Study on SOC estimation of lithium battery based on improved AUKF algorithm

Haoran Zhou; Yi Guo; Yuhang Chen; Jangwei Lu

doi:10.1117/12.3004422

25 September 2023 Study on SOC estimation of lithium battery based on improved AUKF algorithm

Haoran Zhou, Yi Guo, Yuhang Chen, Jangwei Lu

Proceedings Volume 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023); 127881Y (2023) https://doi.org/10.1117/12.3004422
Event: Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 2023, Kuala Lumpur, Malaysia

Abstract

An improved AUKF algorithm is proposed based on the adaptive traceless Kalman filter (AUKF), and the main factors that affect SOC estimation are parametrically corrected in the algorithm. The goal of this research is to be able to accurately estimate the battery state of charge (SOC) of lithium batteries. In order to do this, the main factors that affect the accuracy of battery SOC estimation as well as the advantages and disadvantages of traditional battery SOC estimation are considered. The algorithm is derived from the second-order RC equivalent circuit model of the battery. To obtain the improved AUKF algorithm, the output deviation covariance of each measurement is taken as the noise covariance. This allows the noise covariance to be updated with time and eliminates the issue that the noise covariance is a constant source of error. The results of the experiments demonstrate that an upgraded version of the AUKF algorithm may provide an accurate estimation of the battery SOC value.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Haoran Zhou, Yi Guo, Yuhang Chen, and Jangwei Lu "Study on SOC estimation of lithium battery based on improved AUKF algorithm", Proc. SPIE 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 127881Y (25 September 2023); https://doi.org/10.1117/12.3004422

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