Centre of Expertise Applied Artificial Intelligence

Identifying factors that influence electric vehicle charging station performance in expanding networks

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Charging infrastructure deployment has taken off in many cities with the rise of the number of electric vehicles on the road. Expansion of infrastructure is a matter of prioritisation of resources to optimise the infrastructure. This paper explores how to measure charging station performance, to address the challenges that policy makers face. These performance indicators are used in a regression model, based upon current utilisation of the network, to predict which charging stations perform best. The results show that a model based on available geographical data and performance metrics of the current network are best combined to predict infrastructure performance. The variability between public charging stations is however big, as frequent user characteristics do determine the performance to a large extent.

Reference Wolbertus, R. (2024). Identifying factors that influence electric vehicle charging station performance in expanding networks. PLoS ONE , 19(4), Article e0302132. https://doi.org/10.1371/journal.pone.0302132
Published by  Faculty of Technology 26 April 2024

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Apr 2024

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