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Title: Planning Optimization for Inductively Charged On-demand Automated Electric Shuttles Project at Greenville, South Carolina

Abstract

Wireless charging technology presents an ideal fit for autonomous electric vehicles for realizing a fully automated system (vehicle and charger). This paper presents a planning optimization analysis for a pilot project of in-route wireless charging infrastructure serving fixed-route on-demand shared automated electric shuttles (SAESs) at Greenville, South Carolina, USA. A single-objective non-linear mixed integer system planning optimization problem is formulated. A comprehensive cost model representing the overall inductively charged SAESs system is developed, considering road construction, power electronics and materials, traction battery, and installation costs. The optimization problem is solved to determine the best combination of the system key design parameters (number and allocations of wireless chargers, charging power level, track length and on-board battery capacity) that show the most cost-effective solution and allow the SAESs to achieve charge-sustaining operation. The planning platform incorporates representative simulated traffic data (driving speed and routes) for four SAESs in the Greenville using the Simulation of Urban Mobility tool. These data are fed to a vehicle powertrain model and a wireless charger power model to predict the battery power, energy and state-of-charge profiles, which are provided to the search algorithm to assess the design objectives under specific constraints. Finally, the results indicate that implementingmore » high-power (100 kW) wireless charger at a few designated stops for fixed-route SAESs with the proper track length allows the vehicles to realize charge-sustaining operation, infinite range, and zero recharge downtime, with a significant reduction in the on-board battery (36%) and road coverage (69%), at minimum cost.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States). Center for Integrated Mobility Sciences
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1583091
Report Number(s):
NREL/JA-5400-74341
Journal ID: ISSN 0093-9994; MainId:18226;UUID:81726684-13a7-e911-9c24-ac162d87dfe5;MainAdminID:6704
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Industry Applications
Additional Journal Information:
Journal Volume: 56; Journal Issue: 2; Journal ID: ISSN 0093-9994
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; autonomous electric shuttles; dynamic wireless charging; fixed route; optimization; wireless power transfer; WPT

Citation Formats

Mohamed, Ahmed A. S., Zhu, Lei, Meintz, Andrew L, and Wood, Eric W. Planning Optimization for Inductively Charged On-demand Automated Electric Shuttles Project at Greenville, South Carolina. United States: N. p., 2019. Web. https://doi.org/10.1109/TIA.2019.2958566.
Mohamed, Ahmed A. S., Zhu, Lei, Meintz, Andrew L, & Wood, Eric W. Planning Optimization for Inductively Charged On-demand Automated Electric Shuttles Project at Greenville, South Carolina. United States. https://doi.org/10.1109/TIA.2019.2958566
Mohamed, Ahmed A. S., Zhu, Lei, Meintz, Andrew L, and Wood, Eric W. Mon . "Planning Optimization for Inductively Charged On-demand Automated Electric Shuttles Project at Greenville, South Carolina". United States. https://doi.org/10.1109/TIA.2019.2958566. https://www.osti.gov/servlets/purl/1583091.
@article{osti_1583091,
title = {Planning Optimization for Inductively Charged On-demand Automated Electric Shuttles Project at Greenville, South Carolina},
author = {Mohamed, Ahmed A. S. and Zhu, Lei and Meintz, Andrew L and Wood, Eric W},
abstractNote = {Wireless charging technology presents an ideal fit for autonomous electric vehicles for realizing a fully automated system (vehicle and charger). This paper presents a planning optimization analysis for a pilot project of in-route wireless charging infrastructure serving fixed-route on-demand shared automated electric shuttles (SAESs) at Greenville, South Carolina, USA. A single-objective non-linear mixed integer system planning optimization problem is formulated. A comprehensive cost model representing the overall inductively charged SAESs system is developed, considering road construction, power electronics and materials, traction battery, and installation costs. The optimization problem is solved to determine the best combination of the system key design parameters (number and allocations of wireless chargers, charging power level, track length and on-board battery capacity) that show the most cost-effective solution and allow the SAESs to achieve charge-sustaining operation. The planning platform incorporates representative simulated traffic data (driving speed and routes) for four SAESs in the Greenville using the Simulation of Urban Mobility tool. These data are fed to a vehicle powertrain model and a wireless charger power model to predict the battery power, energy and state-of-charge profiles, which are provided to the search algorithm to assess the design objectives under specific constraints. Finally, the results indicate that implementing high-power (100 kW) wireless charger at a few designated stops for fixed-route SAESs with the proper track length allows the vehicles to realize charge-sustaining operation, infinite range, and zero recharge downtime, with a significant reduction in the on-board battery (36%) and road coverage (69%), at minimum cost.},
doi = {10.1109/TIA.2019.2958566},
journal = {IEEE Transactions on Industry Applications},
number = 2,
volume = 56,
place = {United States},
year = {2019},
month = {12}
}

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