Optimization of engine out responses with different biodiesel fuel blends for energy transition

Abstract

A dynamometer test was commonly used to find the optimum biodiesel blend ratio. Nonetheless, it has a significant disadvantage which was due to the high time consuming and financial commitment required to undertake this procedure. Only a few studies have used grey-Taguchi method (GTM) to optimize coconut oil-diesel fuel blends utilizing various parameters such as speed, load, and blend ratio. This study aims to find the optimum biodiesel blend ratio and other engine input parameters under different specified constraints using the GTM. A four-cylinder CI diesel engine was fuelled with different blends of coconut biodiesel and tested at various load and speed conditions. The Taguchi-Grey technique was used to carry out the optimization. The Taguchi approach with L16 orthogonal array was utilized to design the experiment, and the LTB and STB were employed to optimize 13 performance indices. In order to determine the optimal parameters, grey relational grade and S/N ratio were used. An ANOVA-based analysis was used to investigate the relationship between the three engine inputs and their responses. The optimization result shows that 30% blend ratio, 3850 rpm engine speed, and 25% engine load were the optimum results for the performance, emissions, and combustion of the CI engine. With the optimum condition, it improves the SOI-Main, turbocharges boost air pressure, O2, CO, and smoke by 6.18, 0.44, 1.15, 12.9 and 14.97 %, respectively, as compared to conventional diesel fuel. However, BSFC, BSEC, exhaust gas temperature, main injection duration, rail pressure, load demand, and NOx showed slightly degradation, 2.44, 0.84, 0.05, 0.81, 0.12, 1.64 and 11.93%, respectively. It was observed that the Taguchi-Grey approach has demonstrated to be highly effective in determining important parameters for multi-response variables.