电动汽车用锂离子电池荷电状态的卡尔曼滤波算法  

Estimate State of Charge of Power Lithium-ion Batteries Based on Kalman Filtering for Electric Vechicle

作　　者：孙静霞[1] 谭德荣[1] 

机构地区：[1]山东理工大学交通与车辆工程学院,山东淄博255049

出　　处：《农业装备与车辆工程》2010年第9期20-23,共4页Agricultural Equipment & Vehicle Engineering

摘　　要：在考虑电动汽车蓄电池在使用过程表现的高度非线性基础上,分析了影响电池荷电状态的主要因素及其处理方法,建立了改进的二阶线性化电路模型,采用KALMAN滤波法与安时计量法的组合算法来精确估算电池荷电状态,通过Matlab/Simulink仿真,验证该方法的可行性及准确性。Accurate state of charge（SOC） estimation for battery is very difficult for showing highly nonlinear on battery for electric vehicle.Main factors affecting SOC were analyzed.Strategy of estimating state of charge based on combinatorial algorithm of Kalman filter and Ampere-hour method was presented.State space model of a lithium battery derived from second-order model was proposed,which was combined with structure characteristic of lithium battery.The feasibility and accuracy of the model was verified by using Matlab/Simulink software.

关 键 词：荷电状态(SOC) 锂离子电池 Kalman滤波算法 

分 类 号：U469.72[机械工程—车辆工程]