Abstract
The rising demand for electric vehicles (EVs) has highlighted the urgent need for innovative EV charging methods, given the numerous operational and technological challenges. This study introduces an innovative real-time energy allocation model aimed at optimizing the service quality of mobile charging stations (MCSs), an emerging EV charging concept, while ensuring fairness among EV users. We evaluate our approach through case studies considering varying numbers of charging demands, and road traffic congestion status. We incorporate a 24-node Sioux Falls transportation network and real EV parking lot data to ensure practicality. Our results demonstrate the effectiveness of the proposed strategy in terms of quality-of-service (QoS) and fairness scores, even during periods of traffic congestion and high energy demand. Additionally, we conduct sensitivity and scalability analyses to assess the algorithm's decision-making under uncertain EV user behavior regarding reservation requests on a larger scale.