Vis enkel innførsel

dc.contributor.authorWang, Yi-Fu
dc.contributor.authorTseng, Sheng-Tsaing
dc.contributor.authorLindqvist, Bo Henry
dc.contributor.authorTsui, Kwok-Leung
dc.date.accessioned2019-04-04T11:28:13Z
dc.date.available2019-04-04T11:28:13Z
dc.date.created2019-01-26T10:48:50Z
dc.date.issued2019
dc.identifier.issn0022-4065
dc.identifier.urihttp://hdl.handle.net/11250/2593314
dc.description.abstractRechargeable batteries are critical components for the performance of portable electronics and electric vehicles. The long-term health performance of rechargeable batteries is characterized by state of health, which can be quantified by end of performance (EOP) and remaining useful performance. Focusing on EOP prediction, this article first proposes an accelerated testing version of the trend-renewal process model to address this decision problem. The proposed model is also applied to a real case study. Finally, a NASA dataset is used to address the prediction performance of the proposed model. Comparing with the existing prediction methods and time series models, our proposed procedure has better performance in the EOP prediction.nb_NO
dc.language.isoengnb_NO
dc.publisherAsqc American Society for Quality Control/ Taylor & Francsis Groupnb_NO
dc.titleEnd of performance prediction of lithium-ion batteriesnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.journalJournal of QualityTechnologynb_NO
dc.identifier.doi10.1080/00224065.2018.1541388
dc.identifier.cristin1665424
dc.description.localcodePublisher embargo applies until January 18, 2020nb_NO
cristin.unitcode194,63,15,0
cristin.unitnameInstitutt for matematiske fag
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel