摘要
锂离子电池荷电状态的快速准确估计是电池管理系统的关键技术。针对锂离子电池这一动态非线性系统,以二阶RC等效电路模型为基础,采用递推最小二乘法估算模型参数,运用有限差分扩展卡尔曼滤波算法对电池荷电状态进行估算。仿真结果表明,该模型能较好地体现电池的动态特性,有限差分扩展卡尔曼滤波算法在估算过程中能保持很好的精度,并可以有效地减小由模型误差引入的荷电状态估计误差。
The fast and accurate estimation of state of charge（SOC） of lithium-ion battery is the key technology of battery management system. In view of this nonlinear dynamic system of lithium battery, this report, based on the second-order RC equivalent circuit model, uses recursive least squares method to rapidly estimate the model parameters, and then uses finite difference extended Kalman filter to estimate the battery state of charge. The simulation results show that, the battery model can essentially predict the dynamic voltage behavior of the lithium-ion battery and finite difference extended Kalman filtering algorithm can maintain good accuracy in the estimation process. What＇s more, this model can effectively reduce the error of SOC estimation introduced by model errors.
出处
《电工技术学报》
EI
CSCD
北大核心
2014年第1期221-228,共8页
Transactions of China Electrotechnical Society
关键词
锂离子电池
荷电状态
参数辨识
有限差分扩展卡尔曼滤波
Lithium-ion battery, state of charge, parameter identification, finite difference extended Kalman filter
