The following publications are possibly variants of this publication:
- High-Precision State of Charge Estimation for the Power Lithium Ion Batteries by Introducing an Improved Extended Kalman Filtering Algorithm with Complex Varying TemperaturesWenhua Xu, Shunli Wang, Carlos Fernandez, ChunMei Yu, Yongcun Fan, Daniel-Ioan Stroe. icarm 2020: 700-705 [doi]
- Robustness Evaluation of Extended and Unscented Kalman Filter for Battery State of Charge EstimationChao Huang, Zhenhua Wang, Zihan Zhao, Long Wang 0015, Chun Sing Lai, Dong Wang 0001. access, 6:27617-27628, 2018. [doi]
- A Method of State-of-Charge Estimation for EV Power Lithium-Ion Battery Using a Novel Adaptive Extended Kalman FilterZhicheng He, Ziming Yang, Xiangyu Cui, Eric Li. tvt, 69(12):14618-14630, 2020. [doi]
- State-of-charge estimation of lithium-ion battery based on an improved Kalman FilterHao Fang, Yue Zhang 0005, Min Liu, Weiming Shen. cscwd 2017: 515-520 [doi]
- State of Charge Estimation of the Lithium-Ion Power Battery Based on a Multi-Time-Scale Improved Adaptive Unscented Kalman FilterMuyao Wu, Li Wang, Yu-qing Wang, Ji Wu 0009. tim, 73:1-12, 2024. [doi]
- High-precision state of charge estimation of lithium-ion batteries based on improved particle swarm optimization-backpropagation neural network-dual extended Kalman filteringLu Chen, Shunli Wang, Lei Chen, Jialu Qiao, Carlos Fernandez. ijcta, 52(3):1192-1209, March 2024. [doi]