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Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries

Author

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  • Thomas R. B. Grandjean

    (Energy and Electrical Systems, WMG, University of Warwick, Coventry CV4 7AL, UK)

  • Andrew McGordon

    (Energy and Electrical Systems, WMG, University of Warwick, Coventry CV4 7AL, UK)

  • Paul A. Jennings

    (Energy and Electrical Systems, WMG, University of Warwick, Coventry CV4 7AL, UK)

Abstract

Structural identifiability is a critical aspect of modelling that has been overlooked in the vast majority of Li-ion battery modelling studies. It considers whether it is possible to obtain a unique solution for the unknown model parameters from experimental data. This is a fundamental prerequisite of the modelling process, especially when the parameters represent physical battery attributes and the proposed model is utilised to estimate them. Numerical estimates for unidentifiable parameters are effectively meaningless since unidentifiable parameters have an infinite number of possible numerical solutions. It is demonstrated that the physical phenomena assignment to a two-RC (resistor–capacitor) network equivalent circuit model (ECM) is not possible without additional information. Established methods to ascertain structural identifiability are applied to 12 ECMs covering the majority of model templates used previously. Seven ECMs are shown not to be uniquely identifiable, reducing the confidence in the accuracy of the parameter values obtained and highlighting the relevance of structural identifiability even for relatively simple models. Suggestions are proposed to make the models identifiable and, therefore, more valuable in battery management system applications. The detailed analyses illustrate the importance of structural identifiability prior to performing parameter estimation experiments, and the algebraic complications encountered even for simple models.

Suggested Citation

  • Thomas R. B. Grandjean & Andrew McGordon & Paul A. Jennings, 2017. "Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries," Energies, MDPI, vol. 10(1), pages 1-16, January.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:1:p:90-:d:87747
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    References listed on IDEAS

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