Mathematical modelling of electrochemical, thermal and degradation processes in lithium-ion cells—A comprehensive review

Rohit Mehta and Amit Gupta

Renewable and Sustainable Energy Reviews, 2024, vol. 192, issue C

Abstract: The demand for electrochemical energy storage devices is rising rapidly as the world shifts its energy dependence from fossil fuels to renewable sources. In the last few decades, this has led to lithium-ion cells finding applications in various non-conventional applications, including electric vehicles and grid energy storage. In these novel applications, the cells in the battery packs are subjected to high current, dynamically varying load and a wide range of operating conditions such as current and temperature. From an operational point of view, predicting the response and deducing the inaccessible internal states of a cell during its operational life is greatly desired, with the thermal and degradation effects playing a significant role in the behaviour of these cells during their cycle life. Different models have been proposed to address this gap and gain insights into the effects of various internal physical phenomena on cell performance or to predict the cell’s response in real-time applications. This review provides a comprehensive summary of these models, including their governing equations, assumptions and limitations. The progress made till now and the current status of research in modelling lithium-ion cells during operation are discussed. Various physics-based, reduced-order, equivalent-circuit and data-driven models developed over the years to capture the electrochemical, degradation and thermal response of the lithium-ion cells are summarized. It is expected that one or a combination of these approaches will hold the key to developing techniques for accurate charge and health estimation methods for high-fidelity battery management systems.

Keywords: Lithium-ion modelling; Electrochemical; Thermal; Degradation; Reduced-order models; Equivalent circuit; data driven (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.rser.2023.114264

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