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Conference Paper: An optimization model for a battery swapping station in Hong Kong

TitleAn optimization model for a battery swapping station in Hong Kong
Authors
KeywordsBattery swapping station
Electric vehicle
Genetic algorithm
Battery charging methods
Issue Date2015
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1804049
Citation
The 2015 IEEE Transportation Electrification Conference and Expo (ITEC), Dearborn, MI., 14-17 June 2015. In Conference Proceedings, 2015, p. 1-6 How to Cite?
AbstractIn this paper, a battery swapping station (BSS) model is proposed as an economic and convenient way to provide energy for the batteries of the electric vehicles (EVs). This method would overcome some drawbacks to the use of electric vehicles like long charging time and insufficient running distance. On the economic concern of a battery swapping station, the station would optimize the availability of the batteries in stock, and at the same time determine the best strategy for recharging the batteries on hand. By optimizing the charging method of the batteries, an optimization model of BSS with the maximum number of batteries in stock has been developed for the bus terminal at the Hong Kong International Airport. The secondary objective would be to minimize a cost on the batteries due to the use of different charging schemes. The genetic algorithm (GA) has been used to implement the optimization model, and simulation results are shown.
Persistent Identifierhttp://hdl.handle.net/10722/214832
ISBN

 

DC FieldValueLanguage
dc.contributor.authorWu, TH-
dc.contributor.authorPang, KH-
dc.contributor.authorChoy, KL-
dc.contributor.authorLam, HY-
dc.date.accessioned2015-08-21T11:57:59Z-
dc.date.available2015-08-21T11:57:59Z-
dc.date.issued2015-
dc.identifier.citationThe 2015 IEEE Transportation Electrification Conference and Expo (ITEC), Dearborn, MI., 14-17 June 2015. In Conference Proceedings, 2015, p. 1-6-
dc.identifier.isbn978-1-4673-6741-7-
dc.identifier.urihttp://hdl.handle.net/10722/214832-
dc.description.abstractIn this paper, a battery swapping station (BSS) model is proposed as an economic and convenient way to provide energy for the batteries of the electric vehicles (EVs). This method would overcome some drawbacks to the use of electric vehicles like long charging time and insufficient running distance. On the economic concern of a battery swapping station, the station would optimize the availability of the batteries in stock, and at the same time determine the best strategy for recharging the batteries on hand. By optimizing the charging method of the batteries, an optimization model of BSS with the maximum number of batteries in stock has been developed for the bus terminal at the Hong Kong International Airport. The secondary objective would be to minimize a cost on the batteries due to the use of different charging schemes. The genetic algorithm (GA) has been used to implement the optimization model, and simulation results are shown.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1804049-
dc.relation.ispartofIEEE Transporation Electrification Conference and Expo (ITEC)-
dc.rightsIEEE Transporation Electrification Conference and Expo (ITEC). Copyright © IEEE.-
dc.rights©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBattery swapping station-
dc.subjectElectric vehicle-
dc.subjectGenetic algorithm-
dc.subjectBattery charging methods-
dc.titleAn optimization model for a battery swapping station in Hong Kong-
dc.typeConference_Paper-
dc.identifier.emailPang, KH: gpang@eee.hku.hk-
dc.identifier.authorityPang, KH=rp00162-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ITEC.2015.7165769-
dc.identifier.hkuros250193-
dc.identifier.spage1-
dc.identifier.epage6-
dc.publisher.placeUnited State-
dc.customcontrol.immutablesml 151008-

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