Xu, S; Lyu, C; Yang, D; Hinds, G; Lan, T; Sfarra, S; Zhang, H; Luo, W; Shen, D; Bai, M (2025) Online estimation of negative electrode overpotential and detection of lithium plating of batteries using electrochemistry-driven Kalman filter closed-loop framework. Applied Energy, 385. 125487 ISSN 03062619

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Abstract

Thermal runaway caused by lithium plating is a significant safety concern for users of lithium-ion batteries. Diagnosing lithium plating in batteries, which can be achieved by estimating the negative electrode overpotential (NEO) through simplified electrochemical models, is therefore of great importance. However, existing methods lack an appropriate closed-loop structure with a suitable model to simultaneously offer computational efficiency and simulation accuracy. To that end, this work first proposes a parameter-corrected simplified electrochemical model for high C-rate conditions. Based on this model, a method for NEO calculation is then proposed and embedded into the extended Kalman filter algorithm. By using NEO as a state variable and correcting it through terminal voltage measurements, a closed-loop structure is realized. The model is validated experimentally by measuring NEO using a three-electrode battery prototype. Under typical operating conditions, the proposed method can achieve a mean absolute error of 10.0 mV for NEO, which is 54% lower than using the open-loop algorithm. Additionally, this work also analyzes the convergence to the initial NEO and state of charge errors, as well as the robustness of the solid electrolyte interphase film internal resistance and temperature. In short, the proposed method meets the requirements for online applications while offering a high level of accuracy, convergence, and robustness.

Item Type:	Article
Subjects:	Advanced Materials > Electrochemistry
Divisions:	Electromagnetic & Electrochemical Technologies
Identification number/DOI:	10.1016/j.apenergy.2025.125487
Last Modified:	23 Mar 2026 14:52
URI:	https://eprintspublications.npl.co.uk/id/eprint/10347