Diesel Engine Performance and Emission Parameters Optimization Using Taguchi and Response Surface Methodology

Abstract

In present study, the ideal engine functioning condition for pollutants as well as functionality was determined using RSM.  The L16 Orthogonal Array experiment table was designed using Minitab 16 software with Taguchi's design of experiments methodology with Three variables—fuel type, engine speed, and engine load, each of which was varied across four distinct levels. After a comprehensive model examination, the R2 and modified R2 values are close, indicating a low risk of including unimportant components. The model found that an engine load of 6.85 kgf, an engine speed of 2000 rpm, and the 20% OPB blended fuel (OPB20) would optimise BTE, EE, BSFC, and NO, HC, and CO emissions. The model's maximum desirability was 86.79%, indicating that the predicted optimum answers and experimental responses were similar. The utilisation of RSM optimisation in conjunction with OPB fuel has the potential to enhance engine performance and mitigate emissions.