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
  • [41] Study on the estimation of the state of charge of lithium-ion battery
    Yuan, Baohe
    Zhang, Binger
    Yuan, Xiang
    An, Zheng
    Chen, Guoxi
    Chen, Lulu
    Luo, Shijun
    [J]. ELECTROCHIMICA ACTA, 2024, 491
  • [42] Modeling and state of charge estimation of lithium-ion battery
    Xi-Kun Chen
    Dong Sun
    [J]. Advances in Manufacturing, 2015, 3 : 202 - 211
  • [43] Review of lithium-ion battery state of charge estimation
    Ning Li
    Yu Zhang
    Fuxing He
    Longhui Zhu
    Xiaoping Zhang
    Yong Ma
    Shuning Wang
    [J]. Global Energy Interconnection, 2021, 4 (06) : 619 - 630
  • [44] Modeling and state of charge estimation of lithium-ion battery
    Chen, Xi-Kun
    Sun, Dong
    [J]. ADVANCES IN MANUFACTURING, 2015, 3 (03) : 202 - 211
  • [45] Fast Estimation of State of Charge for Lithium-ion Battery
    Chen, Hung-Cheng
    Chou, Shuo-Rong
    Chen, Hong-Chou
    Wu, Shing-Lih
    Chen, Liang-Rui
    [J]. 2014 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C 2014), 2014, : 284 - 287
  • [46] Review of lithium-ion battery state of charge estimation
    Li, Ning
    Zhang, Yu
    He, Fuxing
    Zhu, Longhui
    Zhang, Xiaoping
    Ma, Yong
    Wang, Shuning
    [J]. GLOBAL ENERGY INTERCONNECTION-CHINA, 2021, 4 (06): : 619 - 630
  • [47] Modeling and state of charge estimation of lithium-ion battery
    Xi-Kun Chen
    Dong Sun
    [J]. Advances in Manufacturing, 2015, 3 (03) : 202 - 211
  • [48] Lithium-ion Battery Modeling and State of Charge Estimation
    Wei Xiong
    Mo, Yimin
    Feng Zhang
    [J]. INTEGRATED FERROELECTRICS, 2019, 200 (01) : 59 - 72
  • [49] Lithium-ion Battery State of Charge Estimation based on Moving Horizon
    Ma Yan
    Zhou Xiuwen
    Zhang Jixing
    [J]. 2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2014, : 5002 - 5007
  • [50] State of charge estimation of Lithium-ion battery using an improved fractional-order extended Kalman filter
    Solomon, Oluwole Olalekan
    Zheng, Wei
    Chen, Junxiong
    Qiao, Zhu
    [J]. JOURNAL OF ENERGY STORAGE, 2022, 49