Optimal Deployment of Dynamic Charging Lanes for Plug-in Hybrid Trucks

To effectively implement charging-while-driving (CWD) technology in trucking freight transportation, charging lanes need to be strategically deployed in the road network connecting logistics centers, such as ports, terminals, and distribution centers. The charging lane deployment problem is twofold. First, it is necessary to determine the optimal location for the construction of charging lanes. Second, one must consider the influence of deployed charging lanes on the route choice behaviors of drivers, especially drivers of plug-in hybrid electric trucks (PHETs). The behaviors of drivers in a transportation network are usually described with a user equilibrium (UE) assignment model. Although a number of studies have formulated UE models considering electric vehicles (e.g., Jiang et al., 2012, 2014; He et al., 2014, 2015, 2016; Chen et al., 2016), none of them are capable of describing the behaviors of PHET drivers in a network with charging lanes. An electric motor has much higher energy efficiency than an internal combustion engine (ICE), and as a result, PHET drivers can significantly reduce fuel costs by consuming electricity instead of petroleum fuel (Granovskii et al., 2006; Nanaki and Koroneos, 2013; USDOE, 2017). Therefore, PHET drivers may simultaneously consider travel time and fuel costs when traveling from their origin to their destination and may prefer routes with charging lanes. These two problems should be treated simultaneously in a network setting.

Language

  • English

Project

  • Status: Active
  • Funding: $119468
  • Contract Numbers:

    69A3551747108

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Project Managers:

    Kline, Robin

  • Performing Organizations:

    Utah State University, Logan

    Civil and Environmental Engineering Department
    Logan, UT  United States  84332
  • Principal Investigators:

    Song, Ziqi

    Singleton, Patrick

  • Start Date: 20171211
  • Expected Completion Date: 20220731
  • Actual Completion Date: 0
  • Source Data: MPC-558

Subject/Index Terms

Filing Info

  • Accession Number: 01656117
  • Record Type: Research project
  • Source Agency: Mountain-Plains Consortium
  • Contract Numbers: 69A3551747108
  • Files: UTC, RiP
  • Created Date: Jan 3 2018 9:57AM