The complexity of battery-powered autonomous de-
vices such as Internet of Things (IoT) nodes or Unmanned Aerial
Vehicles (UAV) and the necessity to ensure an acceptable quality
of service, reliability, and security, have significantly increased
their energy demand. In this paper, we discuss using a diffusion
approximation process to approximate the dynamic changes in
the energy content of a battery. We consider the case when
energy harvesting sources are constantly charging the battery.
The model assumes a probabilistic consumption and delivery of
energy, giving the time-dependent distributions of the energy at
the battery, of the time remaining until it becomes empty, the
time required to charge the battery to its total capacity, or the
time it is operational between two moments of complete depletion.
When possible, we compare the diffusion approximation results
with corresponding Markovian models.