Predictive modeling and optimization of a waste cooking oil biodiesel/diesel powered CI engine: an RSM approach with central composite design

Due to the restrictions of the diesel engine emissions and the massive demand of energy, the fossil diesel fuel has been consumed quickly and the resources cannot suffice the demand. Alternative fuels that include bio alcohols, hydrogen and biodiesel can make up the diesel fuel depletion. Biodiesel is convenient for diesel engine operation due to its properties like fossil diesel properties. Response surface methodology is a statistical approach for responses prediction and optimization using definite number of experiments to provide time and cost. This study aims to predict and optimize the performance and emission attributes; of diesel engine has single cylinder and operates at 1400 rpm constant speed fuelled with pure diesel fuel or diesel fuel blended with waste cooked oil (WCO) biodiesel at different blending ratio by using response surface methodology (RSM). The influences of the independent variables that are WCO biodiesel blend percentages and the diesel engine load values on the responses that are predicted and optimized. The WCO biodiesel/ diesel fuel blend percentages are pure diesel fuel without biodiesel (B0), 40% WCO biodiesel with 60% diesel fuel (B40) and 80% WCO biodiesel with 20% diesel fuel (B80). The experiments are performed using diesel engine runs at 1400 rpm constant speed, at varying diesel engine loads are zero, 4 and 8 kW. The design of experiments (DOE) is attempted using central composite design (CCD). The RSM model is a nonlinear model developed according to the independent variables and the responses. The homogeneity between the independent variables is studied to predict and optimize their influences on the diesel engine performance and emission attributes. The RSM model is validated according to the coefficients of regression are R², R² adjusted and the R² predicted that prove the satisfaction of the results. From the experiments it is observed that diesel engine performance and emissions attributes are enhanced by increasing the diesel engine load value and increasing the percentage of WCO biodiesel blending ratio compared to pure diesel only like NO_x emissions which reduced from 1200 ppm to 900 ppm at the same engine load due to the reduced combustion temperatures using WCO biodiesel. According to the response optimizer tool, the optimal responses are 17.11% for the BTE, 658.9 ppm for the NO_x emissions and 1.93% for CO₂ emission at independent variables are 2.6667 kW diesel engine load and 100% pure diesel fuel.