dc.contributor.author | Wang, Yi-Fu | |
dc.contributor.author | Tseng, Sheng-Tsaing | |
dc.contributor.author | Lindqvist, Bo Henry | |
dc.contributor.author | Tsui, Kwok-Leung | |
dc.date.accessioned | 2019-04-04T11:28:13Z | |
dc.date.available | 2019-04-04T11:28:13Z | |
dc.date.created | 2019-01-26T10:48:50Z | |
dc.date.issued | 2019 | |
dc.identifier.issn | 0022-4065 | |
dc.identifier.uri | http://hdl.handle.net/11250/2593314 | |
dc.description.abstract | Rechargeable 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.iso | eng | nb_NO |
dc.publisher | Asqc American Society for Quality Control/ Taylor & Francsis Group | nb_NO |
dc.title | End of performance prediction of lithium-ion batteries | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.journal | Journal of QualityTechnology | nb_NO |
dc.identifier.doi | 10.1080/00224065.2018.1541388 | |
dc.identifier.cristin | 1665424 | |
dc.description.localcode | Publisher embargo applies until January 18, 2020 | nb_NO |
cristin.unitcode | 194,63,15,0 | |
cristin.unitname | Institutt for matematiske fag | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |