Microstructure Scale Lithium-Ion Battery Modeling, Part IV: The Representativity of Microstructure Parameters and Electrochemical Response

Usseglio-Viretta, Francois L. E.; Colclasure, Andrew M.; Allen, Jeffery; Weddle, Peter J.; Finegan, Donal P.; Graf, Peter; Smith, Kandler

doi:10.1149/1945-7111/adee50

Microstructure Scale Lithium-Ion Battery Modeling, Part IV: The Representativity of Microstructure Parameters and Electrochemical Response

Journal Article · Tue Aug 05 00:00:00 EDT 2025 · Journal of The Electrochemical Society

DOI:https://doi.org/10.1149/1945-7111/adee50· OSTI ID:2587218

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National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Lithium-ion battery electrochemical models require an accurate description of the electrodes microstructures to be predictive, that can be achieved through nanoscale imaging. Such observations are however limited by their field of view (FOV), as they provide only a subset of the whole electrode volume that does not necessarily represent the whole electrode microstructure heterogeneity, and therefore can bias the analysis. A representativity analysis has been performed on the microstructure parameters and, in a novel way, on the full cell electrochemical response to evaluate the predictions representativeness, and thus relevance, of a microstructure scale electrochemical model. The microstructure parameter deviation propagations to the electrochemical response have been quantified for different charge rates. This defines a threshold for the microstructure parameters FOV for a desired maximum deviation of the electrochemical response. Electrochemical model shows cell representative section areas are increasing with C-rate, due to higher in-plane heterogeneities, indicating larger FOVs are required specifically for fast charge modeling. Representativity analysis determines a cell FOV of 144.4 × 154.4 μm² is large enough to establish a convergence on the representative section areas for low-intermediate C-rate (≤2.5 C), therefore positively concludes on the model representativeness for these rates, but is not large enough to conclude for higher rates.

View Accepted Manuscript (DOE)

Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Vehicle Technologies Office (VTO)

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 2587218

Report Number(s):: NREL/JA--5700-96850

Journal Information:: Journal of The Electrochemical Society, Journal Name: Journal of The Electrochemical Society Journal Issue: 7 Vol. 172; ISSN 1945-7111; ISSN 0013-4651

Publisher:: The Electrochemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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