Deploying battery swap stations for shared electric vehicles using trajectory data

被引:59
作者
Yang, Xiong [1 ]
Shao, Chunfu [2 ]
Zhuge, Chengxiang [1 ]
Sun, Mingdong [2 ]
Wang, Pinxi [3 ]
Wang, Shiqi [1 ]
机构
[1] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hung Hom, Kowloon, Hong Kong, Peoples R China
[2] Beijing Jiaotong Univ, Key Lab Transport Ind Big Data Applicat Technol C, 3 Shangyuancun, Beijing 100044, Peoples R China
[3] Beijing Transport Inst, 9 LiuLiQiao South Lane, Beijing 100073, Peoples R China
基金
中国国家自然科学基金;
关键词
Shared electric vehicles; Car-sharing; Battery swap station; Data-driven approach; Trajectory data; Infrastructure deployment; LOCATION-ROUTING PROBLEM; CAR-SHARING SYSTEMS; CHARGING STATIONS; OPTIMIZATION FRAMEWORK; TRAVEL PATTERNS; TAXI; INFRASTRUCTURE; MANAGEMENT; DEPLOYMENT; ALGORITHM;
D O I
10.1016/j.trd.2021.102943
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper proposed a novel Station-to-Point (S2P) Battery Swap Mode for Shared Electric Vehicles (SEVs), under which Battery Swap Stations (BSSs) have dedicated delivery vehicles transporting new/used batteries between BSSs and Battery Swapping Demand (BSD) points. We further developed a data-driven BSS location optimization model and day-to-day operation strategy, using a one-month GPS trajectory dataset containing 514 actual SEVs in Beijing. We set up 53 scenarios to test the model. In the baseline scenario, we found that the SEV fleet needed 15 BSSs, and each SEV, on average, needed 1.202 batteries and 0.031 delivery vehicles with the centralized management strategy applied. Through "what-if" scenarios, we found that the key parameters Q (the coverage rate of BSD points), R (the service radius of a BSS), and AADT (the acceptable average delay time) were influential to the outputs of interest.
引用
收藏
页数:26
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