Multi-objective Performance Optimization of Compression Ignition Engine Operated on Mangifera Indica Biodiesel by Applying Taguchi Grey Relational Analysis

Abstract

The experimental study has been carried out on compressed ignition engine using Mangifera indica biodiesel for performance optimization using Taguchi method and grey relational analysis. This paper presents combined effect of six input parameters viz. compression ratio, fuel injection pressure, injection-nozzle geometry, additive, fuel fraction and exhaust gas recirculation in controlling seven important output variables viz. brake specific fuel consumption, brake thermal efficiency, carbon monoxide (CO), unburn-hydrocarbons (HC), carbon dioxide (CO2), oxides of nitrogen (NOx) and Smoke. Five levels were selected to each input parameter and unequal weightage to each output variable. Taguchi’s L 25 orthogonal array has been applied for reducing number of experiments. The data obtained from the experiments has been analyzed using signal-to-noise ratio and grey relational analysis to obtain optimum combination of six input parameters. The injection nozzle geometry was the most influencing parameter whose contribution is 68.73 %. The results of the analysis were further confirmed through experiments. The experimental confirmation test reveals that Taguchi grey relational analysis technique is suitable for multi-objective optimization problem on engine performance and emission. The deviation in predicted value of grey relational grade (GRG) is only 0.0189, which is 2.6 % of the experimental value. Besides, GRG improvement with Mangifera indica biodiesel blend is 0.286 (68.3 %) compared to GRG at initial settings of engine for diesel fuel. Mangifera Indica Biodiesel blend can be used in existing diesel engine, with minor modifications.