期刊
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
卷 97, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trd.2021.102943
关键词
Shared electric vehicles; Car-sharing; Battery swap station; Data-driven approach; Trajectory data; Infrastructure deployment
资金
- Hong Kong Polytechnic University [1-BE2J]
- National Natural Science Foundation of China [52002345, 52072025]
This paper introduces a novel Station-to-Point Battery Swap Mode for Shared Electric Vehicles, and develops a data-driven BSS location optimization model and operation strategy. Key parameters including Q, R, and AADT were found influential to the outputs of interest through various scenarios.
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.
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