Journal article
Gaussian process regression for in-situ capacity estimation of lithium-ion batteries
- Abstract:
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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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- Files:
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(Accepted manuscript, pdf, 3.4MB)
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- Publisher copy:
- 10.1109/TII.2018.2794997
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Authors
Funding
Bibliographic Details
- 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:
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1941-0050
- ISSN:
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1551-3203
- Source identifiers:
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820894
Item Description
- Keywords:
- Pubs id:
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pubs:820894
- UUID:
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uuid:302473df-7fe4-4d49-adea-37d0ca28e501
- Local pid:
- pubs:820894
- Deposit date:
- 2018-01-20
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2018
- Notes:
- Copyright © 2017 IEEE. This is the accepted manuscript version of the article. The final version is available online from IEEE at: https://doi.org/10.1109/TII.2018.2794997
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