System Design and Optimization of In-Route Wireless Charging Infrastructure for Shared Automated Electric Vehicles

Mohamed, Azah; Meintz, Andrew; Zhu, Lei

doi:10.1109/access.2019.2920232

Cited by 30 publications

(11 citation statements)

References 28 publications

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“…Considering the OLEV shuttling system developed at KAIST, Lee et al [34] studied a Markov decision process-based optimization algorithm using reinforcement learning to estimate optimal battery capacities, pickup capacity and the number of ITUs. Mohamed et al [35] focused their work on the integration of a wireless charging system with automated driving. Iliopoulou and Kepaptsoglou [36] design a bi-level optimization related to a transit route network design and a charging infrastructure location problem in public transport.…”

Section: Related Literature and Research Questionsmentioning

confidence: 99%

Designing Dynamic Inductive Charging Infrastructures for Airport Aprons with Multiple Vehicle Types

et al. 2022

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In the effort to combat climate change, the CO2 emissions of the aviation sector must be reduced. The traffic caused by numerous types of ground vehicles on airport aprons currently contributes to those emissions as the vehicles typically operate with combustion engines, which is why an electrification of those vehicles has already begun. While stationary conductive charging of the vehicles is the current standard technology, dynamic wireless charging might be an attractive technological alternative, in particular for airport aprons; however, designing a charging network for an airport apron is a challenging task with important technical and economic aspects. In this paper, we propose a model to characterize the problem, especially for cases of multiple types of vehicles sharing the same charging network, such as passenger buses and baggage vehicles. In a numerical study inspired by real-world airports, we design such charging networks subject to service level constraints and evaluate the resulting structures via a discrete-event simulation, and thus, show the way to assess the margin of safety with respect to the vehicle batteries’ state of charge that is induced by the spatial structure of the charging network.

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Section: Related Literature and Research Questionsmentioning

confidence: 99%

Designing Dynamic Inductive Charging Infrastructures for Airport Aprons with Multiple Vehicle Types

et al. 2022

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“…FASTSim is a microscopic powertrain energy simulation tool developed at NREL which has been widely used in various applications ( 26 , 32 – 34 ). FASTSim has been calibrated and validated against vehicle test data to provide accurate energy efficiency estimates for a variety of vehicle powertrains, including conventional gasoline and electric vehicle designs.…”

Section: Description Of the Amd Modeling And Simulation Toolkitmentioning

confidence: 99%

Decision Support Tool for Planning Neighborhood-Scale Deployment of Low-Speed Shared Automated Shuttles

Zhu

Wang

Garikapati

et al. 2020

Transportation Research Record: Journal of the Transportation R

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Increasing interest and investment in connected, automated, and electric vehicles as well as mobility-as-a-service (MaaS) concepts are paving the way for the next major transformation in transportation through automated and shared mobility. The initial excitement toward rapid deployment and adoption of automated vehicles (AVs) has subsided, and low-speed automated shuttles are emerging as a more pragmatic pathway for introducing automated mobility in geofenced districts. Such shuttles hold the promise to provide a viable alternative for serving short trips in urban districts with high travel densities. As interest in low-speed automated shuttle systems (to improve urban mobility) increases, the need for tools that can inform communities in relation to benefits or disadvantages of automated shuttle deployments is imminent. However, most of the existing transportation planning and simulation tools are not capable of handling emerging shared automated mobility options. This paper presents a microscopic simulation toolkit that can be used by cities and communities to plan for the deployment of low-speed automated shuttles systems, as well as other shared mobility options. Labeled as the Automated Mobility District modeling and simulation toolkit, the proposed decision support tool intends to help cities evaluate the mobility and sustainability impacts of deploying shared automated vehicles (SAVs) in geofenced regions. This paper describes the toolkit, as well as a sample scenario analysis for the deployment of low-speed automated shuttles in Greenville, South Carolina, U.S. Results from the scenario study demonstrate the effectiveness of the proposed simulation toolkit in planning for advanced mobility systems.

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“…systems for long-distance applications [11,58]. Future System design considerations [59], traffic simulations with high charging power and shared CAEV [60] show an interesting prospective. Advanced energy management concepts like vehicular energy have been proposed [61].…”

Section: Prospectivesmentioning

confidence: 99%

Dynamic Wireless Power Transfer Charging Infrastructure for Future EVs: From Experimental Track to Real Circulated Roads Demonstrations

Laporte

Coquery

Deniau³

et al. 2019

WEVJ

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In a context of growing electrification of road transport, Wireless Power Transfer (WPT) appears as an appealing alternative technology as it enables Electric Vehicles (EVs) to charge while driving and without any mechanical contact (with overhead cables or rails in the ground). Although the WPT technology background dates from the end of 20th century, recent advances in semiconductor technologies have enabled the first real demonstrations. Within the FABRIC European project, the French research Institute VEDECOM and its partners implemented a whole prototype wireless power transfer charging infrastructure. The first demonstrations of Inductive WPT in different real driving conditions (up to 20 kW, from 0 to 100 km/h, with one or two serial vehicles) were provided. This paper describes the prototype equipment and its instrumentation and provides the system characterization results. The future of the Inductive WPT technology is further discussed considering its different technical and economic challenges. In parallel, how this technology could be part of future generation road infrastructures is discussed. Future research and demonstration steps are presented in the conclusion.

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System Design and Optimization of In-Route Wireless Charging Infrastructure for Shared Automated Electric Vehicles

Cited by 30 publications

References 28 publications

Designing Dynamic Inductive Charging Infrastructures for Airport Aprons with Multiple Vehicle Types

Designing Dynamic Inductive Charging Infrastructures for Airport Aprons with Multiple Vehicle Types

Decision Support Tool for Planning Neighborhood-Scale Deployment of Low-Speed Shared Automated Shuttles

Dynamic Wireless Power Transfer Charging Infrastructure for Future EVs: From Experimental Track to Real Circulated Roads Demonstrations

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