基于EKF的SOC估算的Simscape实现  

Implementation of Joint Estimation of SOC Based on Extended Kalman Filter in Simscape

作　　者：庞如帅 马军[2] Pang Ru-shuai;Ma Jun(Key Laboratory of Optoelectronic Technology and Intelligent Control,Ministry of Education,Lanzhou Jiaotong University,Lanzhou 730070,China;National Engineering Research Center for Technology and Equipment of Environmental Deposition,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]兰州交通大学光电技术与智能控制教育部重点实验室,甘肃兰州730070 [2]兰州交通大学国家绿色镀膜技术与装备工程技术研究中心,甘肃兰州730070

出　　处：《内燃机与配件》2024年第15期115-117,共3页Internal Combustion Engine & Parts

摘　　要：储能行业是当今热门产业之一,其中储能系统发挥着至关重要的作用,然而,该系统中的电池管理系统(Battery Management System,简称BMS)是储能系统的核心,其精确度和稳定性是储能系统正常工作的基础,为了提高其可靠性,SOC的精确估计至关重要。本文使用扩展卡尔曼滤波(Extended Kalman Filtering,简称EKF)算法来进行单电池的SOC估计,使用Simulink/Simscape搭建二阶RC电池模型来等效18650锂离子电池,经放电实验所得SOC和实际SOC进行对比,其误差不超过2%,验证了该算法具有较高精度。The energy storage industry is one of the hot industries today,in which the energy storage System plays a vital role,however,the Battery Management System(BMS)in the system is the core of the energy storage system,its accuracy and stability is the basis for the normal operation of the energy storage system,in order to improve its reliability,Accurate estimation of SOC is essential.In this paper,Extended Kalman Filtering(EKF)algorithm was used to estimate SOC of a single cell,and Simulink/Simscape was used to build a second-order RC cell model equivalent to 18650 lithium-ion batteries.The error of SOC obtained by discharge experiment is less than 2%,which proves that the algorithm has high precision.

关 键 词：SOC估计 扩展卡尔曼滤波算法 电池管理系统 

分 类 号：TM911[电气工程—电力电子与电力传动]