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A novel feedback correction-adaptive Kalman filtering method for the whole-life-cycle state of charge and closed-circuit voltage prediction of lithium-ion batteries based on the second-order electrical equivalent circuit model.

Wang, Shunli; Takyi-Aninakwa, Paul; Fan, Yongcun; Yu, Chunmei; Jin, Siyu; Fernandez, Carlos; Stroe, Daniel-Ioan

Authors

Shunli Wang

Paul Takyi-Aninakwa

Yongcun Fan

Chunmei Yu

Siyu Jin

Daniel-Ioan Stroe



Abstract

Accurate state of charge (SOC) and closed-circuit voltage (CCV) prediction is essential for lithium-ion batteries and their model performance. In this study, a novel feedback correction-adaptive Kalman filtering (FC-AKF) method is proposed for the online battery state co-prediction, which is adaptive to the whole-life-cycle of the lithium-ion battery based on the improved second-order equivalent circuit model (SO-ECM). For the feedback correction strategy, the optimized iterative state initialization is conducted using the uncertainty covariance matrix of the prior three-time points with the convergence of the updating process. The experimental results show that the SOC prediction error of the proposed FC-AKF method is 0.0099% and 0.975% compared with the ampere-hour integral method under the dynamic stress test (DST) and the Beijing bus dynamic stress test (BBDST) working conditions, respectively. Also, the CCV traction by the SO-ECM is 0.80 V and has fast initial convergence and quick prediction error reduction characteristics. The constructed iterative calculation model promotes the accurate SOC and CCV co-prediction effect, improving the safety and longevity of lithium-ion batteries with high precision and fast convergence advantages.

Citation

WANG, S., TAKYI-ANINAKWA, P., FAN, Y., YU, C., JIN, S., FERNANDEZ, C. and STROE, D.-I. 2022. A novel feedback correction-adaptive Kalman filtering method for the whole-life-cycle state of charge and closed-circuit voltage prediction of lithium-ion batteries based on the second-order electrical equivalent circuit model. International journal of electrical power and energy systems [online], 139, article 108020. Available from: https://doi.org/10.1016/j.ijepes.2022.108020

Journal Article Type Article
Acceptance Date Jan 30, 2022
Online Publication Date Feb 9, 2022
Publication Date Jul 31, 2022
Deposit Date Feb 14, 2022
Publicly Available Date Mar 28, 2024
Journal International Journal of Electrical Power and Energy Systems
Print ISSN 0142-0615
Electronic ISSN 1879-3517
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 139
Article Number 108020
DOI https://doi.org/10.1016/j.ijepes.2022.108020
Keywords State of charge; Closed-circuit voltage; Second-order equivalent circuit model; Feedback correction-adaptive Kalman filter; Whole-life-cycle variation; Fast initial convergence
Public URL https://rgu-repository.worktribe.com/output/1592403