Modelling and optimisation of VCR diesel engine parameters fuelled with microalgae methyl-ester: a RSM-coupled Taguchi approach

Abstract

ABSTRACT Due to the high consumption of fossil fuels and their environmental effects, researchers are attempting to develop clean and environmentally sustainable alternative fuels. This study employs a hybrid statistical approach, combining the Taguchi approach and Response Surface Methodology (RSM), to optimise the input parameters of a diesel engine operating on microalgae methyl ester in order to increase engine performance. Through the execution of L16 pre-designed experiments, this work analyzes the significance of three key process parameters: engine load (25-50-75-100%), fuel injection pressure (200-210-220-230 bar), and microalgae biodiesel blends (B20-B40-B50-B100) with respect to brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), carbon dioxide (CO2), and nitrogen oxides (NOx). The response surface methodology was utilised to conduct an experimental investigation. At 71.52% of the engine load, a 204.23 bar injection pressure and a microalgae biodiesel blend of 20% (B20) were found to be the optimal input parameters. The optimum setting of the input parameters provides responses of 31.83% BTE, 278.658 g/kWh of BSFC, 872.053 g/kWh of CO2, and 1725.57 ppm volume of NOx, respectively. The experimental and predicted responses were compared, and it was found that the optimised values were within acceptable limits, with an error of less than 6%.