Accesso libero

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
Cerca questo autore su
Sciendo|Google Scholar
Zhao, Jing
, 
Dayong Liu

Dayong Liu

  • Shenyang Institute of Automation, Chinese Academy of SciencesShenyang, China
  • University of the Chinese Academy of SciencesBeijing, China
Cerca questo autore su
Sciendo|Google Scholar
Liu, Dayong
 e 
Lingshuai Meng

Lingshuai Meng

  • Shenyang Institute of Automation, Chinese Academy of SciencesShenyang, China
  • University of the Chinese Academy of SciencesBeijing, China
Cerca questo autore su
Sciendo|Google Scholar
Meng, Lingshuai
  
26 mar 2024
Remaining Useful Life Prediction of a Lithium–Ion Battery Based on a Temporal Convolutional Network with Data Extension's Cover Image
INFORMAZIONI SU QUESTO ARTICOLO
Articolo precedente
Articolo Successivo
Cita
Scarica la copertina
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.
Lingua:
Inglese
Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Matematica, Matematica applicata
Feed RSS della rivista