  Electric scooters are becoming immensely popular across the world as a means
of reliable transportation around many cities. As these e-scooters rely on
batteries, it is important to understand how many of these e-scooters have
enough battery life to transport riders and when these e-scooters might require
a battery replacement. To this end, we develop the first stochastic model to
capture the battery life dynamics of e-scooters of a large scooter network. In
our model, we assume that e-scooter batteries are removable and replaced by
agents called swappers. Thus, to gain some insight about the large scale
dynamics of the system, we prove a mean field limit theorem and a functional
central limit theorem for the fraction of e-scooters that lie in a particular
interval of battery life. Exploiting the mean field limit and the functional
central limit theorems, we develop an algorithm for determining the number of
swappers that are needed to guarantee levels of probabilistic performance of
the system. Finally, we show through a stochastic simulation and real data that
our stochastic model captures the relevant dynamics.
