An improved Cauchy robust correction-sage Husa extended Kalman filtering algorithm for high-precision SOC estimation of Lithium-ion batteries in new energy vehicles.

Zhu, Chenyu; Wang, Shunli; Yu, Chunmei; Zhou, Heng; Fernandez, Carlos; Guerrero, Josep M.

Abstract

The accurate estimation of battery State of Charge (SOC) is a key technology in the research of electric vehicle battery management systems. In order to solve the problem of inaccurate noise estimation in nonlinear systems, an improved Cauchy robust correction-Sage Husa extended Kalman filtering (CRC-SHEKF) algorithm is proposed for high-precision SOC estimation of lithium-ion batteries in new energy vehicles. Considering the polarization effect of the battery, the FFRLS algorithm is used for online parameter identification of the Dual Polarization model. Using robust data correction methods, the Cauchy robust function is simplified for real-time correction of the covariance matrix Q of system state noise and the covariance matrix R of the observed noise in the filtering process and combined with SHEKF for SOC estimation. The experimental results show that under different temperature conditions and complex working conditions, the proposed CRC-SHEKF algorithm has the minimum mean absolute error (MAE), root mean square error (RMSE), and maximum error (MAX). Under the condition of the Beijing bus dynamic stress test (BBDST) at 15 °C, the MAE, RMSE, and MAX of the CRC-SHEKF algorithm are 0.392 %, 0.716 %, and 0.945 %, with the computing time of only 4.839 s. The algorithm proposed in this article has high accuracy and robustness, and has practical application value, providing a reference for the application of lithium battery condition monitoring.

Citation

ZHU, C., WANG, S., YU, C., ZHOU, H., FERNANDEZ, C. and GUERRERO, J.M. 2024. An improved Cauchy robust correction-sage Husa extended Kalman filtering algorithm for high-precision SOC estimation of Lithium-ion batteries in new energy vehicles. Journal of energy storage [online], 88, article number 111552. Available from: https://doi.org/10.1016/j.est.2024.111552

• Journal Article Type: Article
• Acceptance Date: Mar 30, 2024
• Online Publication Date: Apr 4, 2024
• Publication Date: May 30, 2024
• Deposit Date: Apr 15, 2024
• Publicly Available Date: Apr 5, 2025
• Journal: Journal of energy storage
• Print ISSN: 2352-152X
• Electronic ISSN: 2352-1538
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 88
• Article Number: 111552
• DOI: https://doi.org/10.1016/j.est.2024.111552
• Keywords: Lithium-ion battery; SOC; Cauchy robust correction; Sage Husa extended Kalman filtering; Dual polarization model
• Public URL: https://rgu-repository.worktribe.com/output/2299385
• Related Public URLs: https://rgu-repository.worktribe.com/output/2303090 (Supplementary files associated with original journal article)