Modelling energy changes in the energy harvesting battery of an IoT device

The complexity of battery-powered autonomous devices 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.