An Experimental and ANNs Study of the Effects of Safflower Oil Biodiesel on Engine Performance and Exhaust Emissions in a CI Engine

Abstract

In this study, the effects of diesel fuel-biodiesel (produced from safflower oil) blends on engine performance and exhaust emissions were investigated as experimentally in a single cylinder, fourcycle, normal aspirated diesel engine. In the results of tests, engine torque, engine power and specific fuel consumption as performance values of test fuels were commentated. Values of engine torque and engine power from biodiesel were lower than diesel fuel fuel as average 26% amount, and values of specific fuel consumption from biodiesel were higher than diesel fuel as average 41.5% amount. CO emission values of biodiesel decreased as average 74% amount according to diesel fuel. With using biodiesel, increased as average 2.45 fold amount for CO2 emissions, as average 1.3 fold amount for NO emissions, and decreased as average 87% amount for HC emissions with compared to diesel fuel. The obtained values were estimated for different inputs by using the ANNs model. The data obtained from the ANNs is very close to the experimental data.

Determining optimal artificial neural network training method in predicting the performance and emission parameters of a biodiesel-fueled diesel generator

“…Artificial neural network (ANN), which is based on the human neural system, have been successfully employed in many purposes [25,26]. In ANN, many neurons are connected with each other and an ANN is formed based on these connections.…”