Patent and latent predictors of electric vehicle charging behavior

Nicolò Daina*, John W. Polak, Aruna Sivakumar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)

Abstract

To anticipate the impacts of electric vehicle (EV) charging on grid systems and the effectiveness of demand response measures for load control, it is critical to understand the determinants of EV charging demand. Previous research suggests that these determinants include both observable patent metrics of travel demand and less easily measurable triggers of charging decisions (such as range appraisal or habit). Nevertheless, analyses accounting simultaneously for both aspects are lacking. Data are used from a survey administered to EV drivers participating in the Low Carbon London EV trial to explore charging decision triggers to test their predictive power of observable metrics of charging demand, while controlling for variability in travel patterns. Results show that charging demand is significantly affected by travel pattern metrics as well as charging decision triggers.

Original languageEnglish
Pages (from-to)116-123
Number of pages8
JournalTransportation Research Record
Volume2502
Issue number1
DOIs
Publication statusPublished - 1 Jan 2015

Funding

This work was supported in part by the UK Engineering and Physical Sciences Research Council. The authors thank UK Power Networks for permission to use the data from the Low Carbon London electric vehicle experience questionnaire. The authors are also grateful to the anonymous reviewers, whose insightful comments contributed to the amelioration of this paper.

Keywords

  • electric vehicle charging
  • grid systems
  • travel pattern metrics

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