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Article: An Optimization Model for Electric Vehicle Battery Charging at a Battery Swapping Station

TitleAn Optimization Model for Electric Vehicle Battery Charging at a Battery Swapping Station
Authors
Keywordsbattery charging
Battery swapping stations
electric vehicles
optimization algorithms
Issue Date2018
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25
Citation
IEEE Transactions on Vehicular Technology, 2018, v. 67 n. 2, p. 881-895 How to Cite?
AbstractA new model for a viable battery swapping station is proposed to minimize its cost by determining the optimized charging schedule for swapped electric vehicle (EV) batteries. The aim is to minimize an objective function considering three factors: the number of batteries taken from stock to serve all the swapping orders from incoming EVs, potential charging damage with the use of high-rate chargers, and electricity cost for different time period of the day. A mathematical model is formulated for the charging process following the constant-current/constant-voltage charging strategy. An integrated algorithm is proposed to determine an optimal charging schedule, which is inspired by genetic algorithm, differential evolution, and particle swarm optimization. A series of simulation studies are executed to assess the feasibility of the proposed model and compare the performance between the proposed algorithm and the typical evolutionary algorithms.
Persistent Identifierhttp://hdl.handle.net/10722/259320
ISSN
2021 Impact Factor: 6.239
2020 SCImago Journal Rankings: 1.365
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWu, H-
dc.contributor.authorPang, GKH-
dc.contributor.authorChoy, KL-
dc.contributor.authorLam, HY-
dc.date.accessioned2018-09-03T04:05:10Z-
dc.date.available2018-09-03T04:05:10Z-
dc.date.issued2018-
dc.identifier.citationIEEE Transactions on Vehicular Technology, 2018, v. 67 n. 2, p. 881-895-
dc.identifier.issn0018-9545-
dc.identifier.urihttp://hdl.handle.net/10722/259320-
dc.description.abstractA new model for a viable battery swapping station is proposed to minimize its cost by determining the optimized charging schedule for swapped electric vehicle (EV) batteries. The aim is to minimize an objective function considering three factors: the number of batteries taken from stock to serve all the swapping orders from incoming EVs, potential charging damage with the use of high-rate chargers, and electricity cost for different time period of the day. A mathematical model is formulated for the charging process following the constant-current/constant-voltage charging strategy. An integrated algorithm is proposed to determine an optimal charging schedule, which is inspired by genetic algorithm, differential evolution, and particle swarm optimization. A series of simulation studies are executed to assess the feasibility of the proposed model and compare the performance between the proposed algorithm and the typical evolutionary algorithms.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25-
dc.relation.ispartofIEEE Transactions on Vehicular Technology-
dc.rights©2017 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.subjectbattery charging-
dc.subjectBattery swapping stations-
dc.subjectelectric vehicles-
dc.subjectoptimization algorithms-
dc.titleAn Optimization Model for Electric Vehicle Battery Charging at a Battery Swapping Station-
dc.typeArticle-
dc.identifier.emailPang, GKH: gpang@eee.hku.hk-
dc.identifier.authorityPang, GKH=rp00162-
dc.description.naturepostprint-
dc.identifier.doi10.1109/TVT.2017.2758404-
dc.identifier.scopuseid_2-s2.0-85030751780-
dc.identifier.hkuros289915-
dc.identifier.volume67-
dc.identifier.issue2-
dc.identifier.spage881-
dc.identifier.epage895-
dc.identifier.isiWOS:000425666800004-
dc.publisher.placeUnited States-
dc.identifier.issnl0018-9545-

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