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Design optimization of lithium-ion battery using hybrid electric vehicle simulation model
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, J. | - |
| dc.contributor.author | Kim, S. | - |
| dc.contributor.author | Kim, S. | - |
| dc.contributor.author | Lim, W. | - |
| dc.contributor.author | Jang, J. | - |
| dc.contributor.author | Kim, Y. | - |
| dc.contributor.author | Yang, W. | - |
| dc.contributor.author | Lee, Tae Hee | - |
| dc.date.accessioned | 2022-07-16T01:11:56Z | - |
| dc.date.available | 2022-07-16T01:11:56Z | - |
| dc.date.created | 2021-05-13 | - |
| dc.date.issued | 2015 | - |
| dc.identifier.issn | 0000-0000 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/158280 | - |
| dc.description.abstract | As electric vehicle (EV) and hybrid electric vehicle (HEV) have been developed, the importance of research and development of lithium-ion battery is on the rise in automobile industry. However, the design method for lithium-ion battery using physical experiment requires expensive cost and much time. Therefore, computational simulation of the battery was introduced to reduce the cost and development-time. In this paper, optimum design of the battery is suggested by using optimization techniques and HEV lithium-ion simulation. We carry out analysis of variance to select the important parameters as design variables. By using these design variables, we build kriging surrogate model for total energy of the battery and define the optimization problem. Finally, we perform the optimization to obtain the maximum energy of lithium-ion battery within mass constraint. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | Korean Society of Automotive Engineers | - |
| dc.title | Design optimization of lithium-ion battery using hybrid electric vehicle simulation model | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Lee, Tae Hee | - |
| dc.identifier.scopusid | 2-s2.0-84962839115 | - |
| dc.identifier.bibliographicCitation | 28th International Electric Vehicle Symposium and Exhibition 2015, EVS 2015 | - |
| dc.relation.isPartOf | 28th International Electric Vehicle Symposium and Exhibition 2015, EVS 2015 | - |
| dc.citation.title | 28th International Electric Vehicle Symposium and Exhibition 2015, EVS 2015 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Conference Paper | - |
| dc.description.journalClass | 1 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.subject.keywordPlus | Analysis of variance (ANOVA) | - |
| dc.subject.keywordPlus | Automotive industry | - |
| dc.subject.keywordPlus | Design | - |
| dc.subject.keywordPlus | Electric batteries | - |
| dc.subject.keywordPlus | Hybrid vehicles | - |
| dc.subject.keywordPlus | Interpolation | - |
| dc.subject.keywordPlus | Ions | - |
| dc.subject.keywordPlus | Lithium | - |
| dc.subject.keywordPlus | Lithium alloys | - |
| dc.subject.keywordPlus | Optimization | - |
| dc.subject.keywordPlus | Secondary batteries | - |
| dc.subject.keywordPlus | Vehicles | - |
| dc.subject.keywordPlus | Computational simulation | - |
| dc.subject.keywordPlus | Design optimization | - |
| dc.subject.keywordPlus | Kriging surrogate model | - |
| dc.subject.keywordPlus | Optimization problems | - |
| dc.subject.keywordPlus | Optimization techniques | - |
| dc.subject.keywordPlus | Physical experiments | - |
| dc.subject.keywordPlus | Research and development | - |
| dc.subject.keywordPlus | Simulation model | - |
| dc.subject.keywordPlus | Lithium-ion batteries | - |
| dc.subject.keywordAuthor | Analysis of variance | - |
| dc.subject.keywordAuthor | Design optimization | - |
| dc.subject.keywordAuthor | Hybrid electric vehicles | - |
| dc.subject.keywordAuthor | Kriging surrogate model | - |
| dc.subject.keywordAuthor | Lithium-ion battery | - |
| dc.subject.keywordAuthor | Simulation model | - |
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