Improved compound correction-electrical equivalent circuit modeling and double transform-unscented Kalman filtering for the high-accuracy closed-circuit voltage and state-of-charge co-estimation of whole-life-cycle lithium-ion batteries.

Wang, Shunli; Takyi-Aninakwa, Paul; Yu, Chunmei; Jin, Siyu; Fernandez, Carlos

Abstract

For complex energy storage conditions, it is necessary to monitor the state-of-charge (SOC) and closed-circuit voltage (CCV) status accurately for the reliable power supply application of lithium-ion batteries. Herein, an improved compound correction-electrical equivalent circuit modeling (CC-EECM) method is proposed by considering the influencing effects of ambient temperature and charge–discharge current rate variations to estimate the CCV. Then, an improved adaptive double transform-unscented Kalman filtering (ADT-UKF) method is constructed with recursive sampling data correction to estimate the nonlinear SOC. A dynamic window function filtering strategy is constructed to obtain the new sigma point set for the online weighting coefficient correction. For a temperature range of 5–45 °C, the CCV for the improved CC-EECM responds well with a maximum error of 0.008608 V, and the maximum SOC estimation error is 6.317%. The proposed ADT-UKF method improves the CCV and SOC estimation reliability and adaptability to the time-varying current rate, temperature, and aging factors.

Citation

WANG, S., TAKYI-ANINAKWA, P., YU, C., JIN, S. and FERNANDEZ, C. 2022. Improved compound correction-electrical equivalent circuit modeling and double transform-unscented Kalman filtering for the high-accuracy closed-circuit voltage and state-of-charge co-estimation of whole-life-cycle lithium-ion batteries. Energy technology [online], 10(12), article 2200921. Available from: https://doi.org/10.1002/ente.202200921

• Journal Article Type: Article
• Acceptance Date: Sep 6, 2022
• Online Publication Date: Sep 27, 2022
• Publication Date: Dec 31, 2022
• Deposit Date: Nov 29, 2022
• Publicly Available Date: Sep 28, 2023
• Journal: Energy technology
• Electronic ISSN: 2194-4296
• Publisher: Wiley-VCH Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 12
• Article Number: 2200921
• DOI: https://doi.org/10.1002/ente.202200921
• Keywords: Adaptive double transform-unscented Kalman filter; Closed-circuit voltage; Compound correction-electrical equivalent circuit modeling; Lithium-ion batteries; State-of-charge
• Public URL: https://rgu-repository.worktribe.com/output/1769416