• DocumentCode
    3589781
  • Title

    The Lithium-ion battery capacity prediction error analysis based on extended Kalman filtering

  • Author

    Zhenwei Zhou ; Yun Huang ; Yudong Lu ; Zhengyu Shi ; Liangbiao Zhu ; Jiliang Wu ; Hui Li

  • Author_Institution
    China Electron. Product Reliability & Environ. Testing Res. Inst., Guangzhou, China
  • fYear
    2014
  • Firstpage
    252
  • Lastpage
    256
  • Abstract
    The Lithium-ion battery capacity prediction error is analyzed by use of extended Kalman filtering(EKF) and curve fitting algorithms. This paper employs the capacity degradation model described by Colum efficient factor, rest time and other two unknown parameters. Then, a nonlinear state-space model is introduced, and the EKF is presented to estimate the capacity and the two unknown parameters. The parameter setting in EKF is discussed in details. The capacity prediction error is analyzed with the help of curve fitting. The experiment example demonstrates the algorithms efficiency.
  • Keywords
    Kalman filters; curve fitting; error analysis; nonlinear filters; secondary cells; Colum efficient factor; Li; capacity degradation model; capacity prediction error; curve fitting algorithms; extended Kalman filtering; lithium-ion battery capacity prediction error analysis; nonlinear state-space model; Algorithm design and analysis; Batteries; Degradation; Estimation; Fitting; Prediction algorithms; Predictive models; Lithiun-ion battery; capacity; curve fitting; extended Kalman filtering; prediction erro;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability, Maintainability and Safety (ICRMS), 2014 International Conference on
  • Print_ISBN
    978-1-4799-6631-8
  • Type

    conf

  • DOI
    10.1109/ICRMS.2014.7107181
  • Filename
    7107181