Equivalent strain model construction and rapid convergence SOC estimation of the cylindrical LiFePO4 battery

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Impact Factor:4.2

DOI number:10.1016/j.epsr.2026.113144

Journal:Electric Power Systems Research

Key Words:Cylindrical LiFePO4 battery; Equivalent strain model; Covariance optimization matching adaptive extended kalman filter; SOC estimation

Abstract:Lithium-ion batteries serve as one of the core components in electric vehicles, the state of charge (SOC) estimation accuracy significantly influences the overall performance of electric vehicles. This paper proposes a SOC estimation method for lithium-ion batteries based on an equivalent strain model and a covariance optimization matching adaptive extended Kalman filter (COMAEKF). Firstly, this paper introduces strain signals into the SOC estimation problem from the perspective of mechanical behaviors and establishes a nonlinear mapping relationship between open circuit strain and SOC via a 5th-order polynomial model. Secondly, a COMAEKF is developed to enhance the adaptability and convergence of the SOC estimation algorithm. Finally, experiment validations under various dynamic operating conditions and ambient temperatures show that the proposed methodology achieves high terminal strain estimation accuracy, with mean absolute error (MAE) below 2.60με and root mean square error (RMSE) below 3.75με Meanwhile, compared to the conventional ECM, it significantly improves the SOC estimation convergence speed and accuracy, with an initial SOC value set to 90%, the average convergence time is within 25 s, a reduction of over 94%, the average MAE remains below 0.50%, a reduction of over 82%, and the average RMSE stays below 0.65%, a reduction of over 85%.

Note:中科院3区

Co-author:Changpeng Tan

First Author:Muyao Wu

Indexed by:Essay collection

Correspondence Author:Li Wang

Document Code:113144

Discipline:Engineering

Document Type:J

Volume:258

ISSN No.:0378-7796

Translation or Not:no

Date of Publication:2026-04-17

Included Journals:SCI、EI

Links to published journals:https://www.sciencedirect.com/science/article/pii/S0378779626004372