Multi-response optimization to obtain better performance and emission level in a diesel engine fueled with water-biodiesel emulsion fuel and nanoadditive

Abstract

The present study aims to investigate the optimum condition of stationary diesel engine's operating parameters to obtain better performance and emission level, where the diesel engine is fueled with different concentrations of soybean biodiesel (SB), water, and alumina (Al) nanoadditive. Taguchi method coupled with gray relational analysis has been implemented in this study to obtain the optimum concentration of SB, water, and Al nanoparticle, and statistical analysis of variance (ANOVA) is applied to obtain the individual response of operating parameters on overall engine performance and emission level. Various concentration of SB (10%, 20%, and 30%), water (10%, 20%, and 30%), and Al nanoparticle (50 ppm, 100 ppm, and 150 ppm) are mixed with base diesel (BD) by mechanical agitation and followed by an ultra-sonication process. The fuel properties are measured based on EN590 standards, and the experiments are conducted in a single-cylinder, four-stroke, natural aspirated stationary diesel engine based on an L₉ orthogonal array fuel combination. From the obtained gray relational co-efficient (GRC) and signal-to-noise (S/N) ratio, the optimum concentration of SB, water, and nanoadditive are identified as 20%, 10%, and 100 ppm, respectively, and a confirmation experiment has also been carried out to confirm the improvements at optimum condition. The ANOVA results imply that water concentration (WC) has the maximum influence on overall diesel engine's performance and emission level followed by nanoparticle and SB concentrations. Overall, it can be concluded that the engine exhibits better performance and greener emissions at optimal condition.

https://ift.tt/2A8puEh