动车组钛酸锂电池荷电状态估计  

State of Charge Estimation of Lithium Titanate Battery for Electric Multiple Units

作　　者：郝文美 张立伟[1] 彭博 蔡娇 杨瑞[2] Hao Wenmei;Zhang Liwei;Peng Bo;Cai Jiao;Yang Rui(School of Electrical Engineering Beijing Jiaotong Universit ,Beijing 100044 China;China Waterborne Transport Research Institute MOT ,Beijing 100088 China)

机构地区：[1]北京交通大学电气工程学院,北京100044 [2]交通部水运科学研究院,北京100088

出　　处：《电工技术学报》2021年第S01期362-371,共10页Transactions of China Electrotechnical Society

基　　金：中央高校基本科研业务费资助项目(2019JBM320)。

摘　　要：蓄电池作为应急供电电源,被广泛应用于动车组辅助供电系统中,电池的荷电状态可以反映充放电过程中电池的剩余电量,是动车组电池管理系统的重要参数。准确估计电池荷电状态,可以有效提高电池的使用效率及使用寿命。但是电池内部的化学反应复杂且难以测量,目前的电池荷电状态大多只能通过间接测量计算的方法得到。该文以中国标准动车组钛酸锂电池作为研究对象,搭建二阶RC等效电路模型,基于扩展卡尔曼滤波法(EKF)的在线辨识方法,并通过电池工况实验对比辨识精度。为克服常规卡尔曼滤波法估计过程中噪声方差固定的缺点,提出了自适应卡尔曼滤波方法(AEKF)对电池荷电状态进行估计,并在Matlab中针对动车组锂电池实际应用工况,验证了其估计电池荷电状态的准确性。As an emergency power supply,the battery is widely used in the auxiliary power supply system of electric multiple units(EMU).The charged state of the battery can reflect the remaining power of the battery in the charging and discharging process,which is an important parameter of the EMU battery management system.Accurate estimation of battery charged state can effectively improve the service efficiency and service life of the battery.However,the chemical reaction inside the battery is complex and difficult to measure,and most of the current charged state of the battery can only be obtained by indirect measurement and calculation.In this paper,Lithium Titanate battery of China standard EMU was taken as the research object,the second-order RC equivalent circuit model was established,and the online identification method based on Extended Kalman filtering(EKF)was studied,and the identification accuracy was compared through battery working condition experiments.In order to overcome the disadvantage of fixed noise variance in the process of conventional Kalman filtering,an adaptive Kalman filtering method was proposed to estimate the battery charged state,and its accuracy in estimating the battery charged state was verified in Matlab.

关 键 词：动车组 荷电状态 钛酸锂电池 自适应扩展卡尔曼滤波 

分 类 号：TM912[电气工程—电力电子与电力传动]