为能在线准确估算电动汽车动力电池的荷电状态 ( SOC) ，提出了一种基于强追踪扩展卡尔曼滤波 ( STEKF) 的锂离子电池的 SOC 估算方法，该滤波器引入了多重次优渐消因子; 以某型锂离子电池为研究对象，基于电池的外特性及相关机理，建立了电池的二阶 ＲC 等效电路模型，使用最小二乘法辨识模型参数，然后按照等效电路模型建立电池的 STEKF 非线性状态空间方程，最后在 ECE15 工况下进行仿真。结果表明， STEKF 估算电池 SOC 的误差保持在 2% 以内，该方法能准确估算电池的 SOC。

A method based on strong tracking extended Kalman filter ( STEKF) with multiple suboptimal fading factors was proposed to accurately estimate the state of charge ( SOC) of EV power batteries online． Taking a lithi- um-ion battery as the research object，the second-order ＲC equivalent circuit model of a lithium-ion battery was es- tablished based on its external characteristics and related mechanism． Then the least square method was used to identify the model parameters，and the STEKF nonlinear state space equation of the battery was established accor- ding to the equivalent circuit model． Finally，the simulation was carried out under ECE15 condition． The results show that the error of STEKF in estimating battery SOC is kept within 2% ，so this method can estimate battery SOC accurately．