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Physics-Based Equivalent Circuit Model for Lithium-Ion Cells via Reduction and Approximation of Electrochemical Model

Journal Article
2022-01-0701
ISSN: 2641-9645, e-ISSN: 2641-9645
Published March 29, 2022 by SAE International in United States
Physics-Based Equivalent Circuit Model for Lithium-Ion Cells via Reduction and Approximation of Electrochemical Model
Sector:
Citation: Seals, D., Ramesh, P., D'Arpino, M., and Canova, M., "Physics-Based Equivalent Circuit Model for Lithium-Ion Cells via Reduction and Approximation of Electrochemical Model," SAE Int. J. Adv. & Curr. Prac. in Mobility 4(4):1154-1165, 2022, https://doi.org/10.4271/2022-01-0701.
Language: English

Abstract:

Physics-based electrochemical models and empirical Equivalent Circuit Models (ECMs) are well-established and widely used modeling techniques to predict the voltage behavior of lithium-ion cells. Electrochemical models are typically very accurate and require relatively little experimental data to calibrate, but present high mathematical and computational complexity. Conversely, ECMs are more computationally efficient and mathematically simpler, making them well-suited for applications in controls, diagnosis, and state estimation of lithium-ion battery packs. However, the calibration process requires extensive testing to calibrate the parameters of the model over a wide range of operating conditions.
This paper bridges the gap between these two classes of models by developing a method to analytically define the ECM parameters starting from an already-calibrated Extended Single-Particle Model (ESPM). The governing equations of the ESPM were reduced via model order reduction, linearization and by introducing approximations to yield the mathematical structure of a second order ECM. This allowed for analytically defining the parameters of the resulting ECM, without resorting to complex lookup tables and related extensive testing for calibration. The newly defined electrochemistry-based ECM (E-ECM) saw less than 1 mV RMS error increase compared to the ESPM voltage prediction across several test profiles.