Power Subsystem Design and Management for Solar Energy Harvesting Embedded Systems

Wireless Sensor Networks (WSN) have reached a level of maturity, at which they have become a feasible option for monitoring processes of interest, when wired infrastructure is not possible. Due to remote and inaccessible deployment sites of such networks, they can generally not rely on reliable power sources, but require batteries to supply the energy for the system to perform its intended task. However, the finite energy store imposed by batteries directly limits the system’s performance and lifetime. Ambient energy harvesting has been shown to be a promising way to boost the performance and lifetime of WSNs. Unfortunately, enhancing a battery powered device with energy harvesting capabilities will by itself neither provide a lower bound on the expected sustainable performance level, nor guarantee uninterrupted long-term operation. This thesis addresses the design and runtime management of the power subsystem for solar energy harvesting embedded systems. We demonstrate that for enabling long-term operation of such systems, a paradigm shift both in the design approach, and the runtime management of the energy is necessary. We provide an end-to-end power management solution, which consists of (i) a power subsystem capacity planning approach, and (ii) two novel dynamic power management schemes that maximize the minimum achievable performance level, while ensuring that long-term, i.e., multi-year operation can be sustained. Compared to three State-of-the-Art approaches, our solution maximizes the longterm sustainable minimum system performance or perform equivalently, but require a smaller solar panel and/or smaller battery. Our theoretical results are supported by simulations using 10 years of solar energy measurements from various geographical locations. To demonstrate the improvements of proper power subsystem design and management, we further present a case study with a real-world WSN deployment for geoscientific research in a high-alpine environment. Specifically, this thesis presents the following contributions to the State-of-the-Art: • We present a systematic method for power subsystem capacity planning, i.e., proper sizing of the solar panel and battery, for solar energy harvesting embedded systems.