Title: Taguchi based grey relational analysis for multi response optimisation of diesel engine performance and emission parameters

Authors: Mohd Muqeem; Ahmad F. Sherwani; Mukhtar Ahmad; Zahid A. Khan

Addresses: School of Engineering and Technology, Department of Mechanical Engineering, IFTM University, Moradabad, 244001, India ' Faculty of Engineering and Technology, Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, 110025, India ' Faculty of Engineering and Technology, Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, 110025, India ' Faculty of Engineering and Technology, Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, 110025, India

Abstract: The aim of this paper is to optimise the input parameters of a diesel engine which results in optimum performance and emission. Four input parameters viz., compression ratio, fuel injection timing, air temperature and air pressure were considered in this study. Four response variables i.e., brake thermal efficiency, brake specific fuel consumption, hydrocarbon emission and smoke opacity were measured. Twenty five experiments as per Taguchi L25 orthogonal array were performed and experimental data was analysed using grey relational analysis (GRA) to accomplish multi response optimisation. Regression analysis was done to determine the experimental value of the grey relational grade (GRG) at optimum setting of the input parameters. In order to validate the experimental results, the experimental value of the GRG was compared with the predicted value and the comparison revealed good relation between the predicted and experimental values of the GRG at optimum combination of the input parameters.

Keywords: brake specific fuel consumption; brake thermal efficiency; Taguchi approach; GRA; grey relational analysis; hydrocarbon emission and smoke opacity.

DOI: 10.1504/IJHVS.2020.109287

International Journal of Heavy Vehicle Systems, 2020 Vol.27 No.4, pp.441 - 460

Received: 16 Oct 2017
Accepted: 01 Dec 2017
Published online: 03 Sep 2020 *

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