Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/155511
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dc.contributor.authorKanbur, Baris Buraken_US
dc.contributor.authorKumtepeli, Volkanen_US
dc.contributor.authorDuan, Feien_US
dc.date.accessioned2022-03-03T07:54:48Z-
dc.date.available2022-03-03T07:54:48Z-
dc.date.issued2020-
dc.identifier.citationKanbur, B. B., Kumtepeli, V. & Duan, F. (2020). Thermal performance prediction of the battery surface via dynamic mode decomposition. Energy, 201, 117642-. https://dx.doi.org/10.1016/j.energy.2020.117642en_US
dc.identifier.issn0360-5442en_US
dc.identifier.urihttps://hdl.handle.net/10356/155511-
dc.description.abstractThe heat dissipation from the battery surface significantly affects battery performance and lifetime. This study proposes a new and an alternative method to predict the thermal performance of the battery operation according to the surface temperature gradients and heat & exergy losses by using a data-driven dynamic mode decomposition method, which is new for thermal flows. To predict the thermal gradients, a 10 min long experiment is performed via an infrared thermographic camera for a commercial Li-polymer battery of a smartphone. The camera collects the thermal images on the battery surface along 1 min as the data training period at first; then, the proposed method predicts the surface temperature gradients for the rest of the experimental period, 5 min. The temperature gradients on the battery surface are well predicted with less than 1% error whereas the heat dissipation and the exergy loss are predicted with the maximum error values of 2.75% and 5.30%, respectively. According to the error probability distribution plots, the vast majority of the occurred error is less than ±5%. The results prove the fast prediction ability of the proposed technique and show promising outcomes for further improvement studies.en_US
dc.language.isoenen_US
dc.relation.ispartofEnergyen_US
dc.rights© 2020 Elsevier Ltd. All rights reserved.en_US
dc.subjectEngineering::Mechanical engineeringen_US
dc.titleThermal performance prediction of the battery surface via dynamic mode decompositionen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.contributor.schoolInterdisciplinary Graduate School (IGS)en_US
dc.contributor.researchEnergy Research Institute @ NTU (ERI@N)en_US
dc.identifier.doi10.1016/j.energy.2020.117642-
dc.identifier.scopus2-s2.0-85084089184-
dc.identifier.volume201en_US
dc.identifier.spage117642en_US
dc.subject.keywordsBattery Thermal Managementen_US
dc.subject.keywordsExergy Analysisen_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:ERI@N Journal Articles
IGS Journal Articles
MAE Journal Articles

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