A User-Preference-Based Charging Station Recommendation for Electric Vehicles

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Abstract
The popularity of electric vehicles (EVs) is increasing, leading to higher demand for electric vehicle charging stations (EVCS). It is crucial to select an appropriate charging station based on user preferences; however, current selection solutions are limited and primarily focus on proximity or price. Such an approach neglects other significant factors of interest to EV users, namely charging time, waiting time, charging cost, and available facilities near the EVCS. To address this issue, this paper proposes a novel recommendation scheme, the User-Preferences based Charging Station Recommendation Scheme (UPCSRS), which integrates user preferences with Multiple Attribute Decision Making (MADM) theory to suggest the best available charging stations for EV users. UPCSRS consists of two parts: adopting Analytical Hierarchical Process (AHP) for weighting the importance of each selection criterion and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for ranking available charging stations. A mathematical model of the proposed scheme was developed, and then the effectiveness and accuracy were evaluated using MATLAB and a real dataset from the US Department of Energy website. Results showed that this proposed scheme provides more precise and personalized recommendations for users compared to current solutions that only consider the nearest or cheapest option. By enhancing the overall user experience through a more customized and efficient charging station selection process, this proposed scheme has the potential to contribute to more EVs adoption.

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