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dc.contributor.author민경한-
dc.date.accessioned2020-10-14T08:02:06Z-
dc.date.available2020-10-14T08:02:06Z-
dc.date.issued2019-10-
dc.identifier.citationWorld Electric Vehicle Journal, v. 10, no. 4, Page. 1-23en_US
dc.identifier.issn2032-6653-
dc.identifier.urihttps://www.mdpi.com/2032-6653/10/4/58-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/154585-
dc.description.abstractTo preserve the fun of driving and enhance driving convenience, a smart regenerative braking system (SRS) is developed. The SRS provides automatic regeneration that is appropriate for the driving conditions, but the existing technology has a low level of acceptability and comfort. To solve this problem, this paper presents an automatic regenerative control system based on a deceleration model that reflects the driver’s characteristics. The deceleration model is designed as a parametric model that mimics the driver’s behavior. In addition, it consists of parameters that represent the driver’s characteristics. These parameters are updated online by a learning algorithm. The validation results of the vehicle testing show that the vehicle maintained a safe distance from the leading car while simulating a driver’s behavior. Of all the deceleration that occurred during the testing, 92% was conducted by the automatic regeneration system. In addition, the results of the online learning algorithm are different based on the driver’s deceleration pattern. The presented automatic regenerative control system can be safely used in diverse car-following situations. Moreover, the system’s acceptability is improved by updating the driver characteristics. In the future, the algorithm will be extended for use in more diverse deceleration situations by using intelligent transportation system information.en_US
dc.description.sponsorshipThis research has been supported by Hyundai Motor Company.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.subjectsmart regenerative braking system (SRS)en_US
dc.subjectadvanced driver assistance system (ADAS)en_US
dc.subjectdriver characteristicsen_US
dc.subjectdriver behavioren_US
dc.subjectautomatic regenerationen_US
dc.titleAutomatic Longitudinal Regenerative Control of EVs Based on a Driver Characteristics-Oriented Deceleration Modelen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/wevj10040058-
dc.relation.page1-23-
dc.relation.journalWorld Electric Vehicle Journal-
dc.contributor.googleauthorSim, Gyubin-
dc.contributor.googleauthorAhn, Seongju-
dc.contributor.googleauthorPark, Inseok-
dc.contributor.googleauthorYoun, Jeamyoung-
dc.contributor.googleauthorYoo, Seungjae-
dc.contributor.googleauthorMin, Kyunghan-
dc.relation.code2019033228-
dc.sector.campusS-
dc.sector.daehakRESEARCH INSTITUTE[S]-
dc.sector.departmentAUTOMOTIVE RESEARCH CENTER AT HANYANG UNIVERSITY-
dc.identifier.pidsturm-
dc.identifier.orcidhttps://orcid.org/0000-0003-4275-476X-


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