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State of health estimation of lithium-ion battery based on an adaptive tunable hybrid radial basis function network
Author(s):
Mingqiang Lin
,
Xianping Zeng
,
Ji Wu
Publication date
Created:
August 2021
Publication date
(Print):
August 2021
Journal:
Journal of Power Sources
Publisher:
Elsevier BV
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Recursive Rule based Visual Categorization
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Modeling of Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell
Marc Doyle
(1993)
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Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries
Yi-Ping Chen
,
Kong Ng
,
Chin-Sien Moo
…
(2009)
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Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Yongzhi Zhang
,
Rui Xiong
,
Hongwen He
…
(2018)
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Author and article information
Contributors
Mingqiang Lin:
(View ORCID Profile)
Xianping Zeng:
(View ORCID Profile)
Ji Wu:
(View ORCID Profile)
Journal
Title:
Journal of Power Sources
Abbreviated Title:
Journal of Power Sources
Publisher:
Elsevier BV
ISSN (Print):
03787753
Publication date Created:
August 2021
Publication date (Print):
August 2021
Volume
: 504
Page
: 230063
Article
DOI:
10.1016/j.jpowsour.2021.230063
SO-VID:
1b944dfe-cf05-4a79-b1b7-910902707149
Copyright ©
© 2021
License:
https://www.elsevier.com/tdm/userlicense/1.0/
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