On-line prediction of lithium battery SOC and SOH based on joint algorithms
Author:
Affiliation:

Funding:

Ethical statement:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
    Abstract:

    The equivalent circuit model of Dual Polarization Thevenin(DP-Thevenin) is established to describe the dynamic and static characteristics of type 18650 lithium battery. The open circuit voltage and model parameters are identified by constant current pulse discharge experiment and Recursive Least Squares method with Forgetting Factor(FFRLS). Then an equivalent circuit model is built in Simulink, and the impulse current is used as the excitation to verify the model. It is concluded that the response voltage of the model is in good agreement with the actual terminal voltage, with an average error of 1.836%. Next, the hardware circuit of battery experiment is constructed, and the algorithm program is compiled to complete the construction of lithium battery test system. Finally, the performance of State Of Charge(SOC) and State Of Health(SOH) of lithium batteries based on joint algorithm in predicting accuracy and convergence of the algorithm at wrong initial values is analyzed by means of Matlab under random test conditions. The experimental results show that the algorithm can accurately estimate the SOC and internal resistance of batteries, the maximum error is not more than 3.5%. When the initial value differs by 15%, the algorithm can converge to the true value within 319 s with good robustness.

    Reference
    Related
    Cited by
Get Citation

刘 熹,李 琳,曹 举,刘海龙.基于联合算法的锂电池SOC与SOH协同在线预测[J]. Journal of Terahertz Science and Electronic Information Technology ,2021,19(4):739~746

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
History
  • Received:September 18,2019
  • Revised:December 02,2019
  • Adopted:
  • Online: August 25,2021
  • Published: