Application of fuzzy logic in internal combustion engines to predict the engine performance

Abstract

This paper describes an application of fuzzy logic principle for predicting the internal combustion engine performance, emission and combustion characteristics using fish oil biodiesel. Experimental investigations on a single cylinder, constant speed, direct injection diesel engine were carried out under variable load conditions. The performance, emission and combustion characteristics such as brake thermal efficiency, hydrocarbon, exhaust gas temperature, oxides of nitrogen (NOx), carbon monoxide, smoke, carbon dioxide, ignition delay, combustion delay and maximum rate of pressure rise were considered. Engine performance was measured using an exhaust gas analyser, smoke metre, piezoelectric pressure transducer and crank angle encoder for different fuel blends and engine load conditions. The obtained data were recorded for each experiment and associated data used to develop a multiple inputs and multiple outputs fuzzy logic model. The developed model produced idealised results with the correlation coefficients of 0.988–0.999 and root mean square error, and was found to be useful for predicting the engine performance characteristics with limited number of available data.