摘要
针对车载锂离子电池的SoC(State of Charge)估算,面临两个主要问题:电池充放电过程中的极化效应,SoC与OCV(Open Circuit Voltage)关系曲线受电池内阻等因素影响,精度较低。从自主设计的锂电池等效电路模型入手,改进现有的Thevenin模型,用一个新的极化模型来代替传统的RC模块克服锂离子电池的极化效应,增加模型的精度。利用改进后的模型,基于DualEKF(dual-Extended Kalman Filter)估计方法,克服传统方法中无法消除电池内阻误差的缺点。对照实验结果表明,在保证较低计算复杂度的情况下,使估算误差保证在6%以内。
SoC（ state of charge） estimation of vehicle-mounted lithium ion battery has a relatively low accuracy due to two factors： polarization effect in the process of battery charging / discharging,and affection of internal resistance of the battery upon SoC-OCV（ open circuit voltage） relation curve. Starting from a self-designed equivalent circuit model of the lithium battery,we improve the existing Thevenin model by using a new polarization model in place of the traditional RC module to overcome the polarization effect of the lithium ion battery and increase the accuracy of the model. With help of the improved model,we use dual-EKF（ dual-extended Kalman filter）estimation approach to overcome the traditional method＇s shortcoming of being unable to eliminate the error of the internal resistance of the battery. Experimental results show that in the case of low computational complexity,estimation error can be maintained below 6%.
出处
《电气自动化》
2016年第3期28-31,共4页
Electrical Automation
