锂电池荷电状态(SOC)预测方法综述
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  • 英文篇名:A Summary of Prediction Methods for State of Charge(SOC)of Lithium Batteries
  • 作者:吕德勇
  • 英文作者:LV De-yong;College of Automation and Electical Engineering,Qingdao University;
  • 关键词:锂电池 ; 荷电状态 ; 预测方法
  • 英文关键词:lithium battery;;state of charge;;prediction method
  • 中文刊名:TXDY
  • 英文刊名:Telecom Power Technology
  • 机构:青岛大学自动化与电气工程学院;
  • 出版日期:2018-03-25
  • 出版单位:通信电源技术
  • 年:2018
  • 期:v.35;No.171
  • 语种:中文;
  • 页:TXDY201803007
  • 页数:2
  • CN:03
  • ISSN:42-1380/TN
  • 分类号:25-26
摘要
电动汽车需要安全、高效的电池作为动力来源。锂电池因为其工作电压平稳、能量密度和充电效率高、自放电率低、没有记忆性、使用寿命长等优点被用作新一代电动汽车理想的动力源[1]。如何实现电池剩余电量的准确估算对提高锂电池的最大利用率、不断优化电池技术意义重大。在电动汽车的研究与开发中,准确地预测电池的SOC对发挥电动汽车的最佳性能、预测电动车的续驶里程有着至关重要的作用。但是锂电池的荷电状态不能直接测出,而且受充放电的速率、电池的老化程度、电池的内阻等诸多因素的影响,使其精确快速的测量具有一定难度。在阅读了大量相关文献的基础上,文中综合阐述了目前锂电池荷电状态的一些主要预测方法,并对各类方法的优缺点进行了比较。
        Electric vehicles need a safe and efficient battery as the power source.Lithium battery has been used as an ideal power source for a new generation of electric vehicles because of its stable working voltage,high energy density,high charging efficiency,low self-discharge rate,no memory,long service life and so on[1].How to accurately estimate the remaining capacity of battery is of great significance to improve the maximum utilization of lithium battery and optimize battery technology.In the research and development of electric vehicles,accurately predicting the SOC of the battery plays an important role in playing the best performance of the electric vehicle and predicting the driving mileage of the electric vehicle.However,the charge state of lithium battery cannot be measured directly,and it is difficult to measure accurately and quickly for many factors,such as the rate of charge and discharge,the aging degree of battery,and the internal resistance of battery.On the basis of reading a large number of relevant documents,the main prediction methods of the current state of charge of lithium batteries were described in this paper,and the advantages and disadvantages of various methods were compared.
引文
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    [8]孙骏,李宝辉.电动汽车电池荷电状态的估算方法研究及展望[C].2012安徽省汽车工程学会年会,2012.
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