Abstract
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.
| Original language | English |
|---|---|
| Article number | e0302132 |
| Number of pages | 19 |
| Journal | PLoS ONE |
| Volume | 19 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 26 Apr 2024 |
Funding
This research is a part of the Future Charging project funded by SIA RAAK (NWO). Project number: RAAK.PRO03.128. https://regieorgaan-sia.nl/v I am grateful for the collaboration and data provision from all partners involved. Partner cities Amsterdam, Utrecht, The Hague and Rotterdam have provided the relevant data and have thought along with relevant predictor variables and provided feedback on early results. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.