Prediction-Optimization of the Effects of Di-Tert Butyl Peroxide-Biodiesel Blends on Engine Performance and Emissions Using Multi-Objective Response Surface Methodology

Abstract

Abstract Alternative fuels, such as biodiesel, can be used in place of fossil fuels, although they have a greater viscosity and a longer igniting delay. To compensate for these limitations, several additives are added to biodiesel. The cetane improver di-tert butyl peroxide (DTBP) was investigated as an additive in this work. DTBP was shown to influence the combustion and emission properties of waste cooking oil biodiesel-diesel blends. The multi-objective response surface technique (MORSM) with Box-Behnken design was used to decrease the number of trials to conserve precious resources such as human effort, time, and money. Theil's uncertainty for the model's predictive capabilities (Theil's U2) was less than 0.1189, demonstrating its robustness. Nash-Sutcliffe efficiency was excellent (0.9885–0.9995), with a mean absolute percentage error of less than 1.32%. The engine operating parameters that were optimized were 71.64% engine load, 4964 ppm DTBP additive, and 24.98-deg advance ignition timing. The MORSM-based proposed technique's reliability and robustness validate the usage of DTBP with biodiesel blends, model prediction, and optimization.