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Asymptotic reduction and homogenization of a thermo-electrochemical model for a lithium-ion battery

    Research output: Contribution to journalArticle (Academic Journal)peer-review

    28 Citations (Scopus)

    Abstract

    In this study, matched asymptotic expansions are used to systematically reduce a thermo-electrochemical model of a lithium-ion battery based on volume averaging the electrode microstructure. In the cases with a constant or oscillating applied current, explicit asymptotic solutions of the full model can be obtained. In the case with a constant cell potential, the reduced model comprises a low-order differential-algebraic system. The asymptotic and numerical solutions of the volume-averaged model are compared with the numerical solutions of a thermal pseudo-two-dimensional (P2D) model, which treats the electrode as a collection of spherical particles. Excellent agreement is found between the models at (dis)charge rates up to 2C, and reasonable agreement is found at 4C. Homogenization is then used to derive a thermal model of a battery comprising several connected lithium-ion cells. We derive a closed-form solution to the homogenized model when the effective Biot number is small, which corresponds to a spatially uniform battery temperature. By comparing simulation times, we show that the asymptotically reduced and homogenized models provide substantial computational savings compared with the full numerical simulations, thereby making them ideal for use in onboard thermal management systems. We also show that thermal runaway does not occur in the model, despite accounting for the Arrhenius dependence of the reaction coefficients.

    Original languageEnglish
    Pages (from-to)724-754
    Number of pages31
    JournalApplied Mathematical Modelling
    Volume80
    DOIs
    Publication statusPublished - Apr 2020

    Bibliographical note

    Funding Information:
    IRM gratefully acknowledges funding from the Charlemont scholar program of the Royal Irish Academy as well as an NSERC Discovery Grant ( 2019-06337 ). MGH received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie grant agreement No. 707658. The authors thank Brian Wetton, Tim Myers, Jon Chapman, Colin Please, and Mohit Dalwadi for insightful discussions related to this research. Appendix A

    Funding Information:
    IRM gratefully acknowledges funding from the Charlemont scholar program of the Royal Irish Academy as well as an NSERC Discovery Grant (2019-06337). MGH received funding from the European Union's Horizon 2020 Research and Innovation Programme under Marie Sk?odowska-Curie grant agreement No. 707658. The authors thank Brian Wetton, Tim Myers, Jon Chapman, Colin Please, and Mohit Dalwadi for insightful discussions related to this research.

    Publisher Copyright:
    © 2019 Elsevier Inc.

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    Research Groups and Themes

    • Engineering Mathematics Research Group

    Keywords

    • Electrochemistry
    • Heat generation
    • Lithium-ion battery
    • Model reduction
    • Porous electrode theory
    • Thermal runaway

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