Fractional-Order GRU Networks With Memory Units Based on Hausdorff Difference for SOC Estimations of Lithium-Ion Batteries

被引:0
|
作者
Gao, Xue [1 ]
Jia, Kai [1 ]
Gao, Zhe [1 ,2 ]
Xiao, Shasha [1 ]
机构
[1] Liaoning Univ, Sch Math & Stat, Shenyang 110036, Peoples R China
[2] Liaoning Univ, Coll Light Ind, Shenyang 110036, Peoples R China
关键词
State of charge; Estimation; Logic gates; Accuracy; Mathematical models; Lithium-ion batteries; Convergence; Recurrent neural networks; Long short term memory; Informatics; Fractional-order difference; gated recurrent unit (GRU); lithium-ion battery (LIB); state of charge (SOC); OF-CHARGE ESTIMATION; STATE; MODEL;
D O I
10.1109/TII.2024.3485762
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The gated recurrent unit (GRU) networks are widely used in engineering applications due to the excellent performance. But, the flexibility of the proportion of update information to reset information is weak in GRU networks. To tackle this issue, this article proposes a fractional-order GRU (FOGRU) with a memory unit for the state of charge (SOC) estimation of lithium-ion batteries (LIBs). First, the Hausdorff difference is introduced into the GRU network to gain the fractional-order memory unit. Then, the range of the order is rigorously analyzed to ensure the convergence of the improved structure in the FOGRU network, and the adjustment rule of orders in the FOGRU network is to adaptively tune the FOGRU network. Finally, the experiment results show that the FOGRU network achieves a satisfactory effect in the SOC estimation of LIBs.
引用
收藏
页码:1576 / 1584
页数:9
相关论文
共 50 条
  • [21] Fractional-Order Equivalent-Circuit Model Identification of Commercial Lithium-Ion Batteries
    Abdelaty, A. M.
    Fouda, Mohammed E.
    Elwakil, A. S.
    Radwan, A. G.
    JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2024, 171 (05)
  • [22] Electrochamical Model-based SOC Estimations by Using Different Algorithms for Lithium-ion Batteries
    Lyu, Chao
    Zhang, Lulu
    Li, Junfu
    Zhao, Yanben
    Luo, Weilin
    Wang, Lixin
    PROCEEDINGS OF THE 2019 14TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2019), 2019, : 2496 - 2501
  • [23] An improved H-infinity filter for SOC estimation of lithium-ion batteries based on fractional order model
    Tu, Taotao
    Ding, Jie
    Yuan, Tingting
    2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 1390 - 1395
  • [24] A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors
    Zou, Changfu
    Zhang, Lei
    Hu, Xiaosong
    Wang, Zhenpo
    Wik, Torsten
    Pecht, Michael
    JOURNAL OF POWER SOURCES, 2018, 390 : 286 - 296
  • [25] SOC Estimation for Lithium-ion Batteries Based on EKF
    Li W.
    Liu W.
    Deng Y.
    Zhongguo Jixie Gongcheng/China Mechanical Engineering, 2020, 31 (03): : 321 - 327and343
  • [26] Fractional-Order Model-Based Incremental Capacity Analysis for Degradation State Recognition of Lithium-Ion Batteries
    Tian, Jinpeng
    Xiong, Rui
    Yu, Quanqing
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 66 (02) : 1576 - 1584
  • [27] State-of-charge estimation for Lithium-Ion batteries using Kalman filters based on fractional-order models
    Xing, Likun
    Ling, Liuyi
    Gong, Bing
    Zhang, Menglong
    CONNECTION SCIENCE, 2022, 34 (01) : 162 - 184
  • [28] State of charge estimation of lithium-ion batteries with unknown parameters using an adaptive fractional-order center difference Kalman filter
    Chai, Haoyu
    Gao, Zhe
    Jiao, Zhiyuan
    Zhou, Baituan
    MEASUREMENT, 2025, 247
  • [29] Co-Estimation of State of Charge and State of Health for Lithium-Ion Batteries Based on Fractional-Order Calculus
    Hu, Xiaosong
    Yuan, Hao
    Zou, Changfu
    Li, Zhe
    Zhang, Lei
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (11) : 10319 - 10329
  • [30] An Approach for SOC Estimation Based on Sliding Mode Observer and Fractional Order Equivalent Circuit Model of Lithium-Ion Batteries
    Zhong, Fuli
    Li, Hui
    Zhong, Qishui
    2014 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (IEEE ICMA 2014), 2014, : 1497 - 1503