Integration of evaluation distance from average solution approach with information entropy weight for diesel engine parameter optimization

Abstract

This research depicts the utilization of a hybrid Multi Criteria Decision Making (MCDM) method for the determination of the best collection of operative parameters of a diesel engine. Nonetheless, selecting the best collection of operative parameters depends on both performance and emission properties that consist of various qualitative and quantitative parameters. The hybrid approach employs information entropy weight (IEW) and The Evaluation Based on Distance from Average Solution (EDAS) is proposed to rank available operating points for choosing the optimal combination of operating parameters of a diesel engine. Firstly, the strength of IWE is used to compute the relative weights of parameters. Then, EDAS technique is used to evaluate the alternatives ranking. The optimal values of performance and emission parameters: BP, SFC, Mech. Eff., BTE, CO, HC, CO2 and NOX emissions are 2.39kW, 0.23(kg/kwh), 52.51%, 36.72%, 0.04%, 43 ppm, 2.8% and 304 ppm, respectively, at load, torque and fuel blend of 11kg, 15.22Nm and B30, respectively. The results obtained by using the proposed integrated approach are validated by five various MCDM techniques. Namely, TOPSIS (Technique for Order Preference by Similarity Ideal Solution), WASPAS (Weighted Aggregated Sum Product Assessment), MOORA (Taguchi-based Multi-Objective Optimization by Ratio Analysis), WPAS (Weighted Product Assessment) and VIKOR (VIsekriterijumsko KOmpromisno Rangiranje) methods. The results indicate that the proposed integrated approach is capable of accurately ranking the operating points for diesel engine and the results well consistent with the other techniques. The proposed approach is clear in ideas and easy in computation, and calculation results are realistic as well.