Research on Mobile Cloud Computing Services for Electric Vehicle Charging Facilities

Yan, Zhao

doi:10.14257/ijgdc.2016.9.7.23

Cited by 2 publications

(1 citation statement)

References 9 publications

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“…The cloud architectures in TOSCs should be potent to tackle the traffic spikes and surges in the xEV demand occurred under emergencies and adversaries. Efficient mobile cloud computing strategies leveraged with data driven demand prediction algorithms can circumvent the scalability concerns caused due to continuous evolution in the xEV network [33].…”

Section: Scalabilitymentioning

confidence: 99%

Federated Cloud Analytics Frameworks in Next Generation Transport Oriented Smart Cities (TOSCs) - Applications, Challenges and Future Directions

Hussain¹,

Alam²,

Beg³

2018

EAI Endorsed Transactions on Smart Cities

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Electric, plug-in electric and plug-in hybrid electric vehicles (xEVs) are receiving a global attention from automotive industries, vehicle vendors, R&D organizations, power sectors and policymakers in the intelligent transportation era. Penetration of xEV fleet into the contemporary charging infrastructure(s) in the absence of robust integration network imbalances the power grid and potentially jeopardize the execution of emerging distributed generation systems. However, smart grid technologies in collaboration with smart charging management strategies can circumvent such operational disparities, thus enabling a reliable, efficient, consistent and optimal electric energy management in the power system. This work employs the notion of Cloud of Things (CoT) to propose a comprehensive cloud aware Transport Oriented Smart City (TOSC) framework intended to provide intelligent solutions to the contemporary transportation infrastructures in the emerging sustainable smart cities. The proposed work also demonstrates a commercially viable vehicle to cloud (V2C) fleet charging framework for charging management of xEVs through micro grids/ smart grid. The unprecedented data breeding across V2C, cloud to grid (C2G) and grid to vehicle (G2V) bidirectional communication interfaces elucidates the need for computationally efficient analytics. A state-of-the-art Big-Data to Knowledge (B2K) workflow structure is thus proposed for translating the generated data into efficient knowledge for noble decisions and inferences. Finally, the substantial Mobility as a service (MaaS) adoption challenges and data science prospects are outlined along with the emerging technologies that can co-work with the proposed framework to ensure commercial viability and optimal implementation in emerging TOSCs.

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Section: Scalabilitymentioning

confidence: 99%

Federated Cloud Analytics Frameworks in Next Generation Transport Oriented Smart Cities (TOSCs) - Applications, Challenges and Future Directions

Hussain¹,

Alam²,

Beg³

2018

EAI Endorsed Transactions on Smart Cities

View full text Add to dashboard Cite

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An Optimal Cloud Based Electric Vehicle Charging System

Chimakurthi

2021

Asia Pac. j. energy environ.

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With the evolution of the internet-of-things and the emergence of cloud computing, the charging dynamics of vehicles have changed. This work discusses cloud-based monitoring and management used in charging electric vehicles and their impact on the smart charging system. Charging management plays a key role in assessing the charging infrastructure because of the automakers and charging service providers. As the market evolves, this system looks at the present public and private sectors that provide charging stations and contrasts them with modern cloud-based charging in electric vehicles. The cloud module developed contains layers, with the top layer of the robust calculating ability, which is globally optimized using machine learning technology. The bottom layer counters the real-time issues with the controller. The system also analyzes the current demands in the market and forms strategies to maximize profits through smart charging systems.

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Research on Mobile Cloud Computing Services for Electric Vehicle Charging Facilities

Abstract: Abstract

Cited by 2 publications

References 9 publications

Federated Cloud Analytics Frameworks in Next Generation Transport Oriented Smart Cities (TOSCs) - Applications, Challenges and Future Directions

Federated Cloud Analytics Frameworks in Next Generation Transport Oriented Smart Cities (TOSCs) - Applications, Challenges and Future Directions

An Optimal Cloud Based Electric Vehicle Charging System

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