Scientific Data, Год журнала: 2025, Номер 12(1)

Опубликована: Март 28, 2025

The recent surge in electric vehicles (EVs), driven by a collective push to enhance global environmental sustainability, has underscored the significance of exploring EV charging prediction. To catalyze further research this domain, we introduce UrbanEV - an open dataset showcasing space availability and electricity consumption pioneering city for vehicle electrification, namely Shenzhen, China. offers rich repository data (i.e., occupancy, duration, volume, price) captured at hourly intervals across extensive six-month span over 20,000 individual stations. Beyond these core attributes, also encompasses diverse influencing factors like weather conditions spatial proximity. Comprehensive experiments have been conducted showcase predictive capabilities various models, including statistical, deep learning, transformer-based approaches, using dataset. This is poised propel advancements prediction management, positioning itself as benchmark resource within burgeoning field.

Язык: Английский