Abstract

This study addresses electric mobility, a key pillar of European decarbonisation targets. To foster the adoption of electric vehicles, a widespread and efficient charging infrastructure is essential. However, sizing charging stations remains challenging because it depends on the interaction of many heterogeneous variables that are often analysed in isolation. To overcome this limitation, this study proposes an integrated simulation model that captures these interactions within a single framework, enabling a more realistic assessment of charging-infrastructure design and operation. Following an extensive literature review, a simulation model was developed in Python environment, capable of jointly integrating the key variables identified in the literature. The model was validated against a certified software (EVerest), achieving a mean absolute percentage error of 2.7%, and against real charging session data, with a mean absolute percentage error of 4.3%. The model was then applied to a highway case study, simulating 111 served vehicles. The results show that the considered variables strongly affect quality-of-service metrics. Moreover, a simple management strategy based on a charging-time limit reduced the average waiting time by up to 97% in the tested scenarios.

Overall, these findings confirm the strong interdependence among the main parameters and highlight the need for integrated modeling approaches to support effective and realistic sizing of EV charging infrastructures.