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

Author

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  • Intissar Darwich
  • Islem Lachhab
  • Lotfi Krichen

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.

Suggested Citation

  • Intissar Darwich & Islem Lachhab & Lotfi Krichen, 2023. "Minimisation of fuel cell electric vehicle cost using Cauchy particles swarm optimisation," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 45(4/5), pages 474-488.
    • Handle: RePEc:ids:ijgeni:v:45:y:2023:i:4/5:p:474-488
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