热力发电2025，Vol.54Issue(4)：68-76,9.DOI:10.19666/j.rlfd.202407203
基于FFRLS-MIUKF算法的全钒液流电池荷电状态估计方法
State-of-charge estimation method for vanadium redox flow battery based on FFRLS-MIUKF algorithm
郑涛 1贾泽峰 1邱亚 1李俊伟 1侯谋1
作者信息
- 1. 合肥工业大学电气与自动化工程学院,合肥 230009
- 折叠
摘要
Abstract
In order to solve the problems of difficult,high cost and poor accuracy of state-of-charge(SOC)estimation for vanadium redox flow batteries(VFB),a joint SOC estimation method is proposed,based on forgetting factor recursive least squares(FFRLS)and multiple innovation unscented Kalman filter(MIUKF).The FFRLS algorithm is used to identify the equivalent circuit model parameters of vanadium redox flow batteries online,and the MIUKF algorithm is used for SOC estimation,so as to achieve the purpose of accurately estimating the SOC of vanadium redox flow batteries.Finally,a 5 kW/30 kW·h vanadium redox flow battery is taken as experimental platform to verify the method.The experimental results show that,compared with the RLS-UKF algorithm and FFRLS-UKF algorithm,the FFRLS-MIUKF algorithm has lower mean square error and root mean square error in the charging and discharging phases,which are 0.003 7,0.060 9 and 0.001 3,0.036 3.关键词
全钒液流电池/SOC估计/递推最小二乘/多新息无迹卡尔曼滤波/遗忘因子Key words
vanadium redox flow battery/state-of-charge estimation/recursive least squares/multiple innovation unscented Kalman filter/forgetting factor引用本文复制引用
郑涛,贾泽峰,邱亚,李俊伟,侯谋..基于FFRLS-MIUKF算法的全钒液流电池荷电状态估计方法[J].热力发电,2025,54(4):68-76,9.
