Multi-Objective Optimization of Performance (BSFC) and Emission (NO _x ) Characteristics for CI Engine Operated on Mangifera Indica Methyl Ester Using Taguchi Grey Relational Analysis

Abstract: This paper presents an experimental study on engine performance & emission based on Taguchi method and grey relational analysis for optimization of six input parameters and their five levels. Combined effect of input parameters viz. compression ratio, injection pressure, injection-nozzle geometry, additive, fuel fraction and EGR in controlling BSFC and NO_xas the response variables in CI engine fueled with Mangifera Indica biodiesel blends was investigated. Number of experiments was reduced by employing Taguchi's L₂₅orthogonal array. The signal-to-noise (S/N) ratio and grey relational analysis techniques were used for data analysis. The combination of six input parameters was obtained for optimized engine performance and emission. The optimal combination of input parameters so obtained was further confirmed through experiments. The injection nozzle geometry was the most influencing parameter. The GRG improvement with mangifera indica Methyl Ester blend is 84.26% compared to GRG at initial settings of engine for diesel fuel