Optimization of multi-response biodiesel fueled diesel engine parameters using Taguchi grey relational analysis and analytical hierarchy process

Compression ignition engines are currently optimized to run on petrodiesel fuel, but due to its increasing demand and depletion of fossil fuel reserves, alternative fuels must be utilized. In this article, an attempt was made to optimize the operating parameters of an unmodified compression ignition engine fueled with linseed methyl ester biodiesel. The input parameters were compression ratio, load, and fuel blend, while output responses included brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), and exhaust gas temperature (EGT), peak cylinder pressure (PCP), the rate of pressure rise (RPR), and net heat release rate (NHR), hydrocarbon (HC), carbon monoxide (CO), NOx, and Smoke. The aim was to determine the optimal combination of input parameters for minimal emissions and better performance and combustion parameters, with a minimum number of experiments. The study used Taguchi's L9 orthogonal array with a grey relational analysis approach (GRA) to obtain the optimum combination of input parameters. The study found that fuel blend B10, CR 18, and load 100% were the optimal input parameter combinations using the TGRA method. The S/N ratio analysis of grey relational grade (GRG) showed the optimal input factor levels to be fuel B10, CR 16, and load 100%, which was confirmed by the AHP method. The analysis of variance (ANOVA) showed that the load was the most influential factor, followed by CR and fuel. The confirmatory results showed an improvement of 56.1%, indicating that biodiesel can be efficiently used in an unmodified compression ignition engine by varying these influencing factors.