SOC estimation based on data driven exteaded Kalman filter algorithm for power battery of electric vehicle and plug-in electric vehicle

作     者：LIU Fang MA Jie SU Wei-xing CHEN Han-ning TIAN Hui-xin LI Chun-qing 刘芳;马杰;苏卫星;陈瀚宁;田慧欣;李春青

作者机构：School of Computer Science & TechnologyTianjin Polytechnic UniversityTianjin 300387China Tianjin Qingyuan Electric Vehicle Limited Liability CompanyTianjin 300457China Control Theory and Control EngineeringTianjin UniversityTianjin 300350China 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2019年第26卷第6期

页      面：1402-1415页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：Projects(51607122,51378350)supported by the National Natural Science Foundation of China Project(BGRIMM-KZSKL-2018-02)supported by the State Key Laboratory of Process Automation in Mining&Metallurgy/Beijing Key Laboratory of Process Automation in Mining&Metallurgy Research,China Project(18JCTPJC63000)supported by Tianjin Enterprise Science and Technology Commissioner Project,China Project(2017KJ094,2017KJ093)supported by Tianjin Education Commission Scientific Research Plan Project,China Project(17ZLZXZF00280)supported by Tianjin Science and Technology Project,China Project(18JCQNJC77200)supported by Tianjin Province Science and Technology projects,China Project(2017YFB1103003,2016YFB1100501)supported by National Key Research and Development Plan,China 

主　　题：state of charge extended Kalman filter autoregressive model power battery 

摘      要：State of charge(SOC)estimation has always been a hot topic in the field of both power battery and new energy vehicle(electric vehicle(EV),plug-in electric vehicle(PHEV)and so on).In this work,aiming at the contradiction problem between the exact requirements of EKF(extended Kalman filter)algorithm for the battery model and the dynamic requirements of battery mode in life cycle or a charge and discharge period,a completely data-driven SOC estimation algorithm based on EKF algorithm is *** innovation of this algorithm lies in that the EKF algorithm is used to get the SOC accurate estimate of the power battery online with using the observable voltage and current data information of the power battery and without knowing the internal parameter variation of the power *** the combination of data-based and model-based SOC estimation method,the new method can avoid high accumulated error of traditional data-driven SOC algorithms and high dependence on battery model of most of the existing model-based SOC estimation methods,and is more suitable for the life cycle SOC estimation of the power battery operating in a complex and ever-changing environment(such as in an EV or PHEV).A series of simulation experiments illustrate better robustness and practicability of the proposed algorithm.