Development of fuzzy logic model to predict the engine performance of fish oil biodiesel with diethyl ether

Abstract

Multiple Inputs and Multiple Outputs (MIMO) fuzzy logic model is developed to predict the engine performance of fish oil biodiesel blended with diethyl ether. Engine performance and emission characteristics such as brake thermal efficiency, hydrocarbon, exhaust gas temperature, oxides of nitrogen (NO _x), carbon monoxide, Smoke and carbon dioxide were considered. Experimental investigations on single-cylinder constant-speed direct-injection diesel engine are carried out under variable load conditions. The performance and emission characteristics are measured using an exhaust gas analyser, smoke meter, piezoelectric pressure transducer and crank angle encoder for different fuel blends and engine load conditions. In this model, triangular membership function is used to predict the performance. Computational results clearly demonstrated that the proposed fuzzy models produced less deviations and exhibited higher predictive accuracy with acceptable determination correlation coefficients of 0.96–0.99 with experimental values. The developed model produces the idealised results and has been found to be useful for predicting the engine performance and emission characteristics with limited number of available data.

Keywords:

• fuzzy logic
• diesel engine
• fish oil
• diethyl ether
• performance and emission