等效滞回模型在锂离子电池SOC估计中的应用  

Application of Equivalent Hysteresis Model in Estimaion of State of Charge of Lithium-ion Battery

作　　者：程泽[1] 吕继考 刘继光[1] 王莉[1] 

机构地区：[1]天津大学电气与自动化工程学院,天津300072

出　　处：《湖南大学学报（自然科学版）》2015年第4期63-70,共8页Journal of Hunan University:Natural Sciences

基　　金：国家自然科学基金资助项目(61374122)~~

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之一.针对锂离子电池这一动态非线性系统,通过测试分析锂离子电池的滞回特性,建立了锂离子电池的二阶RC滞回模型,并利用容积卡尔曼滤波算法对电池荷电状态进行估算.实验结果表明,该模型能较好地体现电池的动态滞回特性,而且容积卡尔曼滤波算法在估算过程中能保持较高的精度.The quick and accurate estimation of the state of charge （SOC） of lithium-ion battery is one of the key technologies of battery management system. In view of this nonlinear dynamic system of lithium battery, through the test and analysis of lithium-ion battery hysteresis characteristics, the second-order RC hysteresis model was established, and the cubature kalman filter algorithm was used to estimate the battery state of charge. The experiment results show that the battery model can essentially predict the dy- namic hysteresis voltage behavior of the lithium-ion battery and cubature kalman filtering algorithm can maintain high accuracy in the estimation process.

关 键 词：锂离子电池 荷电状态 滞回模型 容积卡尔曼滤波 

分 类 号：TM912.1[电气工程—电力电子与电力传动]