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SETSCI - Volume 3 (2018)
ISAS2018-Winter - 2nd International Symposium on Innovative Approaches in Scientific Studies, Samsun, Turkey, Nov 30, 2018

Engine performance and exhaust gas temperature modeling in a diesel engine with butanol-diesel fuel blends: Comparison of artificial neural networks and regression analysis (ISAS2018-Winter_29)
Samet Gürgen1*, İsmail Altın2
1Iskenderun Teknik University, Hatay, Turkey
2Karadeniz Teknik University, Trabzon, Turkey
* Corresponding author: sametgurgen66@gmail.com
Published Date: 2019-01-14   |   Page (s): 163-166   |    11     5

ABSTRACT In this study, the effect of using a mixture of butanol and diesel fuel in a small diesel engine on engine performance
and exhaust emissions is modeled. A comparison has been made with artificial neural networks, which is an up-to-date method,
and multiple linear regression methods. Motor performance parameters, torque, effective power and brake specific fuel
consumption are used as dependent variables. In addition, the exhaust gas temperature, which is an important parameter in the
engines, is taken as another dependent variable. In this study, independent variables are selected as butanol-diesel fuel mixture
ratio and engine speed. In order to compare two different modeling techniques, the mean squared error and mean absolute percent
error are calculated. As a result of this study, artificial neural networks give better results than multiple linear regression
techniques for four different dependent variables.  
KEYWORDS Diesel engine, butanol, engine performance, exhaust temperature, artificial neural network, multiple linear regression
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