GREY-FUZZY TAGUCHI APPROACH FOR MULTI-OBJECTIVE OPTIMIZATION OF PERFORMANCE AND EMISSION PARAMETERS OF A SINGLE CYLINDER CRDI ENGINE COUPLED WITH EGR

摘要

The present study attempts to address the challenges of the multiobjective optimization problem of the BSFC-NOx-PM trade-off paradox of an existing diesel engine by harnessing the synergetic benefit of PM and BSFC reduction through CRDI operation and simultaneous NOx reduction by EGR application. Load, FIP and EGR were chosen as the input parameters while NOx, PM and BSFC were the response variables. In order to reduce the experimental effort, the Taguchi L-16 orthogonal array technique was employed to obtain the corresponding values of the response variables. The grey relational analysis coupled with fuzzy logic has been employed as the optimization routine. The optimal combination of the input parameters corresponding to the calibrated values of the response variables were obtained by employing the Grey-Fuzzy Grade and S-N ratio strategy as a performance index. The computed optimal combination so obtained were further validated through actual experimentation. EGR was found to be the most influencing factor in the present optimization endeavour. The study also established that the Grey-Fuzzy-Taguchi method was not only comparable but superior to the Grey-Taguchi method usually employed for such optimization studies.