Statement of contribution: This study is the first to systematically and quantitatively explore the factors that determine the length of charging sessions at public charging stations for electric vehicles in urban areas. We use a unique and large data set – containing information concerning 3.7 million charging sessions of 84,000 (i.e., 70% of) Dutch EV-users – in which both private users and taxi and car sharing vehicles are included; thus representing a large variation in charging duration behavior. Based on a estimation of a series of mixed logit- and latent class-based ordinal regression models, we identify key factors explaining heterogeneity in charging duration behavior across charging stations. We show how these explanatory variables can be used to predict EV-charging behavior in urban areas and to optimize types and numbers of charging infrastructure.
|Number of pages
|Published - 2018
|IATBR 2018: 15th International Conference on Travel Behaviour Research - Santa Barbara, United States
Duration: 15 Jul 2018 → 20 Jul 2018
Conference number: 15
|IATBR 2018: 15th International Conference on Travel Behaviour Research
|15/07/18 → 20/07/18