Abstract
Aiming at the problem that the change of capacity during the aging process of lithium-ion batteries affect the accurate estimation of state-of-charge (SOC) and state-of-health (SOH), this paper proposes a joint estimation method combines Ordinary Least Squares (OLS) and Unscented Kalman Filter (UKF) algorithm. First, OLS algorithm is used to estimate SOH online to improve the prior accuracy of SOC. Then, the SOC is estimated by UKF algorithm. The experimental results indicate that the joint SOC-SOH algorithm can realize the accurate estimation of SOC and SOH during battery aging. The SOH estimation error is within 1.5%, and the SOC estimation error is within 2%.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (Grant Nos. 51977131 and 51877138), the Natural Science Foundation of Shanghai (Grant No. 19ZR1435800), the State Key Laboratory of Automotive Safety and Energy under Project No. KF2020, and Shanghai Science and Technology Development Fund (Grant No. 19QA1406200).
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Lai, X., Yuan, M., Weng, J., Yao, Y., Zheng, Y. (2023). Joint Estimation of State-of-Charge and State-of-Health for Lithium-Ion Batteries Based on OLS-UKF Algorithm. In: Sun, F., Yang, Q., Dahlquist, E., Xiong, R. (eds) The Proceedings of the 5th International Conference on Energy Storage and Intelligent Vehicles (ICEIV 2022). ICEIV 2022. Lecture Notes in Electrical Engineering, vol 1016. Springer, Singapore. https://doi.org/10.1007/978-981-99-1027-4_137
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DOI: https://doi.org/10.1007/978-981-99-1027-4_137
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