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Title: Optimum Planning for Inductively Charged On-Demand Automated Electric Shuttles at Greenville, South Carolina

Abstract

Wireless charging technology presents perfect fits 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 integer planning optimization problem is formulated. A comprehensive cost function representing the inductively charged SAESs 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 realizing charge sustaining operation. The planning platform incorporates representative simulated traffic data (drive cycles and routes) for four SAESs at Greenville project using the Simulation of Urban Mobility (SUMO) 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 (SOC) profiles, which are provided to the search algorithm to assess the design objectives under specific constraints. The results indicated that implementing wireless charging at amore » few designated stops for fixed-route SAESs with proper design allows the vehicles realizing 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 Laboratory (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1583088
Report Number(s):
NREL/CP-5400-73484
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2019 IEEE Industry Applications Society Annual Meeting, 29 September - 3 October 2019, Baltimore, Maryland
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, Zhu, Lei, Meintz, Andrew L, and Wood, Eric W. Optimum Planning for Inductively Charged On-Demand Automated Electric Shuttles at Greenville, South Carolina. United States: N. p., 2019. Web. doi:10.1109/IAS.2019.8912343.
Mohamed, Ahmed A, Zhu, Lei, Meintz, Andrew L, & Wood, Eric W. Optimum Planning for Inductively Charged On-Demand Automated Electric Shuttles at Greenville, South Carolina. United States. https://doi.org/10.1109/IAS.2019.8912343
Mohamed, Ahmed A, Zhu, Lei, Meintz, Andrew L, and Wood, Eric W. 2019. "Optimum Planning for Inductively Charged On-Demand Automated Electric Shuttles at Greenville, South Carolina". United States. https://doi.org/10.1109/IAS.2019.8912343.
@article{osti_1583088,
title = {Optimum Planning for Inductively Charged On-Demand Automated Electric Shuttles at Greenville, South Carolina},
author = {Mohamed, Ahmed A and Zhu, Lei and Meintz, Andrew L and Wood, Eric W},
abstractNote = {Wireless charging technology presents perfect fits 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 integer planning optimization problem is formulated. A comprehensive cost function representing the inductively charged SAESs 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 realizing charge sustaining operation. The planning platform incorporates representative simulated traffic data (drive cycles and routes) for four SAESs at Greenville project using the Simulation of Urban Mobility (SUMO) 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 (SOC) profiles, which are provided to the search algorithm to assess the design objectives under specific constraints. The results indicated that implementing wireless charging at a few designated stops for fixed-route SAESs with proper design allows the vehicles realizing 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/IAS.2019.8912343},
url = {https://www.osti.gov/biblio/1583088}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {11}
}

Conference:
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