Optimizing Electric Vehicle Charging Schedules: Minimizing Charging Time and Travel Distance

Growing concerns regarding climate change have led to the development of sustainable transportation solutions. Electric vehicles (EVs) offer a promising alternative to traditional combustion engine vehicles due to their efficiency and reduced environmental impact. However, unlike gasoline-powered vehicles, EVs require longer charging times, introducing limitations on charging accessibility and overall travel time. This study addresses these challenges by proposing an EV charging scheduling model to achieve two objectives: minimizing the time spent on EV charging and reducing the travel distance between charging stations and the final destination. Notably, the proposed method is model-free, eliminating the need for data-driven training processes. The model's efficacy is evaluated through a simulation study utilizing a virtual map and real-world charging station data from Bangkok, Thailand. The simulation results demonstrate significant improvements in scheduling efficiency compared to baseline strategies. The proposed approach achieves 208% and 308% charging time reductions compared to the nearest neighbor station (NNS) and earliest start time (EST) policies.