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Intelligent monitoring systems for electric vehicle charging

dc.contributor.authorMartins, Jaime
dc.contributor.authorRodrigues, Joao
dc.date.accessioned2025-03-21T10:32:25Z
dc.date.available2025-03-21T10:32:25Z
dc.date.issued2025-03-04
dc.description.abstractFeatured Application This paper reviews EV charging challenges and existing monitoring methods to pinpoint key gaps. From our review, we propose a practical monitoring framework that leverages IoT sensors, edge computing, and cloud services for real-time oversight, predictive maintenance, and responsive analysis of user behavior.Abstract The growing adoption of electric vehicles (EVs) presents new challenges for managing parking infrastructure, particularly concerning charging station utilization and user behavior patterns. This review examines the current state-of-the-art in intelligent monitoring systems for EV charging stations in parking facilities. We specifically focus on two key inefficiencies: vehicles occupying charging spots beyond the optimal fast-charging range (80% state-of-charge) and remaining connected even after reaching full capacity (100%). We analyze the theoretical and practical foundations of these systems, summarizing existing research on intelligent monitoring architectures and commercial implementations. Building on this analysis, we also propose a novel monitoring framework that integrates Internet of things (IoT) sensors, edge computing, and cloud services to enable real-time monitoring, predictive maintenance, and adaptive control. This framework addresses both the technical aspects of monitoring systems and the behavioral factors influencing charging station management. Based on a comparative analysis and simulation studies, we propose performance benchmarks and outline critical research directions requiring further experimental validation. The proposed architecture aims to offer a scalable, adaptable, and secure solution for optimizing EV charging infrastructure utilization while addressing key research gaps in the field.eng
dc.description.sponsorshipUID/04516/NOVA
dc.identifier.doi10.3390/app15052741
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/10400.1/26938
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.relationCenter for Electronics, Optoelectronics and Telecommunications
dc.relationCenter for Electronics, Optoelectronics and Telecommunications
dc.relation.ispartofApplied Sciences
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectElectric vehicle charging
dc.subjectInfrastructure monitoring
dc.subjectSmart parking systems
dc.subjectEdge computing
dc.subjectInternet of things
dc.subjectPredictive analytics
dc.subjectUser behavior analysis
dc.subjectEnergy management systems
dc.titleIntelligent monitoring systems for electric vehicle chargingeng
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCenter for Electronics, Optoelectronics and Telecommunications
oaire.awardTitleCenter for Electronics, Optoelectronics and Telecommunications
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00631%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00631%2F2020/PT
oaire.citation.issue5
oaire.citation.startPage2741
oaire.citation.titleApplied Sciences
oaire.citation.volume15
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameMartins
person.familyNameRodrigues
person.givenNameJaime
person.givenNameJoao
person.identifier.ciencia-id8A19-98F7-9914
person.identifier.orcid0000-0001-9360-0221
person.identifier.orcid0000-0002-3562-6025
person.identifier.scopus-author-id55061238600
person.identifier.scopus-author-id55807461600
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublicationdc16525e-6025-44b8-ac52-425a8e9e6c06
relation.isAuthorOfPublication683ba85b-459c-4789-a4ff-a4e2a904b295
relation.isAuthorOfPublication.latestForDiscoverydc16525e-6025-44b8-ac52-425a8e9e6c06
relation.isProjectOfPublication6c1217d9-1340-45e8-91d8-e75348854f62
relation.isProjectOfPublication77b70459-1e8c-4a6c-9856-58860aaddb6b
relation.isProjectOfPublication.latestForDiscovery6c1217d9-1340-45e8-91d8-e75348854f62

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