Cited by 193Advanced Battery Technologies ResearchElectric and Hybrid Vehicle TechnologiesAdvancements in Battery Materials

State of charge estimation of lithium-ion battery using denoising autoencoder and gated recurrent unit recurrent neural network

Chen, Junxiong, Feng, Xiong, Jiang, Lin, Zhu, Qiao·2021·Energy

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Crossref · 10.1016/j.energy.2021.120451

Cites

23 of 23 references verified0 citation errors · 0 not checkable

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Authors
Chen, J., Feng, X., Jiang, L., & Zhu, Q.
Affiliations
Southwest Jiaotong University (CN)
Corresponding author
Zhu, Qiao
Venue
Energy
Publisher
Elsevier BV
Published
2021-07
Volume
227
Pages
120451
ISSN
0360-5442 (ISSN-L)
OpenAlex
W3138581309
Cited by
193
References
23
Citations by year
2026: 22 · 2025: 38 · 2024: 40 · 2023: 51 · 2022: 34 · 2021: 8
FWCI
10.80
Type
journal article
Language
en
Open access
closed
Locations
  • Energy (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • Sichuan Province Science and Technology Support Program (2020JDTD0012)
  • National Natural Science Foundation of China (51775450)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
  • Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
Keywords
state of charge estimation, lithium-ion batteries, denoising autoencoder, gated recurrent unit, recurrent neural networks, measurement noise reduction, feature extraction, driving cycles, battery management systems

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