This study develops a taxi trajectory data based fast-charging facility planning model for an urban taxi system by considering battery degradation and vehicle heterogeneity in driving range. The developed model comprises three functional modules: (i) fast-charging location determination, (ii) fast-charging facility deployment (FCFD) and (iii) FCFD solution tuning. Under the FCFD module, charging demand prediction considering battery degradation and vehicle heterogeneity, charging demand allocation and charger configuration optimization are executed sequentially. The FCFD solution is tuned by an effective backward elimination method to find a more economic and practical planning solution where the minimal number of chargers at each station can be specified. A case study in Singapore is thoroughly conducted, and insightful policy implications are revealed: policy-makers could use the tuning mechanism to significantly save investment and reduce total waiting time for charging; overlooking battery degradation and vehicle heterogeneity will yield a biased electric taxi charging facility planning.

这项研究通过考虑电池劣化和行驶范围内的车辆异质性，开发了一种基于出租车轨迹数据的城市出租车系统快速充电设施规划模型。开发的模型包含三个功能模块：（i）快速充电位置确定，（ii）快速充电设施部署（FCFD）和（iii）FCFD解决方案调整。在FCFD模块下，依次执行考虑电池退化和车辆异质性的充电需求预测，充电需求分配和充电器配置优化。通过有效的后向消除方法对FCFD解决方案进行调整，以找到一种更经济实用的计划解决方案，其中可以指定每个站点的最小充电器数量。在新加坡进行的个案研究已全面展开，并揭示了深刻的政策含义：决策者可以使用调整机制来显着节省投资并减少充电的总等待时间；忽视电池退化和车辆异质性将导致电动出租车充电设施规划有偏差。