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

Abstract

Deploying shared automated electric vehicles (SAEVs) on current roadways in cities will significantly shape current transportation systems and make our urban mobility systems more efficient, convenient, and environmentally friendly. Utilizing wireless power transfer (WPT) technology to charge the SAEVs provides perfect fits for realizing a fully automated mobility system. However, the investment in wireless charging infrastructure (WCI) presents a critical barrier for commercializing and adopting this technology. The barrier can be cleared by realizing the proper design of the WPT system that maximizes the benefits and minimizes the cost of WCI at the same time. This paper introduces a system design optimization tool and methodology for WCI for serving fixed-route SAEVs in automated mobility districts (AMDs). The tool offers the capability of integrating driving data (simulated or collected from the real world), vehicle parameters (e.g., battery, motor, dimensions, and so on), and wireless charger characteristics (rate, locations, alignment, and so on) to generate energy and state-of-charge profiles for each vehicle, considering motoring, regenerative braking, and charging. Furthermore, the proposed tool incorporates a multi-objective optimization layer for searching the optimum design parameters based on predefined objectives and constraints. The proposed method was utilized to design the WCI for a hypothetical AMDmore » scenario with four SAEVs. The outcomes show that implementing in-route wireless chargers at designated stops for the SAEVs with maximum power level has the potential to provide a charge sustaining operation with 52% reduction in the on-board battery and presents the most cost-effective solution. The proposed solution is assessed in comparison with other charging technologies, such as stationary WPT and dc fast charging, and it shows the most feasible option for an AMD network in terms of cost, convenience, and performance.« less

Authors:
ORCiD logo; ; ORCiD logo
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1812774
Alternate Identifier(s):
OSTI ID: 1559426
Report Number(s):
NREL/JA-5400-73772
Journal ID: ISSN 2169-3536; 8734845
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Published Article
Journal Name:
IEEE Access
Additional Journal Information:
Journal Name: IEEE Access Journal Volume: 7; Journal ID: ISSN 2169-3536
Publisher:
Institute of Electrical and Electronics Engineers
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; automated mobility district; in-route; shared automated electric vehicles; wireless charging infrastructure; wireless power transfer

Citation Formats

Mohamed, Ahmed A. S., Meintz, Andrew, and Zhu, Lei. System Design and Optimization of In-Route Wireless Charging Infrastructure for Shared Automated Electric Vehicles. United States: N. p., 2019. Web. https://doi.org/10.1109/ACCESS.2019.2920232.
Mohamed, Ahmed A. S., Meintz, Andrew, & Zhu, Lei. System Design and Optimization of In-Route Wireless Charging Infrastructure for Shared Automated Electric Vehicles. United States. https://doi.org/10.1109/ACCESS.2019.2920232
Mohamed, Ahmed A. S., Meintz, Andrew, and Zhu, Lei. Tue . "System Design and Optimization of In-Route Wireless Charging Infrastructure for Shared Automated Electric Vehicles". United States. https://doi.org/10.1109/ACCESS.2019.2920232.
@article{osti_1812774,
title = {System Design and Optimization of In-Route Wireless Charging Infrastructure for Shared Automated Electric Vehicles},
author = {Mohamed, Ahmed A. S. and Meintz, Andrew and Zhu, Lei},
abstractNote = {Deploying shared automated electric vehicles (SAEVs) on current roadways in cities will significantly shape current transportation systems and make our urban mobility systems more efficient, convenient, and environmentally friendly. Utilizing wireless power transfer (WPT) technology to charge the SAEVs provides perfect fits for realizing a fully automated mobility system. However, the investment in wireless charging infrastructure (WCI) presents a critical barrier for commercializing and adopting this technology. The barrier can be cleared by realizing the proper design of the WPT system that maximizes the benefits and minimizes the cost of WCI at the same time. This paper introduces a system design optimization tool and methodology for WCI for serving fixed-route SAEVs in automated mobility districts (AMDs). The tool offers the capability of integrating driving data (simulated or collected from the real world), vehicle parameters (e.g., battery, motor, dimensions, and so on), and wireless charger characteristics (rate, locations, alignment, and so on) to generate energy and state-of-charge profiles for each vehicle, considering motoring, regenerative braking, and charging. Furthermore, the proposed tool incorporates a multi-objective optimization layer for searching the optimum design parameters based on predefined objectives and constraints. The proposed method was utilized to design the WCI for a hypothetical AMD scenario with four SAEVs. The outcomes show that implementing in-route wireless chargers at designated stops for the SAEVs with maximum power level has the potential to provide a charge sustaining operation with 52% reduction in the on-board battery and presents the most cost-effective solution. The proposed solution is assessed in comparison with other charging technologies, such as stationary WPT and dc fast charging, and it shows the most feasible option for an AMD network in terms of cost, convenience, and performance.},
doi = {10.1109/ACCESS.2019.2920232},
journal = {IEEE Access},
number = ,
volume = 7,
place = {United States},
year = {2019},
month = {1}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1109/ACCESS.2019.2920232

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Cited by: 8 works
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