Reliability assessment of a continuous-state fuel cell stack system with multiple degrading components
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yuan, Tao | - |
dc.contributor.author | Wu, Xinying | - |
dc.contributor.author | Bae, Suk Joo | - |
dc.contributor.author | Zhu, Xiaoyan | - |
dc.date.accessioned | 2022-07-09T07:33:23Z | - |
dc.date.available | 2022-07-09T07:33:23Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2019-09 | - |
dc.identifier.issn | 0951-8320 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147180 | - |
dc.description.abstract | A polymer electrolyte membrane fuel cell (PEMFC) stack is a multi-component system composed of continuously degrading fuel cells. The voltage degradation of the fuel cells causes the degradation of the stack system, which has two system-level degradation measures; the overall stack output voltage and the minimum voltage of individual cells. This paper develops a hierarchical Bayesian modeling and data analysis method to predict the reliability of a PEMFC stack system using the voltage degradation data collected from its fuel cell components. We introduce a two-term exponential model to describe the nonlinear voltage degradation paths of the fuel cell components, then builds a hierarchical Bayesian degradation model to predict the stack system reliability by taking a k-out-of-m:F system into account. Possible alternative modeling approaches are discussed with an in-depth comparison. This paper will contribute to the modeling and data analysis methods for continuous-state systems composed of continuous-state components. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCI LTD | - |
dc.title | Reliability assessment of a continuous-state fuel cell stack system with multiple degrading components | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Bae, Suk Joo | - |
dc.identifier.doi | 10.1016/j.ress.2019.04.021 | - |
dc.identifier.scopusid | 2-s2.0-85064442792 | - |
dc.identifier.wosid | 000474493000013 | - |
dc.identifier.bibliographicCitation | RELIABILITY ENGINEERING & SYSTEM SAFETY, v.189, pp.157 - 164 | - |
dc.relation.isPartOf | RELIABILITY ENGINEERING & SYSTEM SAFETY | - |
dc.citation.title | RELIABILITY ENGINEERING & SYSTEM SAFETY | - |
dc.citation.volume | 189 | - |
dc.citation.startPage | 157 | - |
dc.citation.endPage | 164 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Operations Research & Management Science | - |
dc.relation.journalWebOfScienceCategory | Engineering, Industrial | - |
dc.relation.journalWebOfScienceCategory | Operations Research & Management Science | - |
dc.subject.keywordPlus | CHANGE-POINT | - |
dc.subject.keywordPlus | DEGRADATION | - |
dc.subject.keywordPlus | PREDICTION | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordAuthor | Continuous-state systems | - |
dc.subject.keywordAuthor | Degradation analysis | - |
dc.subject.keywordAuthor | Failure-time distribution | - |
dc.subject.keywordAuthor | Gibbs sampling | - |
dc.subject.keywordAuthor | Hierarchical Bayesian modeling | - |
dc.subject.keywordAuthor | k-out-of-m:Fsystem | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0951832018311992?via%3Dihub | - |
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