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Energy Sources, Part A: Recovery, Utilization, and Environmental Effects Volume 44, 2022 - Issue 4
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Research Article

State of charge estimation for the Vanadium Redox Flow Battery based on Extended Kalman filter using modified parameter identification

Qu DaweiCollege of Automotive Engineering, Jilin University, Changchun, ChinaView further author information
,
Luo ZixuanView further author information
,
Yang FanView further author information
,
Fan LuyanCorrespondence[email protected]
View further author information
,
Zhu MingyueView further author information
&
Li HaoxuanView further author information
Pages 9747-9763 | Received 02 Aug 2022, Accepted 10 Oct 2022, Published online: 22 Oct 2022

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Read on this site (1)

Deepak Kumar, M. Rizwan & Amrish K. Panwar. (2023) Advanced Intelligent approach for state of charge estimation of lithium-ion battery. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 45:4, pages 10661-10681.
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Articles from other publishers (2)

Junjie Yang, Shunli Wang, Lei Chen, Jialu Qiao, Carlos Fernandez & Josep M. Guerrero. (2023) High-precision State of Charge Estimation of Lithium-ion Batteries Based on Joint Compression Factor Particle Swarm Optimization-Forgetting Factor Recursive Least Square-Adaptive Extended Kalman Filtering. Journal of The Electrochemical Society 170:6, pages 060527.
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Chenyu Zhu, Shunli Wang, Chunmei Yu, Heng Zhou & Carlos Fernandez. (2023) An improved proportional control forgetting factor recursive least square-Monte Carlo adaptive extended Kalman filtering algorithm for high-precision state-of-charge estimation of lithium-ion batteries. Journal of Solid State Electrochemistry.
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