Lithium‑ion battery state of charge and parameters joint estimation using cubature Kalman filter and particle filter

Wei Xu; Jinli Xu; Xiaofeng Yan

Lithium‑ion battery state of charge and parameters joint estimation using cubature Kalman filter and particle filter

Wei Xu

Jinli Xu

Xiaofeng Yan

Vol. 20, No. 1, pp. 292-307, Jan. 2020

10.1007/s43236-019-00023-4

Cubature Kalman filter

Joint estimation

Lithium-ion battery

Parameters identification

Particle Filter

State of charge

Abstract

Accurate estimation of the state of charge (SOC) of a lithium-ion battery is one of the most crucial issues of battery management system (BMS). Existing methods can achieve accurate estimation of the SOC under stable working conditions. However, they may result in inaccuracy under unstable working conditions such as dynamic cycles and different temperature conditions. This is due to the fact that the dynamic behaviors of battery states have not been considered by the parameter identification methods. In this paper, a SOC and parameter joint estimation method is put forward, where the battery model parameters are identified in real time by a particle filter (PF) with consideration of the battery states. Meanwhile, a cubature Kalman filter (CKF) is used to estimate SOC. Then, experiments under dynamic cycles and different temperature conditions are undertaken to assess the performance of the proposed algorithm when compared with the existing joint estimations. The results show that the proposed joint method can achieve a high accuracy and robustness for SOC estimation.

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Cite this article

[IEEE Style]

W. Xu, J. Xu, X. Yan, "Lithium‑ion battery state of charge and parameters joint estimation using cubature Kalman filter and particle filter," Journal of Power Electronics, vol. 20, no. 1, pp. 292-307, 2020. DOI: 10.1007/s43236-019-00023-4.

[ACM Style]

Wei Xu, Jinli Xu, and Xiaofeng Yan. 2020. Lithium‑ion battery state of charge and parameters joint estimation using cubature Kalman filter and particle filter. Journal of Power Electronics, 20, 1, (2020), 292-307. DOI: 10.1007/s43236-019-00023-4.