摘要
针对无迹卡尔曼滤波法(UKF)因固定的噪声滤波协方差不能跟随工况变化致使荷电状态(SOC)估算不准确的问题,将自适应滤波算法和UKF算法相融合,在SOC估计时对系统过程噪声和测量噪声的协方差进行实时预测和修正,进而提高SOC的估算精度。仿真结果表明,自适应UKF(AUKF)的SOC估计误差在0.02以内,比UKF具有更高的估计精度。同时,基于DSP28335搭建了电池SOC硬件在环估计实验平台,对自适应UKF进行了实验验证。
In view of the problem of estimation inaccuracy in unscented Kalman filter(UKF) caused by the fixed noise filter covariance that cannot change with the change of working conditions,the combination of adaptive filter algorithm and UKF algorithm is proposed.In the process of state of charge(SOC) estimation,the covariance of system process noise and measurement noise is predicted and corrected in real time so as to improve the estimation accuracy of SOC.The simulation results show that the estimation error of the adaptive unscented Kalman filter(AUKF) is less than 0.02,which has a higher estimation accuracy than UKF.At the same time,based on DSP28335,an experimental platform on SOC hardware-in-loop estimation was built to verify the AUKF.
作者
杜洪刚
刘广忱
李阳
王方胜
DU Honggang;LIU Guangchen;LI Yang;WANG Fangsheng(Electric Power College,Inner Mongolia University of Technology,Hohhot Inner Mongolia 010080,China;Inner Mongolia Key Laboratory of Electrical Power Conversion,Transmission and Control,Hohhot Inner Mongolia 010080,China;HUADIAN Inner Mongolia Energy Co.,Ltd.,Hohhot Inner Mongolia 010000,China;State Grid East Inner Mongolia Electronic Power Synthesis Energy Co.,Ltd.,Hohhot Inner Mongolia 010010,China)
出处
《电源技术》
CAS
北大核心
2022年第9期1009-1012,共4页
Chinese Journal of Power Sources
基金
国家自然科学基金项目(51867020,51767019)
内蒙古自治区科技重大专项(2020ZD0014,2020ZD0018)。
