Journal
COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING
Volume 38, Issue 5, Pages 1533-1544Publisher
EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/COMPEL-12-2018-0533
Keywords
Multiphysics; Differential evolution; Optimal design; Finite element method; Evolution strategies; Material modelling
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Funding
- Florida International University
- COMET K2 - Competence Centers for Excellent Technologies Programme of the Federal Ministry for Transport, Innovation and Technology (bmvit)
- Federal Ministry for Digital, Business and Enterprise (bmdw)
- Austrian Research Promotion Agency (FFG)
- Province of Styria
- Styrian Business Promotion Agency (SFG)
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Purpose This paper aims to solve the parameter identification problem to estimate the parameters in electrochemical models of the lithium-ion battery. Design/methodology/approach The parameter estimation framework is applied to the Doyle-Fuller-Newman (DFN) model containing a total of 44 parameters. The DFN model is fit to experimental data obtained through the cycling of Li-ion cells. The parameter estimation is performed by minimizing the least-squares difference between the experimentally measured and numerically computed voltage curves. The minimization is performed using a state-of-the-art hybrid minimization algorithm. Findings The DFN model parameter estimation is performed within 14 h, which is a significant improvement over previous works. The mean absolute error for the converged parameters is less than 7 mV. Originality/value To the best of the authors' knowledge, application of a hybrid optimization framework is new in the field of electrical modelling of lithium-ion cells. This approach saves much time in parameterization of models with a high number of parameters while achieving a high-quality fit.
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