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Identifiability and parameter estimation of the single particle lithium-ion battery model

Abstract:

This paper investigates the identifiability and estimation of the parameters of the single particle model (SPM) for lithium-ion battery simulation. Identifiability is addressed both in principle and in practice. The approach begins by grouping parameters and partially nondimensionalising the SPM to determine the maximum expected degrees of freedom in the problem. We discover that excluding open-circuit voltage (OCV), there are only six independent parameters. We then examine the structural id...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1109/TCST.2018.2838097

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
ORCID:
0000-0002-3440-1262
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
St Hugh's College
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
St Hilda's College
ORCID:
0000-0002-0620-3955
Publisher:
IEEE Publisher's website
Journal:
IEEE Transactions on Control Systems Technology Journal website
Publication date:
2018-06-14
Acceptance date:
2018-05-10
DOI:
EISSN:
1558-0865
ISSN:
1063-6536
Pubs id:
pubs:820432
URN:
uri:7971ecb3-53fe-4303-b699-336c41df5647
UUID:
uuid:7971ecb3-53fe-4303-b699-336c41df5647
Local pid:
pubs:820432

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