Joint Estimation of State-of-Health and State-of-Charge for Lithium-Ion Battery Based on Electrochemical Model Optimized by Neural Network

被引:17
|
作者
Sun, Xiaodong [1 ]
Chen, Qi [1 ]
Zheng, Linfeng [2 ]
Yang, Jufeng [1 ]
机构
[1] Jiangsu University, Automotive Engineering Research Institute, Zhenjiang,212013, China
[2] Jinan University, Institute of Rail Transportation, Zhuhai,519070, China
关键词
D O I
10.1109/JESTIE.2022.3148031
中图分类号
学科分类号
摘要
引用
收藏
页码:168 / 177
相关论文
共 50 条
  • [21] Joint State-of-Charge and State-of-Health Estimation for Lithium-Ion Batteries Based on Improved Lebesgue Sampling and Division of Aging Stage
    Mao, Ling
    Yang, Chuan
    Zhao, Jinbin
    Qu, Keqing
    Yu, Xiaofang
    [J]. ENERGY TECHNOLOGY, 2023, 11 (10)
  • [22] 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
  • [23] 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
  • [24] State-of-Charge Estimation of Lithium-Ion Batteries in the Battery Degradation Process Based on Recurrent Neural Network
    Li, Shuqing
    Ju, Chuankun
    Li, Jianliang
    Fang, Ri
    Tao, Zhifei
    Li, Bo
    Zhang, Tingting
    [J]. ENERGIES, 2021, 14 (02)
  • [25] A Collaborative Estimation Scheme for Lithium-Ion Battery State of Charge and State of Health Based on Electrochemical Model
    Wu, Sheyin
    Pan, Wenjie
    Zhu, Maotao
    [J]. JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2022, 169 (09)
  • [26] A novel state-of-health estimation for the lithium-ion battery using a convolutional neural network and transformer model
    Gu, Xinyu
    See, K. W.
    Li, Penghua
    Shan, Kangheng
    Wang, Yunpeng
    Zhao, Liang
    Lim, Kai Chin
    Zhang, Neng
    [J]. ENERGY, 2023, 262
  • [27] Enhanced state-of-charge and state-of-health estimation of lithium-ion battery incorporating machine learning and swarm intelligence algorithm
    Wang, Chengchao
    Su, Yingying
    Ye, Jinlu
    Xu, Peihang
    Xu, Enyong
    Ouyang, Tiancheng
    [J]. JOURNAL OF ENERGY STORAGE, 2024, 83
  • [28] A review of machine learning state-of-charge and state-of-health estimation algorithms for lithium-ion batteries
    Ren, Zhong
    Du, Changqing
    [J]. ENERGY REPORTS, 2023, 9 : 2993 - 3021
  • [29] Online State-of-Health Estimation for the Lithium-Ion Battery Based on An LSTM Neural Network with Attention Mechanism
    Zhang, Jiachang
    Hou, Jie
    Zhang, Zijian
    [J]. PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020), 2020, : 1334 - 1339
  • [30] State-of-health estimation of lithium-ion battery based on convolutional neural network considering health indicator extraction
    Mun, Tae-Suk
    Han, Dong-Ho
    Kwon, Sang-Uk
    Baek, Jong-Bok
    Kim, Jong-Hoon
    [J]. Transactions of the Korean Institute of Electrical Engineers, 2021, 70 (10): : 1467 - 1474