Multi-response optimization to improve the performance and emissions level of a diesel engine fueled with ZnO incorporated water emulsified soybean biodiesel/diesel fuel blends

The present work aims to select the optimal operating condition to improve the performance and emissions level of a diesel engine running with ZnO incorporated water emulsified SB blended diesel fuel based on Taguchi-grey relational based multi-response optimization tool. SB-water emulsion fuels were prepared and stabilized using sorbitan monolaurate surfactant through mechanical agitation and then ultra-sonication processes was followed to incorporate the nanoparticle. Experiments were conducted in a single cylinder, natural aspirated, four-stroke diesel engine with an eddy current dynamometer at full load condition based on an L-16 orthogonal array. The optimal level of operating parameters was determined based on S/N ratio and GRC and verified through a confirmation experiment. To measure the significance of the individual operating parameters on overall engine performance, a statistical analysis of variance was applied. The results of this study reveal that the performance and emissions characteristics of ZnO incorporated water emulsified SB blended diesel fuel engine has efficiently improved at the optimal parametric setting.