Optimization and investigation the effects of using biodiesel-ethanol blends on the performance and emission characteristics of a diesel engine by genetic algorithm

Abstract

The purpose of this research is to investigate the combined effects of biodiesel-ethanol fuel blends on the performance and emission parameters of a diesel engine by the response surface methodology (RSM). The genetic algorithm was also applied for optimizations of the parameters. According to the results, the brake power and torque were decreased by approximately 30% with increasing the amount of ethanol in the fuel mixture. On the other hand, the BSFC of fuel blends enhanced around 16% with a higher percentage of ethanol as a result of the lower calorific value of ethanol compared with biodiesel. However, higher viscosity and density of biodiesel cause more fuel injection; so there is no notable difference in BSFC values for all blends. About emission parameters, the more percentage of ethanol resulted in less amount of smoke level and NOx emission around 38% and 17%, respectively due to the high level of oxygen in the molecular structure of ethanol. However, there is an approximately 44% decrease in CO emissions for a high percentage of biodiesel contained blends. According to the GA optimization, the results showed that the biodiesel percentage in the fuel mixture, RPM, and engine load were converged to 94.65%, 2800, and 65.75%, respectively as the optimal conditions. It is concluded that ethanol is more effective to improve the emission characteristics than that of the performance characteristics.