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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Mohd Afifi Jusoh
Universiti Malaysia Terengganu
Control & Systems Engineering Electrical & Electronics Engineering

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Accurate battery model parameter identification using heuristic optimization Mohd Afifi Jusoh; Muhamad Zalani Daud
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (994.715 KB) | DOI: 10.11591/ijpeds.v11.i1.pp333-341

Abstract

This paper presents an accurate Lithium-ion battery model representation in Matlab/Simulink. The Tremblay's battery model was used as a BES model platform, where the determination of the model parameters was obtained based on heuristic optimization approach. This approach is simple but more accurate compared to the conventional method. In the classical method, it requires the user to manually select the battery model parameters from relevant points on the manufacturer discharge curves. However, this way of battery parameters extraction normally exposed to the human error and would easily result in an inaccurate selection of battery parameters for the BES simulation studies. Therefore, an easy and accurate approach using heuristic optimization for determining battery model parameters was introduced. The simulation studies utilized three different optimization algorithms for comparison purposes, i.e. 1) Particle Swarm Optimization (PSO), 2) Gravitational Search Algorithm (GSA), and 3) Genetic Algorithm (GA). The performance of BES model discharge accuracy with respect to the test data from three different algorithms was compared and the results showed that the GA approach gives the best results in terms of accuracy and execution time. Finally, the validated results of GA-optimized battery model showed the accuracy of 98% compared to the conventional approach.
Co-Authors Muhamad Zalani Daud