期刊文献+

电动汽车动力电池荷电状态估计方法探讨 预览 被引量:6

Discussion on state of charge estimation methods for electric vehicle power batteries
在线阅读 下载PDF
收藏 分享 导出
摘要 准确估计电池荷电状态(SOC)是电动汽车电池管理的重要内容,SOC的准确评估对延长电池寿命和提高电动汽车整车性能具有重要意义。各国研究人员对电池SOC估计方法进行大量研究,先后提出了多种估计方法。文中介绍了电池SOC的定义及其主要影响因素,根据电池SOC估计方法的特点,按离线和在线方法对SOC估计方法进行总结和介绍,并比较了各方法的特点及实用效果。最后展望了电池SOC估计方法的两个潜在发展方向,即基于电池模型的非线性滤波方法和具有自学习能力的智能方法,为今后深入研究动力电池SOC估计方法提供借鉴。 The accurate estimation of state of charge ( SOC) is an important content in electric vehicle battery man-agement, which is also significant for extending the battery lifetime and improving the electric vehicle performance. Many studies are performed on SOC estimation methods by researchers all over the world, and lots of estimation meth-ods are proposed.In this paper, the definition of battery SOC and its main influencing factors are introduced.Accord-ing to the characteristics of estimation methods for battery SOC, the estimation methods are summarized and recom-mended based on off-line and on-line methods.The characteristics and practical effects of each method are compared. In order to give reference to the further research about SOC estimation methods for power battery in future, two poten-tial development directions of battery SOC estimation method are prospected, which are the nonlinear filtering method based on the cell model and the intelligent method with self-learning ability.
作者 曾求勇 张鑫 范兴明 Zeng Qiuyong, Zhang Xin, Fan Xingming (Department of Mechanical and Electrical Engineering, Gu~lin University of Electronic Technology, Guilin 541004, Guangxi, China)
出处 《电测与仪表》 北大核心 2014年第24期76-84,共9页 Electrical Measurement & Instrumentation
基金 国家自然科学基金(51067002 51167004) 广西科技攻关重大专项(桂科重1348003-8) 广西制造系统与先进制造技术重点实验室主任课题(13-051-09-002Z)
关键词 电动汽车 动力电池 荷电状态SOC(state of charge) 估计方法 electric vehicle power battery state of charge estimation method
作者简介 曾求勇(1989-),男,硕士研究生,主要研究方向为智能化电器。Email:429498241@qq.com 张鑫(1976-),女,讲师,主要研究方向为智能化电器。Email:zhangxin_wt@163.com 范兴明(1978-),男,博士,教授,主要研究方向为智能化电器、高电压新技术。
  • 相关文献

参考文献58

二级参考文献218

共引文献609

同被引文献49

  • 1林成涛,王军平,陈全世.电动汽车SOC估计方法原理与应用[J].电池,2004,34(5):376-378. 被引量:164
  • 2孟良荣,王金良.电动车电池现状与发展趋势[J].电池工业,2006,11(3):202-206. 被引量:33
  • 3黄文华,韩晓东,陈全世,林成涛.电动汽车SOC估计算法与电池管理系统的研究[J].汽车工程,2007,29(3):198-202. 被引量:69
  • 4崔玮,徐根林.DSP和DS18B20的温度测量系统[J].微计算机信息,2007(05Z):166-168. 被引量:12
  • 5Man K L, Wan K, Ting T O, et al. Towards a hybrid approach to SOC estimation for a smart Battery Management System (BMS) and battery supported Cyber-Physical Systems (CPS)[ C ]//Future Inter- net Communications (BCFIC), Vilnius, Lithuania , 2012 2nd Baltic Congress on. IEEE, 2012: 113-116. 被引量:1
  • 6Chen S X, Tseng K J, Choi S S. Modeling of lithium-ion battery for energy storage system simulation[ C ]//Power and Energy Engineering Conference, 2009. APPEEC 2009, Asia-Pacific. IEEE, 2009 : 1-.4. 被引量:1
  • 7Rahimi-Eichi H, Chow M Y. Adaptive parameter identification and State-of-Charge estimation of lithium-ion batteries [ C ]//IECON 2012- 38th Annum Conference of IEEE Industrial Electronics. Montreal, QC, Canada, 2012: 4012-4017. 被引量:1
  • 8Deng J. L. Control problems of grey systems [ J ]. Systems & Control Letters, 1982, 1(5):288-294. 被引量:1
  • 9Saha B, Goebel K, "Battery Data Set", NASA Ames Prognostics Da- ta Repository[ DB/OL], NASA Ames, Moffett Field, CA, 2007. ht- tp : //ti. arc. nasa. gov/project/prognostic-data-repository. 被引量:1
  • 10United States Advanced Battery Consortium. ELECTRIC VEHICLE BATTERY TEST PROCEDURES MANUAL, Revision 2, Published January 1996. 被引量:1

引证文献6

二级引证文献13

投稿分析

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部 意见反馈