A New State of Charge Estimation Method for Lithium-Ion Battery Based on the Fractional Order Model

被引:20
|
作者
Liu, Shulin [1 ]
Dong, Xia [1 ]
Zhang, Yun [2 ]
机构
[1] Qilu Univ Technol, Dept Elect Engn & Automat, Shandong Acad Sci, Jinan 250353, Shandong, Peoples R China
[2] Univ Jinan, Dept Elect Engn & Automat, Jinan 250022, Shandong, Peoples R China
来源
IEEE ACCESS | 2019年 / 7卷
关键词
Lithium-ion battery; fractional order model; state of charge estimation; Kalman filter; EQUIVALENT-CIRCUIT MODELS; KALMAN FILTER; HYBRID;
D O I
10.1109/ACCESS.2019.2932142
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents that the fractional order Kalman filter (FOKF) method is used to estimate the state of charge (SOC) for lithium-ion battery based on the fractional order model. First, a fractional order battery model was established which can better reflect the dynamic characteristics of the battery. The fractional orders were identified by genetic algorithm. Then, compared with three other modeling methods in four aspects: maximum absolute error, maximum relative error, computational complexity and number of model parameters, it is shown that the fractional order model proposed in this paper is more accurate and reliable. The results shows that the maximum absolute error of the terminal voltage is 0.014 V under constant current discharge test. The accuracy improves 0.058 V comparing to the integer order model. Finally, the SOC was estimated through two methods. The results shows that the maximum absolute estimation error of SOC is under 0.02 by FOKF, which has higher accuracy and faster convergence speed compared with extend Kalman filter (EKF) method.
引用
收藏
页码:122949 / 122954
页数:6
相关论文
共 50 条
  • [1] Fractional Order Model-based Estimation for State of Charge in Lithium-ion Battery
    Shi, Qin
    Jiang, Zhengxin
    Liu, Yiwen
    Wei, Yujiang
    Hu, Xiaosong
    He, Lin
    [J]. Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2024, 60 (08): : 224 - 232
  • [2] A novel fractional order model based state-of-charge estimation method for lithium-ion battery
    Mu, Hao
    Xiong, Rui
    Zheng, Hongfei
    Chang, Yuhua
    Chen, Zeyu
    [J]. APPLIED ENERGY, 2017, 207 : 384 - 393
  • [3] Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model
    Lu, Xin
    Li, Hui
    Xu, Jun
    Chen, Siyuan
    Chen, Ning
    [J]. ENERGIES, 2018, 11 (04)
  • [4] Joint estimation of state of charge and state of health of lithium-ion battery based on fractional order model
    Yuanzhong Xu
    Bohan Hu
    Tiezhou Wu
    Tingyi Xiao
    [J]. Journal of Power Electronics, 2022, 22 : 318 - 330
  • [5] Joint estimation of state of charge and state of health of lithium-ion battery based on fractional order model
    Xu, Yuanzhong
    Hu, Bohan
    Wu, Tiezhou
    Xiao, Tingyi
    [J]. JOURNAL OF POWER ELECTRONICS, 2022, 22 (02) : 318 - 330
  • [6] Research on the State of Charge of Lithium-Ion Battery Based on the Fractional Order Model
    Su, Lin
    Zhou, Guangxu
    Hu, Dairong
    Liu, Yuan
    Zhu, Yunhai
    [J]. ENERGIES, 2021, 14 (19)
  • [7] Lithium-ion battery state of charge estimation using a fractional battery model
    Francisco, J. M.
    Sabatier, J.
    Lavigne, L.
    Guillemard, F.
    Moze, M.
    Tari, M.
    Merveillaut, M.
    Noury, A.
    [J]. 2014 INTERNATIONAL CONFERENCE ON FRACTIONAL DIFFERENTIATION AND ITS APPLICATIONS (ICFDA), 2014,
  • [8] Comparisons of Modeling and State of Charge Estimation for Lithium-Ion Battery Based on Fractional Order and Integral Order Methods
    Xiao, Renxin
    Shen, Jiangwei
    Li, Xiaoyu
    Yan, Wensheng
    Pan, Erdong
    Chen, Zheng
    [J]. ENERGIES, 2016, 9 (03)
  • [9] Identification of fractional-order equivalent circuit model of lithium-ion battery for improving estimation of state of charge
    Wang, Jierui
    Yu, Wentao
    Cheng, Guoyang
    Chen, Lin
    [J]. JOURNAL OF ENERGY STORAGE, 2023, 70
  • [10] Co-estimation of lithium-ion battery state-of-charge and state-of-health based on fractional-order model
    Ye, Lihua
    Peng, Dinghan
    Xue, Dingbang
    Chen, Sijian
    Shi, Aiping
    [J]. JOURNAL OF ENERGY STORAGE, 2023, 65