Understanding the linkage between electric vehicle charging network coverage and charging opportunity using GPS travel data

Eleftheria Kontou, Changzheng Liu, Fei Xie, Xing Wu, Zhenhong Lin

Research output: Contribution to journalArticlepeer-review

Abstract

Using GPS travel survey data from three metropolitan areas, this paper estimates the relationship between plug-in electric vehicle (PEV) public charging infrastructure coverage and charging opportunity. The former is defined as the percentage of public areas with charging stations installed and the latter represents the drivers probability of accessing a public charger at their trip stops (stop-based) or during at least one stop of their travel day (trip chain-based). Understanding this relationship is important to PEV manufacturers and electric vehicle supply equipment (EVSE) providers, as well as government agencies, for evaluating different levels of EVSE deployment and estimating the impact of its availability on PEV adoption. Heuristic procedures are developed to estimate stop- and trip chain-based charging opportunities. Charging opportunity reflects the visibility of EVSE as the incremental security that charging stations enable, while evaluating the potential of a driver to access EVSE at travel stops or during the day, for different levels of EVSE deployment on the transportation network. The metrics proposed do not assess the probability of completing trips with electric vehicles of a given range. The analysis results indicate that drivers’ trip destinations concentrate in a few popular places and EVSE deployment in these areas could achieve relatively high levels of charging opportunity. This finding is also robust to regional variations.

Original languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalTransportation Research Part C: Emerging Technologies
Volume98
DOIs
StatePublished - Jan 2019
Externally publishedYes

Keywords

  • Charging coverage
  • Charging infrastructure
  • Charging opportunity
  • Electric vehicle

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications

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