Cited by 347Advanced Battery Technologies ResearchAdvancements in Battery MaterialsElectric and Hybrid Vehicle Technologies

Support vector based battery state of charge estimator

Open access
Hansen, Terry, Wang, Chia-Jiu·2005·Journal of Power Sources

Integrity signals

Registry

Crossref · 10.1016/j.jpowsour.2004.09.020

Cites

10 of 10 references verified0 citation errors · 0 not checkable

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  • The major weakness of SVM is that performance depends greatly on the kernel function that defines the shape of the hyperplane line.

    “The major weakness of Support Vector Machines is that their performance depends greatly on the kernel function that defines the shape of the hyperplane line [53].”
  • ML methods have been applied to battery energy management and to detect faults and lateral misalignment in wireless charging of EVs.

    “ML methods have also been applied to battery energy management (for example charge estimation [330] or optimization in hybrid EVs [15]), and to detect faults and lateral misalignment in wireless charging of EVs [780].”

    From Tackling climate change with machine learning (2023) · cites this paper as [330]

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Authors
Hansen, T., & Wang, C.-J.
Affiliations
University of Colorado Colorado Springs (US)
Corresponding author
Wang, Chia-Jiu
Venue
Journal of Power Sources
Publisher
Elsevier BV
Published
2005-03
Volume
141
Issue
2
Pages
351-358
ISSN
0378-7753 (ISSN-L)
OpenAlex
W2170977282
Cited by
347
References
10
Citations by year
2026: 8 · 2025: 24 · 2024: 18 · 2023: 18 · 2022: 20 · 2021: 19 · 2020: 18 · 2019: 26 · 2018: 18 · 2017: 26 · 2016: 20 · 2015: 33 · 2014: 17 · 2013: 24 · 2012: 13
FWCI
7.07
Type
journal article
Language
en
Open access
Locations
Journal of Power Sources (publishedVersion)
Funders
  • U.S. Department of Energy (DE-AC36-99GO-10337)
  • National Renewable Energy Laboratory
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
state of charge estimation, support vector machine, lithium polymer batteries, battery pack, Coulomb counting, US06 driving cycle, real-time embedded systems, low computational load

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