钒
流动电池
荷电状态
氧化还原
观察员(物理)
模式(计算机接口)
控制理论(社会学)
材料科学
流量(数学)
电池(电)
计算机科学
机械
冶金
热力学
物理
功率(物理)
人工智能
控制(管理)
量子力学
操作系统
作者
Alejandro Clemente,M. Montiel,Félix Barreras,Antonio Lozano,Ramon Costa‐Castelló
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2021-01-01
卷期号:9: 72368-72376
被引量:26
标识
DOI:10.1109/access.2021.3079382
摘要
Vanadium redox flow batteries are very promising technologies for large-scale, inter-seasonal energy storage. Tuning models from experimental data and estimating the state of charge is an important challenge for this type of devices. This work proposes a non-linear lumped parameter concentration model to describe the state of charge that differentiates the species concentrations in the different system components and allows to compute the effect of the most relevant over-potentials. Additionally, a scheme, based on the particle swarm global optimization methodology, to tune the model taking into account real experiments is proposed and validated. Finally, a novel state of charge estimation algorithm is proposed and validated. This algorithm uses a simplified version of previous models and a sliding mode control feedback law. All developments are analytically formulated and formally validated. Additionally, they have been experimentally validated in a home-made single vanadium redox flow battery cell. Proposed methods offer a constructive methodology to improve previous results in this field.
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