Search: id:"swepub:oai:DiVA.org:kth-290348" >
A Continuous-time L...
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Andersson, MalinKTH,Reglerteknik
(author)
A Continuous-time LPV model for battery state-of-health estimation using real vehicle data
- Article/chapterEnglish2020
Publisher, publication year, extent ...
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Institute of Electrical and Electronics Engineers Inc.2020
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Numbers
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LIBRIS-ID:oai:DiVA.org:kth-290348
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https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-290348URI
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https://doi.org/10.1109/CCTA41146.2020.9206257DOI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:kon swepub-publicationtype
Notes
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QC 20220519Part of proceedings: ISBN 978-172817140-1
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One approach for State-of-health estimation onboard electric vehicles is to train a data-driven virtual battery on operational data and use this model, rather than the actual battery, for performance tests. A temperature-dependent continuous-time output-error (OE) model is proposed as virtual battery and identified and validated on real operational data from electric buses. The proposed model is compared to discrete-time and parameter-invariant models and shows better performance on all data sets. In addition, the OE model structure is shown to be superior to a conventional Auto Regressive eXogenous (ARX) model for the purpose of modeling the battery voltage response. Finally, challenges regarding vehicle log data are identified and improvements to the model are suggested in order to capture observed un-modeled phenomena.
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Johansson, MikaelKTH,Reglerteknik(Swepub:kth)u13pw0wb
(author)
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Klass, V. L.
(author)
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KTHReglerteknik
(creator_code:org_t)
Related titles
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In:CCTA 2020 - 4th IEEE Conference on Control Technology and Applications: Institute of Electrical and Electronics Engineers Inc., s. 692-698
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