Citation

Philipsen R, Brell T, Brost W, Eickels T, Ziefle M. Transp. Res. F Traffic Psychol. Behav. 2018; 59: 475-492.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.trf.2018.09.024

PMID

unavailable

Abstract

The demand-oriented establishment of a charging infrastructure is crucial for the deep market penetration of electric vehicles. In order to identify specific optimal locations for charging stations, a deeper understanding of the users' charging behavior is required. For reliable simulations and forecasts, it is not only necessary to take the charging behavior of the current early-adopter group into account, but also to compare it with the current refueling behavior of those, who could switch to electric vehicles in the near and medium-term future. The study follows a two-stage research approach. First of all, qualitative interviews (N=24) were conducted to identify refueling behavior in terms of behavioral patterns, refueling motives and conditions. The second step involves a quantitative comparison of the refueling and charging behavior with regard to conditions, frequencies and critical levels. A large-scale questionnaire study (N=1021) with car drivers from Germany was carried out for this purpose. The results showed that the conditions for a refueling or charging decision only differ partially. While financial aspects play a minor role for e-vehicle users, for internal combustion engine users planning and habit are less important. There is no difference between the two groups regarding range-relevant factors. In particular, the filling level perceived as critical is identical for fuel tanks and batteries. In terms of behavior patterns, e-vehicle users tend to charge consumed quantities in a timely manner, while users of vehicles with combustion engines often run on empty and then refill the tank completely. Only a few predictors for both behaviors could be identified. While socio-demographic factors hardly play a role, socio-economy and vehicle utilization are the biggest predictors. The results are incorporated into the modeling of potential users when planning new charging infrastructure.

Language: en

Keywords

Battery electric vehicles; Charging behavior; Critical fill level; Motivational factors; Traditional refueling; User profiles