摘要
估算锂电池的剩余电量一直是当前研究的热点,由于锂电池充放电过程中复杂的电化学反应,电池荷电状态(SOC)与其影响因素呈现非线性动态关系,导致难以实时精确估算SOC。本文提出了一种基于扩展卡尔曼滤波(EKF)算法,并选用戴维南(Thevenin)模型来对锂电池的剩余电量进行估算。本文在戴维南模型的基础上建立了电池的非线性状态空间方程,通过实验和仿真的结果表明,该算法的误差小于3.00%,精度达到了应用的要求。
Estimating the residual capacity of lithium battery has always been the focus of current research.Due to the complex electrochemical reaction of lithium battery during charging and discharging,the charge state(SOC)of the battery presents a nonlinear dynamic relationship with its influencing factors,which leads to the difficulty of accurate estimation of the SOC in real time.An algorithm based on extended kalman filter(EKF)is proposed in this paper,and the Thevenin model to estimate the residual electricity of lithium batteries is selected.In this paper,the nonlinear state space equation of the battery is established on the basis of the Thevenin model.The experimental and simulation results show that the error of the algorithm is less than 3.00%,and the precision can meet the requirements of the application.
作者
周义枞
王顺利
谢滟馨
康财
李建超
谢东
ZHOU Yi-cong;WANG Shun-li;XIE Yan-xin;KANG Cai;LI Jian-chao;XIE Dong(School of Information Engineering,Southwest University of Science and Technology,Mianyang621010,Sichuan,China;Mianyang Product Quality Supervision and Inspection Institute,Mianyang621000,China;Deyang Product Quality Supervision and Inspection Institute,Deyang,Sichuan 618000,China)
出处
《电池工业》
CAS
2019年第1期39-43,共5页
Chinese Battery Industry
基金
国家自然科学基金基金项目(61801407)
国家级大学生创新训练计划项(201810619028)
四川省科技厅重点研发项目(2017FZ0013
2018GZ0390)
四川省教育厅科研(17ZB0453)
四川省科技创新苗子工程项目(2017109)
大学生精准资助创新基金项目(jz18-076)
关键词
荷电状态
扩展卡尔曼滤波
戴维南模型
状态估计
锂电池
Charge state
Extended Kalman filter
Thevenin model
State estimation
Lithium battery
作者简介
第一作者:周义枞(1997-),男,本科,主要研究方向:新能源测控与电源管理;通讯作者:王顺利(1985-),男,博士,讲师,主要研究方向:检测技术及应用,青年学者,新能源测控领衔专家。
