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Prediction-Based Fast Simulation with a Lightweight Solver for EV Batteries

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dc.contributor.authorKyung, Donggu-
dc.contributor.authorJoe, Inwhee-
dc.date.accessioned2022-07-09T07:32:40Z-
dc.date.available2022-07-09T07:32:40Z-
dc.date.created2021-05-13-
dc.date.issued2019-09-
dc.identifier.issn2194-5357-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/147167-
dc.description.abstractIn this paper, we propose a fast simulation method using a lightweight solver for EV batteries. In CPS, the simulation time should be reduced for real-time simulation by minimizing the overhead. In order to reduce the simulation time, the number of simulation steps needs to be decreased by a variable step size. To control the step size, a lightweight solver is introduced to predict the event as soon as possible before actual simulation. Through the prediction, a large step size can be used if there is no event, while a small step size can be used if there is an event. The simulation results show that our prediction-based method reduces the simulation time significantly, compared to the conventional non-prediction-based method.-
dc.language영어-
dc.language.isoen-
dc.publisherSpringer-
dc.titlePrediction-Based Fast Simulation with a Lightweight Solver for EV Batteries-
dc.typeArticle-
dc.contributor.affiliatedAuthorJoe, Inwhee-
dc.identifier.doi10.1007/978-3-030-30329-7_34-
dc.identifier.scopusid2-s2.0-85075614530-
dc.identifier.wosid000564759600034-
dc.identifier.bibliographicCitationAdvances in Intelligent Systems and Computing, v.1046, pp.385 - 392-
dc.relation.isPartOfAdvances in Intelligent Systems and Computing-
dc.citation.titleAdvances in Intelligent Systems and Computing-
dc.citation.volume1046-
dc.citation.startPage385-
dc.citation.endPage392-
dc.type.rimsART-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Software Engineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.subject.keywordPlusApplication programs-
dc.subject.keywordPlusComputational methods-
dc.subject.keywordPlusElectric batteries-
dc.subject.keywordPlusIntelligent systems-
dc.subject.keywordPlusEV battery-
dc.subject.keywordPlusFast simulation-
dc.subject.keywordPlusFast simulation methods-
dc.subject.keywordPlusLightweight solver-
dc.subject.keywordPlusPrediction-based-
dc.subject.keywordPlusReal time simulations-
dc.subject.keywordPlusSimulation time-
dc.subject.keywordPlusVariable step size-
dc.subject.keywordPlusForecasting-
dc.subject.keywordAuthorCPS-
dc.subject.keywordAuthorEV battery-
dc.subject.keywordAuthorFast simulation-
dc.subject.keywordAuthorFMI-
dc.subject.keywordAuthorLightweight solver-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/978-3-030-30329-7_34-
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