基于Thevenin模型和UKF的锂电池SOC估算方法研究

为解决在多种工况下锂电池实时估算困难、估算精度不高等问题,以三元锂电池为研究对象,建立Thevenin模型,对电池的工作特性进行表征。综合多种工况对锂电池工作特性进行研究分析,避免了依据电池内部复杂结构建立等效模型的困难。考虑到估算初期荷电状态(SOC)准确性对于后期估算的重要性,首先用开路电压法标定初值,然后运用无迹卡尔曼滤波(UKF)算法进行估算跟踪。UKF算法基于无迹变换,没有忽略高阶项,对于非线性分布具有较高的计算精度。在Matlab/Simulink中搭建仿真模型并结合多种工况数据进行分析。试验结果表明,Thevenin模型能够较好地对锂电池SOC进行估算,收敛速度快、跟踪效果好且能将估算误差控制在0.8%以内,验证了UKF在对锂电池进行SOC估算时具有较高的精度。

Research on the Estimation Method of Lithium Battery SOC Based on Thevenin Model and UKF

In order to solve the problems of difficult real-time estimation and low estimation accuracy under various operating conditions,the Thevenin model was established to characterize the working characteristics of lithium battery with Ternary lithium battery as the research object,and the working characteristics of lithium battery were studied and analyzed by integrating various operating conditions,which avoided the difficulty of establishing an equivalent model in accordance with the complex internal structure of the battery.Considering the importance of the accuracy of the initial state of charge(SOC)estimation for later estimation,the initial value was firstly calibrated with open circuit voltage method,and then estimated and tracked by the unscented Kalman filter(UKF)algorithm.As UKF algorithm was based on unscented transformation and no higher-order terms were ignored,so it had high computational accuracy for nonlinear distribution.The simulation model was built in Matlab/Simulink and analyzed with the data at various working conditions.Experimental results showed that Thevenin model estimated SOC of lithium battery well,with fast convergence speed good tracking effect,and the estimation error within 0.8%,verifying that UKF has high accuracy in SOC estimation of lithium battery.