Lithium-ion battery state-of-charge estimation for small target sample sets using the improved GRU-based transfer learning
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Wang et al. utilized transfer learning for GRU-based estimators, cutting the training time for target batteries by nearly 4 min.
“Wang et al. utilized transfer learning for GRU-based estimators, cutting the training time for target batteries by nearly 4 min[108].”
From Advancements in the estimation of the state of charge of lithium-ion battery: a comprehensive review of traditional and deep learning approaches (2025) · cites this paper as [108]
The citation lists haven’t been fetched yet
References 40 · Cited by 166
- Authors
- Wang, Y.-X., Chen, Z., & Zhang, W.
- Affiliations
- Beijing Institute of Technology (CN)
- Fuzhou University (CN)
- Contemporary Amperex Technology Co., Limited. (CN)
- Corresponding author
- Wang, Ya-Xiong
- Venue
- Energy
- Publisher
- Elsevier BV
- Published
- 2022-04
- Volume
- 244
- Pages
- 123178
- ISSN
- 0360-5442 (ISSN-L)
- OpenAlex
- W4205629695
- Cited by
- 166
- References
- 40
- Citations by year
- 2026: 20 · 2025: 38 · 2024: 59 · 2023: 34 · 2022: 15
- FWCI
- 9.95
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Energy (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Natural Science Foundation of China (51907030)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Keywords
- lithium-ion batteries, state of charge estimation, gated recurrent unit, transfer learning, battery management systems, Lagrange interpolation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
