ABSTRACT Electric vehicles (EVs) frequently encounter prolonged waiting times for charging at highway service areas particularly during holidays, resulting in a poor user experience. Aimed at enhancing the service quality of the charging stations while minimizing their operating and investment costs, a cost‐effective and waiting times‐aware charging strategy for EVs is proposed. Initially, a varying rate charging model is employed to dynamically adjust the charging rate based on the queue length of EVs at charging stations. The charging process of EVs is subsequently modeled using a Markov modulated poisson process (MMPP), and the charging time for EVs is calculated by M/MMPP/C queuing model. The steady‐state probability distribution is derived through the quasi‐birth‐and‐death process and matrix‐geometric method. Finally, numerical simulations are conducted to analyze the influence of parameters on the performance of charging stations. The results indicate that the performance can be optimized by selecting appropriate parameters to adjust the charging rate. As the EV arrival rate increased from 5 to 13, the average queuing time of EVs in M/MMPP/C model decreased by 8.38%. Compared to the M/M/C model, the M/MMPP/C model can reduce the battery degradation cost by up to 50.29 RMB/kWh.
Zhang et al. (2026) studied this question.