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

Ahmed Mohamed, Andrew Meintz, Lei Zhu, Eric Wood

Research output: Contribution to conferencePaperpeer-review

6 Scopus Citations

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 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.

Original languageAmerican English
Number of pages10
DOIs
StatePublished - Sep 2019
Event2019 IEEE Industry Applications Society Annual Meeting, IAS 2019 - Baltimore, United States
Duration: 29 Sep 20193 Oct 2019

Conference

Conference2019 IEEE Industry Applications Society Annual Meeting, IAS 2019
Country/TerritoryUnited States
CityBaltimore
Period29/09/193/10/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

NREL Publication Number

  • NREL/CP-5400-73484

Keywords

  • Autonomous Electric Shuttles
  • In-route
  • Optimization
  • Planning
  • Wireless Charging
  • Wireless Power Transfer (WPT)

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