流动电池
钒
荷电状态
容量损失
电池(电)
分离器(采油)
稳健性(进化)
氧化还原
计算机科学
卡尔曼滤波器
电极
化学
电解质
模拟
控制理论(社会学)
无机化学
功率(物理)
人工智能
热力学
基因
物理
物理化学
量子力学
生物化学
控制(管理)
作者
Zhongbao Wei,Arjun Bhattarai,Changfu Zou,Shujuan Meng,Tuti Mariana Lim,Maria Skyllas‐Kazacos
标识
DOI:10.1016/j.jpowsour.2018.04.063
摘要
The long-term operation of the vanadium redox flow battery is accompanied by ion diffusion across the separator and side reactions, which can lead to electrolyte imbalance and capacity loss. The accurate online monitoring of capacity loss is therefore valuable for the reliable and efficient operation of vanadium redox flow battery system. In this paper, a model-based online monitoring method is proposed to detect capacity loss in the vanadium redox flow battery in real time. A first-order equivalent circuit model is built to capture the dynamics of the vanadium redox flow battery. The model parameters are online identified from the onboard measureable signals with the recursive least squares, in seeking to keep a high modeling accuracy and robustness under a wide range of working scenarios. Based on the online adapted model, an observer is designed with the extended Kalman Filter to keep tracking both the capacity and state of charge of the battery in real time. Experiments are conducted on a lab-scale battery system. Results suggest that the online adapted model is able to simulate the battery behavior with high accuracy. The capacity loss as well as the state of charge can be estimated accurately in a real-time manner.
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