Combined RLS-EKF Method for Simultaneous SOC and Parameter Estimations for Lithium-Ion Batteries

被引:4
|
作者
Oya, M. [1 ]
Sueki, W. [2 ]
Hayakawa, Y. [3 ]
Takaba, K. [4 ]
Fukui, M. [4 ]
机构
[1] GS Yuasa Corp, Osaka, Japan
[2] Osaka Univ, Grad Sch Engn, Osaka, Japan
[3] Ritsumeikan Univ, Grad Sch Sci & Engn, Kyoto, Japan
[4] Ritsumeikan Univ, Coll Sci & Engn, Kyoto, Japan
来源
关键词
MODEL PARAMETERS; CHARGE; STATE;
D O I
10.1149/08010.0207ecst
中图分类号
O646 [电化学、电解、磁化学];
学科分类号
081704 ;
摘要
This paper is concerned with the State-Of-Charge (SOC) estimation for lithium-ion batteries based an equivalent circuit model. A method for simultaneous estimation of the SOC and circuit parameters is presented by combining the extended Kalman filter (EKF) and the recursive least squares (RLS) estimation methods. The estimation accuracy of the present method is assessed through a discharge experiment of a LiFePO4 battery. In particular, the AC impedance analysis using the Cole-Cole plots shows that the parameter estimates obtained by the RLS part well describe the behavior of the battery in the operating frequency range. This supports the effectiveness of the present method.
引用
收藏
页码:207 / 217
页数:11
相关论文
共 50 条
  • [21] State of Health Estimations for Lithium-Ion Batteries Based on MSCNN
    Wang, Jiwei
    Li, Hao
    Wu, Chunling
    Shi, Yujun
    Zhang, Linxuan
    An, Yi
    ENERGIES, 2024, 17 (17)
  • [22] A Novel BCRLS-BP-EKF Method for the State of Charge Estimation of Lithium-ion Batteries
    Wang, Chao
    Wang, Shunli
    Zhou, Jinzhi
    Qiao, Jialu
    INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE, 2022, 17 (04):
  • [23] SOC Estimation Method for Lithium-ion Batteries: Extended Kalman Filter with Weighted Innovation
    Han, Yiyang
    Ding, Jie
    Chen, Jiazhong
    Sun, Peng
    PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 5074 - 5078
  • [24] The Adaptive Fading Extended Kalman Filter SOC Estimation Method for Lithium-ion Batteries
    Zhao, Yunfei
    Xu, Jun
    Wang, Xiao
    Mei, Xuesong
    RENEWABLE ENERGY INTEGRATION WITH MINI/MICROGRID, 2018, 145 : 357 - 362
  • [25] An Accurate SOC Estimation Method for Lithium-ion Batteries which Considers Thermal Variation
    Ishizaki, Ryu
    Lin, Lei
    Fukui, Masahiro
    ELECTROCHEMISTRY, 2015, 83 (10) : 852 - 854
  • [26] An Active Balancing Method Based on SOC and Capacitance for Lithium-Ion Batteries in Electric Vehicles
    Liu, Renxiong
    Zhang, Chaolong
    FRONTIERS IN ENERGY RESEARCH, 2021, 9 (09):
  • [27] An Online SOC and SOH Estimation Model for Lithium-Ion Batteries
    Huang, Shyh-Chin
    Tseng, Kuo-Hsin
    Liang, Jin-Wei
    Chang, Chung-Liang
    Pecht, Michael G.
    ENERGIES, 2017, 10 (04):
  • [28] SoC Estimation for Lithium-ion Batteries: Review and Future Challenges
    Pablo Rivera-Barrera, Juan
    Munoz-Galeano, Nicolas
    Omar Sarmiento-Maldonado, Henry
    ELECTRONICS, 2017, 6 (04)
  • [29] SOC estimation for lithium-ion batteries based on a novel model
    Li, Jiabo
    Ye, Min
    Gao, Kangping
    Xu, Xinxin
    IET POWER ELECTRONICS, 2021, 14 (13) : 2249 - 2259
  • [30] A hybrid Kalman filter for SOC estimation of lithium-ion batteries
    Hao, Tianyun
    Ding, Jie
    Tu, Taotao
    2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 5222 - 5227