Spatial planning of electric vehicle infrastructure for Belo Horizonte, Brazil

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dc.contributor.author Costa, Evaldo
dc.contributor.author Paiva, Arthur
dc.contributor.author Seixas, Julia
dc.contributor.author Costa, Gustavo
dc.contributor.author Baptista, Patricia
dc.contributor.author Ó Gallachóir, Brian P.
dc.date.accessioned 2019-05-22T09:31:44Z
dc.date.available 2019-05-22T09:31:44Z
dc.date.issued 2018-12-19
dc.identifier.citation Costa, E., Paiva, A., Seixas, J., Costa, G., Baptista, P. and Gallachóir, B.Ó., 2018. Spatial Planning of Electric Vehicle Infrastructure for Belo Horizonte, Brazil. Journal of Advanced Transportation, 2018, 8923245 (16pp). DOI: 10.1155/2018/8923245 en
dc.identifier.volume 2018 en
dc.identifier.startpage 1 en
dc.identifier.endpage 16 en
dc.identifier.issn 0197-6729
dc.identifier.uri http://hdl.handle.net/10468/7962
dc.identifier.doi https://doi.org/10.1155/2018/8923245 en
dc.description.abstract In pursuit of a more sustainable transportation system, electric vehicles (EVs) have the potential to play a fundamental role due to their improved efficiency and lower emissions. The absence of an adequate electric vehicle supply equipment (EVSE) network has been one of the major obstacles for the mass adoption of EV, in large municipalities of developing countries. This is the case in Belo Horizonte (BH), Brazil, which also has a high motorization rate (7 light-duty vehicles per 10 inhabitants). The purpose of this study is to measure and identify the optimal locations for EVSE according to selected criteria to meet the needs of light-duty electric vehicles (LDEV) corresponding to a penetration of 1% by 2025 in the municipality of BH. The study highlights the most important attributes that need to be considered for the installation of an EVSE network in an urban space for a developing country. Multi-Criteria Decision Making (MCDM), the Weighted Linear Combination (WLC) method, and the Analytical Hierarchy Process (AHP) technique based on the inputs from a group of Brazilian electrical mobility specialists, coupled with a Geographic Information System (GIS) modeling tool, were used for this study. The results revealed that around 1,200 EVSE units are needed, with a large concentration of EVSE in a small region. We also illustrate where stakeholders should focus their attention for the successful promotion of EV. The development methodology has the potential to be applied in other future EVSE development projects. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Hindawi en
dc.relation.uri https://www.hindawi.com/journals/jat/2018/8923245/
dc.rights © 2018 Evaldo Costa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. en
dc.rights.uri https://creativecommons.org/licenses/by/4.0/ en
dc.subject Electric vehicle en
dc.subject Sustainable transportation en
dc.subject Spatial planning en
dc.title Spatial planning of electric vehicle infrastructure for Belo Horizonte, Brazil en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Brian Ó Gallachóir, Department of Civil, Structural and Environmental Engineering, University College Cork, Cork, Ireland. +353-21-490-3000 Email: b.ogallachoir@ucc.ie en
dc.internal.availability Full text available en
dc.description.version Published Version en
dc.contributor.funder Fundação para a Ciência e a Tecnologia en
dc.description.status Peer reviewed en
dc.identifier.journaltitle Journal of Advanced Transportation en
dc.internal.IRISemailaddress b.ogallachoir@ucc.ie en
dc.identifier.articleid 8923245 en
dc.relation.project info:eu-repo/grantAgreement/FCT/5876/147329/PT/Laboratory for Robotics and Engineering Systems/UID/EEA/50009/2013 en
dc.relation.project info:eu-repo/grantAgreement/FCT/5665-PICT/137220/PT/SusCity: Urban data driven models for creative and resourceful urban transitions/MITP-TB/CS/0026/2013 en
dc.identifier.eissn 2042-3195


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© 2018 Evaldo Costa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Except where otherwise noted, this item's license is described as © 2018 Evaldo Costa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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