Multiple objective optimization of a diesel engine fueled with Karanja biodiesel using response surface methodology

Abstract

This study optimizes the fuel quality of a diesel fuel while using biodiesel blends as fuel. Using the response surface Design of Experiments and Taguchi approach, the effects of load, compression ratio, and mixture on thermal efficiency (BTE) and nitrogen oxides (NOx) were statistically investigated. All input parameter is examined. at four specific levels. The findings shows that the highest values for BTE and NOx were discovered when the load was at its highest level, while the optimum values for the other two input parameters were obtained at various levels. As an outcome, the response surface technique is utilized in addition to the Taguchi method to reduce variance. In this study, engine performance is optimised for Kusum Oil in terms of thermal efficiency (BTE) and nitrogen oxides (NOx) Using Taguchi's method, an optimised dataset of the input parameters, such as Engine Load (percent), Blend (percent), and Fuel CR, is generated, which is then input into the prediction methods, such as response surface methodology and multiple regressions. Based on the evidence collected, these approaches are also evaluated in terms of accuracy.Mathematical Regression model created using RSM-based design of experiments. Effects of operational conditions on CI engine emissions and performance the fuel for the analysis was biodiesel blends. RSM's desirability technique is used to optimise input parameters. Optimal process Engine Load (%) 100, Blend (%) 20 and CR18 with their proper effects parameters obtained are BTE (%) 27.3264, NOx (ppm). = 550.5.