Energy Storage Science and Technology ›› 2023, Vol. 12 ›› Issue (10): 3230-3241.doi: 10.19799/j.cnki.2095-4239.2023.0450

• Energy Storage Test: Methods and Evaluation • Previous Articles     Next Articles

RLS-based adaptive equivalent circuit model for lithium batteries under full working conditions

Xiangwei GUO(), Chen WANG, Gang CHEN, Xiaozhuo XU   

  1. School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454003, Henan, China
  • Online:2023-10-05 Published:2023-10-09
  • Contact: Xiangwei GUO E-mail:gxw@hpu.edu.cn
  • About author:GUO Xiangwei(1987—), male, doctor, associate professor, research interests: Power electronics and its application in battery management system, E-mail:gxw@hpu.edu.cn.
  • Supported by:
    National Natural Science Foundation Project(52177039);Fundamental Research Funds for the Universities of Henan Province(NSFRF210332);Key scientific research projects of colleges and universities in Henan Province(23A470006);Science and Technology Research Project of Henan Province(232102240078)

Abstract:

This study uses a dual-polarization (DP) model to improve the identification accuracy of the battery model parameters and the model adaptability. According to the different time-varying characteristics of the model parameters, the identification process of the ohmic resistance is first separated to reduce the number of parameters that must be identified by the recursive least square (RLS). The mutual influence of the parameters is then reduced to improve the RLS identification accuracy and decrease the amount of computation. Considering the adaptability of the online and offline identifications of the model parameters to different working conditions, a full working condition-adaptive output equivalent circuit model (ECM) is proposed herein to further improve the model accuracy. Based on the model accuracy and the running speed, a model evaluation method is finally established to verify the superiority of the adaptive output ECM. The simulation experiments show that the RLS-based full working condition-adaptive output ECM has a higher accuracy than the R-DP online model with a known ohmic resistance, DP online model, and DP offline model and achieves a better accuracy and speed balance.

Key words: battery model, parameters identification, RLS, model accuracy, full working condition

CLC Number: