Cited by 70Advanced Battery Technologies ResearchAdvancements in Battery MaterialsControl Systems and Identification

Mechanics-based state of charge estimation for lithium-ion pouch battery using deep learning technique

Jiang, Bo, Tao, Siyi, Wang, Xueyuan, Zhu, Jiangong, Wei, Xuezhe, Dai, Haifeng·2023·Energy

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Registry

Crossref · 10.1016/j.energy.2023.127890

Cites

53 of 53 references verified0 citation errors · 0 not checkable

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Authors
Jiang, B., Tao, S., Wang, X., Zhu, J., Wei, X., & Dai, H.
Affiliations
Tongji University (CN)
Corresponding author
  • Wang, Xueyuan
  • Dai, Haifeng
Venue
Energy
Publisher
Elsevier BV
Published
2023-09
Volume
278
Pages
127890
ISSN
0360-5442 (ISSN-L)
OpenAlex
W4377101611
Cited by
70
References
53
Citations by year
2026: 11 · 2025: 29 · 2024: 23 · 2023: 7
FWCI
5.08
Type
journal article
Language
en
Open access
closed
Locations
  • Energy (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • National Natural Science Foundation of China
  • China Postdoctoral Science Foundation
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
  • Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
Keywords
state of charge estimation, long short-term memory neural network, battery management systems, battery datasets, measurement noise robustness

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