Using response surface methodology approach for optimizing performance and emission parameters of diesel engine powered with ternary blend of Solketal-biodiesel-diesel

This study focused on optimizing operation parameters of a diesel engine powered with ternary blends of oxygenated additive (Solketal)-biodiesel (originated from waste cooking oil)-diesel. Different ratios of the ternary blend were used to fuel the test engine at various compression ratios, fuel injection pressures and injection timings. The experimental data were used for RSM-based model prediction, establishing the relation function, and optimization. The RSM-based prognostic model was evaluated with statistical regression indices such as Pearson's coefficient (0.9695 – 0.9858) and coefficient of determination (0.9401 – 0.9717), showing highly robust predictive models. Besides, root mean square error (0.002 – 1.74) and mean absolute percentage deviation (0.3–0.9%) of the predictive model were low. The optimized values of CR, FIP, FIT, and Solketal content in the ternary blend was 17.8, 270 bar, 27^obTDC, and 9.5%, respectively. The model predicted and observed outputs were within 8%, indicating that the used model in this study is robust to predict output at this optimized condition with 29.4% of brake thermal efficiency, 0.396 kg/kWh brake-specific fuel consumption, 0.39% of carbon monoxide, 228 ppm of nitrogen oxides, and 52 ppm of unburnt hydrocarbon. Generally, using the Solketal oxygenated additive could improve engine performance and reduce harmful emissions.