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Go Electric! – Recent CSAI work advances electric vehicle usage

Published: 22nd November 2022 Last updated: 22nd November 2022

A paper on forecasting the availability of charging stations for electric vehicles written by CSAI researchers has been accepted for publication at this year’s BNAIC/Benelearn conference. The paper, authored by Stijn Rotman and Boris Čule, has been presented at the conference in Mechelen, Belgium, in early November, 2022.

While still relatively small, the market for electric cars is growing rapidly. The advent of electric driving poses novel scientific challenges. One such challenge is predicting the availability of electric vehicle charging points. Not being able to find an available charging point can be a frustrating experience. It is therefore not surprising that an increase in charger availability has a positive effect on the uptake of electric driving, which is something we should strive for. As a result, being able to accurately forecast when and where charging points will be available is crucial for advancing electric vehicle usage.

Previous work in this area made use of insufficient data sources, limiting the usefulness of state-of-the-art data analytics. In this paper, the authors make use of a much larger amount of data from various sources across Europe, opening the door to more powerful algorithms previously unused in this domain. The data used is especially suited for prediction using deep learning models, because of the high number of similar charging points present in the data.

Several algorithms designed specifically for predicting the future based on historical trends have been compared in their ability to predict the availability of a charging point in a given hour. The performed experiments demonstrated that the algorithms are capable of accurately predicting charging point availability. The authors hope their work will help charging point providers improve the availability of charging points, leading to more people using electric vehicles and, ultimately, reducing the carbon footprint of transport and travel.

The full paper is available online at https://research.tilburguniversity.edu/files/65404465/Forecasting_Elect…

Stijn J. Rotman and Boris Čule. Forecasting Electric Vehicle Supply Equipment Availability. Benelux Conference on Artificial Intelligence (BNAIC/Benelearn), 2022.