基于ASRUKF的锂离子电池SOC估算  

State of charge of estimation of lithium ion battery based on ASRUKF

作　　者：徐劲力[1] 郎锦峰 徐维[1] 刘佳俊 XU Jinli;LANG Jinfeng;XU Wei;LIU Jiajun(School of Mechanical and Electrical Engineering,Wuhan University of Technology,Wuhan Hubei 430070,China)

机构地区：[1]武汉理工大学机电工程学院,湖北武汉430070

出　　处：《电源技术》2021年第11期1439-1442,共4页Chinese Journal of Power Sources

摘　　要：电池荷电状态(SOC)估计对电池管理系统进行实时监控、策略控制和保障行车安全具有重要意义。为了能够提高模型辨识精度和SOC估算结果,在一阶RC电路模型的基础上,采用限定记忆递推最小二乘法(LMRLS)辨识模型参数,通过自适应平方根无迹卡尔曼滤波(ASRUKF)算法进行SOC估计,将结果与UKF算法的估算结果进行比较,结果表明ASRUKF算法具有更高的精度。Estimation of the state of charge(SOC)plays a significant role in real-time monitoring,strategy control and driving safety protection of battery management systems.For the purpose of improving the precision on model identification and SOC estimation,first order RC model is set up and limited memory least square method(LMRLS)is used for model parameters identification.Adaptive square root unscented Kalman filtering(ASRUKF)algorithm is established for SOC estimation.The results show that ASRUKF algorithm has higher precision in contrast with UKF algorithm.

关 键 词：限定记忆 自适应 荷电状态 无迹卡尔曼滤波 

分 类 号：TM911[电气工程—电力电子与电力传动]