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Journal article

Gaussian process regression for in-situ capacity estimation of lithium-ion batteries

Abstract:

Accurate on-board capacity estimation is of critical importance in lithium-ion battery applications. Battery charging/discharging often occurs under a constant current load, and hence voltage vs. time measurements under this condition may be accessible in practice. This paper presents a data-driven diagnostic technique, Gaussian Process regression for In-situ Capacity Estimation (GP-ICE), which estimates battery capacity using voltage measurements over short periods of galvanostatic operation...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/TII.2018.2794997

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
St Hilda's College
Role:
Author
Publisher:
IEEE Publisher's website
Journal:
IEEE Transactions on Industrial Informatics Journal website
Volume:
15
Issue:
1
Pages:
127-138
Publication date:
2018-01-18
Acceptance date:
2018-01-14
DOI:
EISSN:
1941-0050
ISSN:
1551-3203
Source identifiers:
820894
Keywords:
Pubs id:
pubs:820894
UUID:
uuid:302473df-7fe4-4d49-adea-37d0ca28e501
Local pid:
pubs:820894
Deposit date:
2018-01-20

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