Use of response surface methodology approach for development of sustainable Jojoba biodiesel diesel blend with CuO nanoparticles for four stroke diesel engine

This study focuses primarily on the optimization of performance parameters, namely Brake thermal efficiency (BTE), Brake power (BP) and emission characteristics, namely Hydrocarbon (HC), carbon monoxide (CO) and oxides of nitrogen (NOX) emissions of a diesel engine fuelled with jojoba biodiesel-diesel blend with copper oxide (CuO) nanoparticles dispersed into it with different concentrations of 25, 50, 75 and 100 ppm. Variables such as blend (%), nanoparticles concentration (ppm), fuel injection pressure (bar) and Load (kg) are considered as input parameters. A series of experiments are designed under the central composite rotatable design (CCRD) approach considering 4 input factors each with 5 levels. A nonlinear RSM model is developed between the response and input variables based on the interaction plots. The model is validated by regression coefficient of R2, Adj. R2 and Pred. R2 which shows satisfactory results. Based on the desirability approach the model retrieve the best combination of input factors as 7.45 kg engine load, 16.76 % mixing of jojoba biodiesel with diesel, 209.89 bar fuel injection pressure, and CuO nanoparticles concentration of 76.76 ppm. After RSM optimization, target values of engine responses (BTE, BP, CO, HC, and NOx) are 27.18 %, 2.5582 kW, 0.1981 % volume, 24.5720 ppm, and 710.9470 ppm, respectively. When the results of the optimization process were compared to the experimental results, the deviations were found to be within the acceptable range of errors which establish the robustness of RSM model.