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Remaining Useful Life Prediction of a Lithium–Ion Battery Based on a Temporal Convolutional Network with Data Extension

Jing Zhao

Jing Zhao

  • Shenyang Institute of Automation, Chinese Academy of SciencesShenyang, China
  • Institute of Robotics and Intelligent Manufacturing, Chinese Academy of SciencesShenyang, China
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Zhao, Jing
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Dayong Liu

Dayong Liu

  • Shenyang Institute of Automation, Chinese Academy of SciencesShenyang, China
  • University of the Chinese Academy of SciencesBeijing, China
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Liu, Dayong
 e 
Lingshuai Meng

Lingshuai Meng

  • Shenyang Institute of Automation, Chinese Academy of SciencesShenyang, China
  • University of the Chinese Academy of SciencesBeijing, China
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Meng, Lingshuai
  
26 mar 2024
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Pubblicato online: 26 mar 2024
Pagine: 105 - 117
Ricevuto: 15 mar 2023
Accettato: 13 nov 2023
DOI: https://doi.org/10.61822/amcs-2024-0008
Parole chiave
© 2024 Jing Zhao et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Zhao, Jing
Shenyang Institute of Automation, Chinese Academy of SciencesShenyang, China
Institute of Robotics and Intelligent Manufacturing, Chinese Academy of SciencesShenyang, China
Liu, Dayong
Shenyang Institute of Automation, Chinese Academy of SciencesShenyang, China
University of the Chinese Academy of SciencesBeijing, China
Meng, Lingshuai
Shenyang Institute of Automation, Chinese Academy of SciencesShenyang, China
University of the Chinese Academy of SciencesBeijing, China
Lingua:
Inglese
Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Matematica, Matematica applicata
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