LiPB Battery SOC Estimation Using Extended Kalman Filter Improved with Variation of Single Dominant Parameter
Author:
Publisher
The Korean Institute of Power Electronics
Subject
Electrical and Electronic Engineering,Control and Systems Engineering
Link
http://ocean.kisti.re.kr/downfile/crosscheck/kipe/JAKO201208040011306.pdf
Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An optimized quantum particle swarm optimization–extended Kalman filter algorithm for the online state of charge estimation of high-capacity lithium-ion batteries under varying temperature conditions;Ionics;2024-08-06
2. Accurate state of temperature estimation for Lithium-Ion batteries based on square root cubature Kalman filter;Applied Thermal Engineering;2024-04
3. State of charge estimation for the Vanadium Redox Flow Battery based on Extended Kalman filter using modified parameter identification;Energy Sources, Part A: Recovery, Utilization, and Environmental Effects;2022-10-22
4. A dual‐rate sampled multiple innovation adaptive extended Kalman filter algorithm for state of charge estimation;International Journal of Energy Research;2022-08-16
5. A New SOC Estimation for LFP Batteries: Application in a 10 Ah Cell (HW 38120 L/S) as a Hysteresis Case Study;Electronics;2021-03-17
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