TY - JOUR
T1 - Deploying battery swap stations for shared electric vehicles using trajectory data
AU - Yang, Xiong
AU - Shao, Chunfu
AU - Zhuge, Chengxiang
AU - Sun, Mingdong
AU - Wang, Pinxi
AU - Wang, Shiqi
N1 - Funding Information:
This work was supported by the Hong Kong Polytechnic University [1-BE2J], and the National Natural Science Foundation of China (52002345; 52072025).
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/8
Y1 - 2021/8
N2 - 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.
AB - 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.
KW - Battery swap station
KW - Car-sharing
KW - Data-driven approach
KW - Infrastructure deployment
KW - Shared electric vehicles
KW - Trajectory data
UR - http://www.scopus.com/inward/record.url?scp=85109127449&partnerID=8YFLogxK
U2 - 10.1016/j.trd.2021.102943
DO - 10.1016/j.trd.2021.102943
M3 - Journal article
AN - SCOPUS:85109127449
SN - 1361-9209
VL - 97
JO - Transportation Research Part D: Transport and Environment
JF - Transportation Research Part D: Transport and Environment
M1 - 102943
ER -