As clean energy vehicles, electric vehicles (EVs) have been paid unprecedented attention in dealing with serious energy crises and heavy tailpipe emission in recent years. Due to its limited battery range and long charging time, it's significant to reasonably determine the locations and capacities of EV charging infrastructure. There are two research gaps in existing researches: unrealistically assuming the infinite queuing length based on the M/M/1 or M/M/S queuing model and lacking the research on variable quantities of chargers allocated at different charging stations. To fill up these gaps, we propose an optimal location model to determine the optimal locations and capacities of EV charging infrastructure to minimize the comprehensive total cost, which considers the charging queuing behavior with finite queue length and various siting constrains. And the results show that (1) the proposed model has a good performance in determining the optimal locations and capacities of EV charging infrastructure (i.e. the optimal locations of charging stations, the optimal quantities of chargers installed at each charging station, the optimal allowable maximum queue length and maximum capacity of each charging station); (2) the quantity of chargers and allowable maximum queue length at each charging station are consistent with the distribution densities of existing charging stations at these locations; (3) the two parameters of unit value of time and unit distance cost have a more significant impact on the total cost. Therefore, the total cost can be effectively reduced by appropriately increasing the quantity of chargers at each charging station and the distribution density of charging stations.

作为清洁能源汽车，近年来，电动汽车（EV）在处理严重的能源危机和严重的排气管排放方面受到了前所未有的关注。由于电池范围有限且充电时间长，因此合理确定EV充电基础设施的位置和容量非常重要。现有研究存在两个研究空白：不现实地假设基于M / M / 1或M / M / S的无限排队长度排队模型，缺乏对不同充电站分配的可变数量充电器的研究。为了填补这些空白，我们提出了一种最佳位置模型，以确定电动汽车充电基础设施的最佳位置和容量，以最大程度地降低综合成本，该模型考虑了具有有限队列长度和各种选址约束的充电排队行为。结果表明：（1）所提出的模型在确定电动汽车充电基础设施的最佳位置和容量方面具有良好的性能（例如，充电站的最佳位置，每个充电站安装的最佳充电器数量，最佳允许最大值）。每个充电站的队列长度和最大容量）；（2）每个充电站的充电器数量和允许的最大排队长度与这些位置上现有充电站的分配密度一致；（3）时间单位价值和单位距离成本这两个参数对总成本有较大的影响。因此，通过适当地增加每个充电站处的充电器的数量和充电站的分布密度，可以有效地降低总成本。