Title: Minimisation of fuel cell electric vehicle cost using Cauchy particles swarm optimisation

Authors: Intissar Darwich; Islem Lachhab; Lotfi Krichen

Addresses: Electrical Systems and Renewable Energies Laboratory (LSEER), National Engineering School of Sfax, BP 1173, 3038 Sfax, Tunisia ' Electrical Systems and Renewable Energies Laboratory (LSEER), National Engineering School of Sfax, BP 1173, 3038 Sfax, Tunisia ' Electrical Systems and Renewable Energies Laboratory (LSEER), National Engineering School of Sfax, BP 1173, 3038 Sfax, Tunisia

Abstract: In this paper, enhanced particle swarm optimisation algorithm is suggested that uses mutated inertia weight which is based on Cauchy distribution in order to optimise fuel cell/ultra-capacitor electrical vehicle cost. This approach is dedicated to identify the optimal number of units of each energy source according to the vehicle performances. The proposed algorithm is based on Cauchy operator which substitutes the random function in classic PSO. Moreover, this method operates within constraints and inhibits to fall in local optimum problem. Cauchy distribution function permits to improve the convergence speed algorithm and to benefit global search ability of particle swarm optimisation. Simulation results show that the enhanced particle swarm optimisation contributes better in speed convergence and accuracy in comparison with classic PSO algorithm for solving traction system cost optimisation.

Keywords: FCHEV; PSO optimisation; Cauchy operator; hydrogen consumption.

DOI: 10.1504/IJGEI.2023.132020

International Journal of Global Energy Issues, 2023 Vol.45 No.4/5, pp.474 - 488

Received: 24 Jan 2022
Accepted: 27 Jul 2022
Published online: 06 Jul 2023 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article