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基于扩展卡尔曼滤波模型的电动汽车锂电池SOC估算研究
引用本文:高文哲,黄涛. 基于扩展卡尔曼滤波模型的电动汽车锂电池SOC估算研究[J]. 通信电源技术, 2020, 0(1): 44-45,47
作者姓名:高文哲  黄涛
作者单位:四川长虹电源有限责任公司;四川星辉诺通讯工程有限公司
摘    要:针对新能源电动汽车锂电池电荷状态SOC估算问题,在锂电池二阶RC等效电路模型基础上,引入扩展卡尔曼滤波方法,利用扩展卡尔曼滤波方法处理复杂非线性系统能力,建立了扩展卡尔曼滤波锂电池SOC估算模型,并通过MATLAB/Simulink对新建模型仿真分析。仿真结果显示,建立的扩展卡尔曼滤波锂电池SOC估算模型具有较高估算精度,整体误差小于±0.05%,满足新能源电动汽车对锂电池SOC估算要求。

关 键 词:SOC  扩展卡尔曼滤波  二阶RC模型

SOC Estimation of Lithium Battery in Electric Vehicle Based on Extended Kalman Filter Model
GAO Wen-zhe,HUANG Tao. SOC Estimation of Lithium Battery in Electric Vehicle Based on Extended Kalman Filter Model[J]. Telecom Power Technologies, 2020, 0(1): 44-45,47
Authors:GAO Wen-zhe  HUANG Tao
Affiliation:(Sichuan Changhong Power Supply Co.,Ltd.,Mianyang 621000,China;Sichuan Xinghuinuo Communication Engineering Co.,Ltd.,Chengdu 610000,China)
Abstract:Based on the second-order RC equivalent circuit model of lithium battery,the Extended Kalman Filter(EKF)method is used to deal with the complex nonlinear system capability,and an Extended Kalman Filter(EKF)model for SOC estimation of lithium battery is established.Through the MATLAB/Simulink simulation analysis of the new estimation model,the simulation results show that the extended Kalman filter lithium battery SOC estimation model established in this paper has high estimation accuracy,the overall error is less than±0.05%,which meets the requirements of new energy electric vehicles for lithium battery SOC estimation.
Keywords:SOC  Extended Kalman Filter(EKF)  second order RC model
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