动力电池荷电状态研究的可视化分析  

Visual analysis on state of charge for power battery

作　　者：陈燎[1] 戴俊 盘朝奉[1,2] CHEN Liao;DAI Jun;PAN Chao-feng(School of Automotive and Traffic Engineering,Jiangsu University,Zhenjiang,Jiangsu 212013,China;Automotive and Traffic Engineering Research Institute,Jiangsu University,Zhenjiang,Jiangsu 212013,China)

机构地区：[1]江苏大学汽车与交通工程学院,江苏镇江212013 [2]江苏大学汽车与交通工程研究院,江苏镇江212013

出　　处：《电池》2020年第2期187-190,共4页Battery Bimonthly

基　　金：国家重点研发计划(2018YFB0104400)。

摘　　要：基于2010-2019年Web of Science核心数据集中收录的985篇电池荷电状态(SOC)研究论文,运用Cite Space和VOSviewer知识图谱工具,对发文国家、核心作者、共引文、前沿及关键词等进行可视化呈现。2010-2019年,电池SOC研究热度逐年上升;研究国家主要是中国、美国和德国等,机构主要为各国大学;发文量较多的作者主要在中国和德国。准确高效地预测电池SOC是电动汽车管理系统的研究重点;电池模型的选择、改良及优化估算方法是动力电池SOC研究的焦点。Based on 985 articles about state of charge(SOC) for battery in the core dataset of Web of Science in 2010-2019,adopting the Cite Space and VOSviewer knowledge mapping tools were comprehensively used to visualize the publishing countries,core authors,common citations,frontiers and key words of the research on the state of battery charge,the classical literature in the field of SOC was sorted out.The research on the SOC in 2010-2019 was increasing year by year;The research were mainly in China,the United States and Germany.Research institutions were mainly concentrated in universities in different countries.The authors who published a lot were mainly concentrated in China and Germany.Accurate and efficient battery charge state prediction was the research focus development trend of electric vehicle management system,the selection and improvement of battery model and the optimization of estimation algorithm,which would be the focus of power battery SOC research.

关 键 词：动力电池 荷电状态 知识图谱 电池模型 估算方法 

分 类 号：TM912.9[电气工程—电力电子与电力传动]