  This paper compares two prevalent charging strategies for electric vehicles,
plug-in charging and battery swapping, to investigate which charging strategy
is superior for electric autonomous mobility-on-demand (AMoD) systems. To this
end, we use a queueing-theoretic model to characterize the vehicle waiting time
at charging stations and battery swapping stations, respectively. The model is
integrated into an economic analysis of the electric AMoD system operated by a
transportation network company (TNC), where the incentives of passengers, the
charging/operating shift of TNC vehicles, the operational decisions of the
platform, and the planning decisions of the government are captured. Overall, a
bi-level optimization framework is proposed for charging infrastructure
planning of the electric AMoD system. Based on the proposed framework, we
compare the socio-economic performance of plug-in charging and battery
swapping, and investigate how this comparison depends on the evolving charging
technologies (such as charging speed, battery capacity, and infrastructure
cost). At the planning level, we find that when choosing plug-in charging,
increased charging speed leads to a transformation of infrastructure from
sparsely distributed large stations to densely distributed small stations,
while enlarged battery capacity transforms the infrastructure from densely
distributed small stations to sparsely distributed large stations. On the other
hand, when choosing battery swapping, both increased charging speed and
enlarged battery capacity will lead to a smaller number of battery swapping
stations. At the operational level, we find that improved charging speed leads
to increased TNC profit when choosing plug-in charging, whereas improved
charging speed may lead to smaller TNC profit under battery swapping. The above
insights are validated through realistic numerical studies.
