摘要
针对非线性系统锂电池剩余电量(State of Charge,SOC)估计常用算法——安时积分法初值精度要求高、累计误差大的问题,提出了基于扩展卡尔曼滤波(Extended Kalman Filter,EKF)算法的SOC估计方法。通过建立合理的电池模型,利用MATLAB仿真在恒流工况下证明:安时积分法的平均误差为2.7%,EKF算法在无初始误差和存在初始误差两种工况下降低平均误差分别为0.97%和1.3%。最后通过ADVISOR 2002软件仿真验证了锂电池工作在两种动态电流工况下,基于EKF的SOC估计平均误差分别为1.06%、1.13%,符合SOC估计精度要求。
As a traditional algorithm for estimating the state of charge(SOC)of lithium battery in nonlinear systems,ampere-hour integral method requires high initial value accuracy and produces large cumulative error.In view of these problems,this paper proposes an SOC estimation method based on Extended Kalman Filter(EKF).By establishing a reasonable battery model,MATLAB(Matrix&Laboratory)simulation under constant current conditions shows that the average error of ampere-hour integral method is 2.7%,and the average error of EKF algorithm is reduced to 0.97%without initial error and 1.3%with initial error.Finally,through the simulation of ADVISOR 2002 software,it is verified that under two dynamic current conditions,the average error of SOC estimation based on EKF is 1.06%and 1.13%respectively,which meets the requirements of SOC estimation accuracy.
作者
李田丰
王富洲
徐潇凡
LI Tianfeng;WANG Fuzhou;XU Xiaofan(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《软件工程》
2022年第4期1-6,共6页
Software Engineering
