Title: Ensemble of different improvements in differential evolution for parameter extraction of PEMFC model

Authors: Wenyin Gong; Zhihua Cai; Jun Du

Addresses: School of Computer Science, China University of Geosciences, Wuhan 430074, China ' School of Computer Science, China University of Geosciences, Wuhan 430074, China ' Department of Computer Science, The University of Western Ontario, London N6A 3K7, Canada

Abstract: In order to improve the design of the proton exchange membrane fuel cell (PEMFC) model, in this paper, a modified differential evolution (MDE) method is employed for extracting the unknown parameters of PEMFC model. In MDE, an ensemble of three improvements presented in the differential evolution (DE) literature is implemented. These improvements are: i) opposition-based population initialisation; ii) tournament-based base vector selection; iii) single population structure of DE. To verify the performance of MDE, it is used to solve the parameter extraction problems of PEMFC model. Experimental results indicate that the simulated data of the EPMFC model with the extracted parameters well agrees with the experimental data. In addition, compared with artificial bee colony, the original DE algorithm, and the comprehensive learning particle swarm optimisation, the superiority of MDE is demonstrated.

Keywords: PEMFC design; proton exchange membrane fuel cells; parameter extraction; differential evolution; ensemble; model parameters; opposition-based population initialisation; tournament-based base vector selection; single population structure; simulation; artificial bee colony; ABC; PSO; particle swarm optimisation.

DOI: 10.1504/IJCAT.2015.069333

International Journal of Computer Applications in Technology, 2015 Vol.51 No.3, pp.193 - 202

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 11 May 2015 *

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