Adaptive state-of-charge estimation of lithium-ion batteries based on square-root unscented Kalman filter

Liping Chen, Xiaobo Wu, António M. Lopes, Lisheng Yin and Penghua Li

Energy, 2022, vol. 252, issue C

Abstract: This paper proposes a state of charge (SOC) estimation method for lithium-ion batteries. Firstly, a fractional second-order RC circuit model of the battery is established. Then, a particle swarm optimization algorithm with a linear differential decline strategy is adopted to identify the model parameters, and the accuracy of the parameterized model is verified. Finally, an adaptive fractional-order square root unscented Kalman filter (AFSR-UKF) is developed, which is able to update the noise information in real time and to overcome divergence caused by inappropriate noise covariance matrices. The effectiveness of the SOC estimation method based on the AFSR-UKF is verified under a variety of operational conditions in the perspective of the root-mean-squared error, which is shown to be below 1.0%, including at extreme temperatures, revealing good accuracy and robustness.

Keywords: State-of-charge estimation; Fractional-order equivalent circuit; Square-root unscented Kalman filter (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:252:y:2022:i:c:s0360544222008751

DOI: 10.1016/j.energy.2022.123972

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