State of Charge Estimation of Vanadium Redox Flow Battery Based on Online Equivalent Circuit Model

被引:6
作者
Dong, Sidi [1 ]
Feng, Jun [1 ]
Zhang, Yu [2 ]
Tong, Shiqi [3 ]
Tang, Jinrui [1 ]
Xiong, Binyu [1 ]
机构
[1] Wuhan Univ Technol, Sch Automat, Wuhan, Peoples R China
[2] State Grid Hubei Elect Power Res Inst, Wuhan, Peoples R China
[3] State Grid Hubei Elect Power Co, Dept Operat & Maintenance, Wuhan, Peoples R China
来源
PROCEEDINGS OF 2021 31ST AUSTRALASIAN UNIVERSITIES POWER ENGINEERING CONFERENCE (AUPEC) | 2021年
关键词
State of charge (SOC); the recursive least squares with forgetting factor (FRLS); unscented Kalman filter (UKF); Vanadium redox flow battery; OF-CHARGE;
D O I
10.1109/AUPEC52110.2021.9597837
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
State of charge (SOC) is an important index to ensure the safe and stable operation of vanadium redox flow battery (VRB) and its accurate estimation can protect the battery from overcharge and over-discharge. Time-varying model parameters and nonlinear estimation algorithm are the main challenges for accurate estimation of SOC. This paper proposes the SOC estimation method for VRB based on online equivalent circuit model. Firstly, the recursive least squares with forgetting factor (FRLS) is used to online identify the model parameters. Then, based on this online model, the unscented Kalman filter (UKF) is employed to online estimate SOC. Finally, a hybrid pulse current experiment is conducted to verify the proposed the estimation method on a 5kW/3kWh VRB system in the laboratory. Validated with experimental data, the online identified model parameters and the estimated SOC present excellent accuracy, the root mean square error (RMSE) of the model and SOC is 0.0165V and 0.01 respectively. The proposed SOC estimation method is capable of estimating SOC accurately.
引用
收藏
页数:6
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