Fuzzy logic modelling of state-of-charge and available capacity of nickel/metal hydride batteries
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SOE was introduced in 2010 to directly delineate the energy state of batteries.
“SOE was introduced in 2010 to directly delineate the energy state of batteries [12,13]”
From A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects (2018) · cites this paper as [12]
Prior power-integral SOE prediction algorithms had significant estimation inaccuracies caused by erroneous measurements and the rate capacity/energy phenomenon of batteries.
“Nevertheless, the disadvantage of the algorith ms was the significant estimation inaccuracies caused by the erroneous measurements and the rate capacity/energy phenomenon of batteries.”
From A Practical Lithium-Ion Battery Model for State of Energy and Voltage Responses Prediction Incorporating Temperature and Ageing Effects (2018) · cites this paper as [12]
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- Authors
- Singh, P., Fennie, C., & Reisner, D.
- Affiliations
- Villanova University (US)
- Corresponding author
- Singh, Pritpal
- Venue
- Journal of Power Sources
- Publisher
- Elsevier BV
- Published
- 2004-10
- Volume
- 136
- Issue
- 2
- Pages
- 322-333
- ISSN
- 0378-7753 (ISSN-L)
- OpenAlex
- W2025614238
- Cited by
- 117
- References
- 4
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 5 · 2022: 4 · 2021: 7 · 2020: 6 · 2019: 5 · 2018: 9 · 2017: 15 · 2016: 5 · 2015: 9 · 2014: 16 · 2013: 5 · 2012: 2
- FWCI
- 3.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Power Sources (publishedVersion)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Physical Sciences › Computer Science › Artificial Intelligence › Fuzzy Logic and Control Systems
- Keywords
- nickel-metal hydride batteries, state of charge estimation, available capacity, fuzzy modeling, electrochemical impedance spectroscopy, hybrid electric vehicles, battery monitoring, feature selection
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