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基于DSP的电动汽车蓄电池电量计量及荷电状态估计 被引量:2

Electricity quantity measurement and SOC estimation of storage battery in electric vehicle based on DSP
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摘要 荷电状态是反映蓄电池能量的重要参数,是电动汽车整车控制器制定能量控制策略的重要依据。为了解决电动汽车蓄电池电量计量及荷电状态估计问题,设计了基于数字信号处理器(DSP)的蓄电池电量快速计量系统,采用安时法对蓄电池充放电容量进行了估计,通过放电率、温度、自放电及容量老化等补偿措施来提高计量精度,并分析了温度与充放电倍率对蓄电池容量的影响。试验结果表明,补偿后的安时法可准确地估计蓄电池荷电状态,最大充放电倍率随温度升高而增大。 State of charge(SOC) is a critical parameter which reflects the energy state of storage battery.SOC is an important basis of energy control strategy in electric vehicle controller.In order to solve the problem of electricity quantity measurement and SOC estimation of storage battery in electric vehicle,a rapid electric energy measuring system based on digital signal processor(DSP) was designed.Ampere-hour method was adopted to estimate the charge and discharge capacity of storage battery.Compensation measures such as discharge rate,temperature,self-discharge and capacity ageing were used to improve the precision of computation.Meanwhile,influences of temperature and charge-discharge rate on battery capacity were analyzed.Experiments results show that SOC can be accurately estimated by compensated Ampere-hour method and the maximum charge-discharge rate increased with the temperature increment.
出处 《机电工程》 CAS 2012年第4期461-464,共4页 Journal of Mechanical & Electrical Engineering
关键词 电动汽车 蓄电池 荷电状态 数字信号处理器 electric vehicles storage battery state of charge(SOC) digital signal processor(DSP)
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  • 1刘险峰,邹积岩.基于灰色理论的蓄电池容量预测[J].大连理工大学学报,2005,45(5):630-632. 被引量:17
  • 2林成涛,陈全世,王军平,黄文华,王燕超.用改进的安时计量法估计电动汽车动力电池SOC[J].清华大学学报(自然科学版),2006,46(2):247-251. 被引量:97
  • 3齐国光,李建民,郏航,徐玉民.电动汽车电量计量技术的研究[J].清华大学学报(自然科学版),1997,37(3):46-49. 被引量:52
  • 4AFFANNI A,BELLINI A,CONCARI C,et al.EV Battery State of Charge:Neural Network Based Estimation[C]//IEEE International Electric Machines and Drives Conference.Medison:[s.n.],2003:684-688.
  • 5KALMAN R E.A new approach to linear filtering and prediction problems[J].Journal of basic Engineering,1960,82(1):35-45.
  • 6PLETT G L.Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs:Part 1.Background[J].Journal of Power sources,2004,134(2):252-261.
  • 7HE H,XIONG R,GUO H,et al.Comparison study on the battery models used for the energy management of batteries in electric vehicles[J].Energy Conversion and Management,2012(64):113-121.
  • 8LI J,KLEE BARILLAS J,GUENTHER C,et al.A comparative study of state of charge estimation algorithms for LiFeP04 batteries used in electric vehicles[J].Journal of Power Sources,2013,230 (15):244-250.
  • 9JWO D-J,LAI S-Y.Navigation integration using the fuzzy strong tracking unscented Kalman filter[J].Journal of Navigation,2009,62 (2):303-322.
  • 10LIU B,MA X-C,HOU C-H.A Particle Filter using SVD based Sampling Kalman Filter to Obtain the Proposal Distribution[C]//IEEE Conference on Cybernetics and Intelligent Systems.Chengdu:[s.n.],2008:581-584.

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