Choosing the best lifetime model for commercial lithium-ion batteries
dc.contributor.author | Kittaneh, Omar | |
dc.date.accessioned | 2023-06-04T09:51:40Z | |
dc.date.available | 2023-06-04T09:51:40Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | 10 | en_US |
dc.identifier.issn | 2352-1538 | en_US |
dc.identifier.doi | https://doi.org/10.1016/j.est.2021.102827 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.14131/879 | |
dc.description | This research paper investigates the suitability of three different lifetime models - Weibull, Lognormal and Normal distributions - for commercial Lithium-Ion batteries. The study involves a comparative analysis of the models using censored data from an accelerated lifetime test (ALT) to determine the best fit. While all three models yielded similar estimations of mean time to failure, they varied in their accuracy when estimating parameters of the distributions due to censoring. The study utilized three standard criteria to identify the most suitable model, ultimately concluding that the lognormal distribution provided the best fit among the three models. | en_US |
dc.description.abstract | This paper explores three-lifetime models for the commercial Lithium-Ion Batteries, namely, Weibull, Lognormal and Normal distributions. A comparative study is performed on the censored data of an accelerated lifetime test (ALT) to select the best of the proposed models. Although the three models fit the real experimental data and provide similar estimations to the mean time to failure of the batteries, the effect of censoring in estimating the parameters of the distributions is entirely different. The work uses three standard criteria to determine the preferable model. In brief, it is found that the lognormal distribution is the best among the three suggested models. | en_US |
dc.description.sponsorship | NA | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.title | Choosing the best lifetime model for commercial lithium-ion batteries | en_US |
dc.source.journal | Journal of Energy Storage | en_US |
dc.contributor.researcher | College collaboration | en_US |
dc.contributor.lab | NA | en_US |
dc.subject.KSA | ENERGY | en_US |
dc.contributor.ugstudent | 0 | en_US |
dc.contributor.alumnae | Talal Mouais | en_US |
dc.source.index | WoS | en_US |
dc.contributor.department | NSMTU | en_US |
dc.contributor.pgstudent | 1 | en_US |
dc.contributor.firstauthor | Mouais, Talal |