, NM 87801
e-mail: yilmaznadir@yahoo.com

Erol Ileri

Gulhane Military Academy,
Ankara 06010, Turkey

Alpaslan Atmanlı, M. Sureyya Kocak

Automotive Sciences Department,
Turkish Land Forces NCO Vocational College,
Balıkesir 10110, Turkey

A. Deniz Karaoglan

Department of Industrial Engineering,
Balikesir University,
Balikesir 10145, Turkey

Umut Okkan

Department of Civil Engineering,
Balikesir University,
Balikesir 10145, Turkey

1Corresponding author.

Contributed by the Internal Combustion Engine Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received August 3, 2015; final manuscript received December 1, 2015; published online April 5, 2016. Assoc. Editor: Stephen A. Ciatti.

J. Energy Resour. Technol 138(5), 052206 (Apr 05, 2016) (7 pages) Paper No: JERT-15-1298; doi: 10.1115/1.4032941 History: Received August 03, 2015; Revised December 01, 2015

An experimental investigation was conducted to evaluate the suitability of hazelnut oil methyl ester (HOME) for engine performance and exhaust emissions responses of a turbocharged direct injection (TDI) diesel engine. HOME was tested at full load with various engine speeds by changing fuel injection timing (12, 15, and 18 deg CA) in a TDI diesel engine. Response surface methodology (RSM) and least-squares support vector machine (LSSVM) were used for modeling the relations between the engine performance and exhaust emission parameters, which are the measured responses and factors such as fuel injection timing (t) and engine speed (n) parameters as the controllable input variables. For this purpose, RSM and LSSVM models from experimental results were constructed for each response, namely, brake power, brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), oxides of nitrogen (NOx), carbon dioxide (CO2), carbon monoxide (CO), and smoke opacity (N), which are affected by the factors t and n. The results of RSM and LSSVM were compared with the observed experimental results. These results showed that RSM and LSSVM were effective modeling methods with high accuracy for these types of cases. Also, the prediction performance of LSSVM was slightly better than that of RSM.

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Figures

Grahic Jump Location
Fig. 1

Experimental arrangement of the test equipment

Grahic Jump Location
Fig. 2

Brake power (a), BSFC (b), BTE (c), and EGT (d) surface plots of t and n for the calculated responses

Grahic Jump Location
Fig. 3

NOx (a), CO2 (b), CO (c), and N (d) surface plots of t and n for the calculated responses

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