What makes a good public EV charging station? A revealed preference study

To determine the optimal locations for electric vehicle charging stations, optimisation models need to predict which charging stations users will select. We estimate discrete choice models to predict the usage of charging stations using only readily available information for charging network operators. Our parameter values are estimated from a unique, revealed preferences dataset of charging sessions in Montreal, Quebec. We find that user distance to stations, proximity to home areas, and the number of outlets at each station are significant factors for predicting station usage. Additionally, amenities near charging stations have a neutral effect overall, with some users demonstrating strong preference or aversion for these locations. High variability among the preferences of users highlight the importance of models which incorporate panel effects. Moreover, integrating mixed logit models within the optimisation of charging station network design yields high-quality solutions, even when evaluated under other model specifications.

Authors

Publication Details

Journal
Transportation Research Part D Transport and Environment
Published
2025-11-05
DOI
https://doi.org/10.1016/j.trd.2025.105066
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

What makes a good public EV charging station? A revealed preference study

Margarida Carvalho, Steven J. Lamontagne, Emma Frejinger, Ribal Atallah
Transportation Research Part D Transport and Environment
Electric Vehicles and Infrastructure
article

What makes a good public EV charging station? A revealed preference study

Margarida Carvalho, Steven J. Lamontagne, Emma Frejinger, Ribal Atallah
article en

Abstract

To determine the optimal locations for electric vehicle charging stations, optimisation models need to predict which charging stations users will select. We estimate discrete choice models to predict the usage of charging stations using only readily available information for charging network operators. Our parameter values are estimated from a unique, revealed preferences dataset of charging sessions in Montreal, Quebec. We find that user distance to stations, proximity to home areas, and the number of outlets at each station are significant factors for predicting station usage. Additionally, amenities near charging stations have a neutral effect overall, with some users demonstrating strong preference or aversion for these locations. High variability among the preferences of users highlight the importance of models which incorporate panel effects. Moreover, integrating mixed logit models within the optimisation of charging station network design yields high-quality solutions, even when evaluated under other model specifications.

Transportation Research Part D Transport and EnvironmentVol. 149
Openalex Percentile: Top 68%
Electric Vehicles and Infrastructure
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What makes a good public EV charging station? A revealed preference study — Margarida Carvalho, Steven J. Lamontagne, et al. · Transportation Research Part D Transport and Environment (2025) | TGRS Research Map | TGRS