Online estimation of model parameters and state-of-charge of LiFePO4 batteries in electric vehicles
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Conventional Backpropagation neural networks handle nonlinear inputs effectively but struggle with temporal relationships in time-series data due to gradient issues.
“While conventional Backpropagation (BP) neural networks handle nonlinear inputs effectively, they struggle with temporal relationships in timeseries data due to gradient issues [29][30][31].”
From SOC and SOH Prediction of Lithium‐Ion Batteries Based on LSTM–AUKF Joint Algorithm (2025) · cites this paper as [29]
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- Authors
- He, H., Xiong, R., & Guo, H.
- Affiliations
- Beijing Institute of Technology (CN)
- Corresponding author
- He, Hongwen
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 89
- Issue
- 1
- Pages
- 413-420
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W2057708672
- Cited by
- 388
- References
- 19
- Citations by year
- 2026: 14 · 2025: 22 · 2024: 23 · 2023: 31 · 2022: 42 · 2021: 41 · 2020: 30 · 2019: 23 · 2018: 35 · 2017: 27 · 2016: 15 · 2015: 29 · 2014: 25 · 2013: 19 · 2012: 12
- FWCI
- 36.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Applied Energy (publishedVersion)
- 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 iron phosphate batteries, state of charge estimation, online parameter estimation, adaptive extended Kalman filter, Thevenin equivalent circuit model, battery management systems, electric vehicles, open-circuit voltage, terminal voltage
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 ›
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