AUTHOR=Guo Jishu , Liu Shulin , Zhu Rui 

TITLE=An unscented kalman filtering method for estimation of state-of-charge of lithium-ion battery

JOURNAL=Frontiers in Energy Research

VOLUME=10

YEAR=2023

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.998002

DOI=10.3389/fenrg.2022.998002

ISSN=2296-598X

ABSTRACT=<p>Accurate estimation of battery state of charge (SOC) is of great significance to improve battery management and service life. An unscented Kalman filter (UKF) method is used to increase the accuracy of SOC estimation in this paper. Firstly, a battery model that the parameters are identified by using the least squares algorithm is established, which is foundation of the two-order RC equivalent circuit model. Secondly, SOC is estimated by UKF. In order to validate the method, experiments have been carried out under different operating conditions for LiFePO<sub>4</sub> batteries. The obtained results are compared with that of the extended Kalman filter. Finally, the comparison shows that the UKF method provides better accuracy in the battery SOC estimation. Its estimation error is less than 2%, which is better than EKF algorithm. An effective method is provided for state estimation for battery management system.</p>