基于模型的动力电池SOC估计方法研究进展  

Research progress on model-based SOC estimation methods for power batteries

作　　者：侯书增 伍志明 程雪 翟博 HOU Shuzeng;WU Zhiming;CHENG Xue;ZHAI Bo(School of Mechanical Engineering,Sichuan University of Science&Engineering,Yibin Sichuan 644000,China)

机构地区：[1]四川轻化工大学机械工程学院,四川宜宾644000

出　　处：《电源技术》2024年第1期38-44,共7页Chinese Journal of Power Sources

基　　金：四川轻化工大学人才引进项目(2020RC17)。

摘　　要：随着电动汽车应用的快速发展,负责行驶安全的电池管理系统(BMS)的重要性日益凸显。高精度的电池荷电状态(SOC)估计方法是BMS有效运行的基础。对近年来有关电池模型、模型参数辨识和SOC估计方法三个领域的研究进行了较为系统的综述,总结了主要电池模型的特点及发展趋势,介绍了模型参数辨识的一般过程以及常见的辨识方法,对四类常见SOC估计方法做了介绍,分析了它们的特点和局限性,并探讨了SOC估算功能在BMS行业中的应用研究。针对当前研究中存在的不足,提出了未来的研究方向。With the rapid development of electric vehicle applications,the importance of battery management system responsible for driving safety is increasingly prominent.High precision battery state of charge estimation method is the basis of effective operation of BMS.This paper systematically reviews the recent research on battery model,model parameter identification and SOC estimation method.The characteristics and development trend of main battery models are summarized.The general process of model parameter identification and common identification methods are introduced.Four kinds of common SOC estimation methods are introduced,and their characteristics and limitations are analyzed.In addition,the research on the application of SOC estimation function in the BMS industry is discussed.Finally,future directions for research are proposed to address the shortcomings in the current study.

关 键 词：电池管理系统 电池模型 参数辨识 综述 SOC估计 

分 类 号：TM912[电气工程—电力电子与电力传动]