An optimized multi-segment long short-term memory network strategy for power lithium-ion battery state of charge estimation adaptive wide temperatures
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Liu et al. introduced an LSTM-based estimator that activates a specific sub-network for the current SOC stage, based on the previous stage's output, while other sub-networks remain dormant.
“Liu et al. introduced an LSTM-based estimator that activates a specific sub-network for the current SOC stage, based on the previous stage’s output, while other sub-networks remain dormant[104].”
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 [104]
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References 55 · Cited by 34
- Authors
- Liu, D., Wang, S., Fan, Y., Fernandez, C., & Blaabjerg, F.
- Affiliations
- Southwest University of Science and Technology (CN)
- Aalborg University (DK)
- Corresponding author
- Wang, Shunli
- Venue
- Energy
- Publisher
- Elsevier BV
- Published
- 2024-09
- Volume
- 304
- Pages
- 132048
- ISSN
- 0360-5442 (ISSN-L)
- OpenAlex
- W4399672257
- Cited by
- 34
- References
- 55
- Citations by year
- 2026: 15 · 2025: 14 · 2024: 5
- FWCI
- 3.67
- Type
- journal article
- Language
- en
- Open access
- green
- vbn.aau.dk
- Licence
- Locations
- Energy (publishedVersion)
- VBN Forskningsportal (Aalborg Universitet) (submittedVersion, cc-by-nc-nd)
- Open Access Institutional Repository at Robert Gordon University (Robert Gordon University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Robert Gordon University
- National Natural Science Foundation of China (62173281, 61801407)
- 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, long short-term memory networks, wide temperature range, electrochemical processes, nonlinear regression, electric vehicle batteries
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