Energy Harvesting for Self-Sufficient Distributed Systems - Investigation into Power Generation in Self-Powered Sensor Networks
Final Report Abstract
Energy harvesting systems (EHS) are structures which collect energy from their ambient environment and convert it into electrical energy. The technology is a strong contender for an alternative to batteries in various applications requiring low power. Stochastic resonance energy harvesting systems (SR-EHS) have been proposed on a conceptual level, but the lack of a rigorous theory and numerical analysis tools has hampered the implementation of real-life applications. The goal of the project was to construct a novel generalized theoretical framework (macro-model) describing bi- and multi-stable systems driven by noise. The aim was to develop theoretical and numerical analysis and synthesis tools for the study and design of SR-EHS. A generalized model description of non-linear systems employing stochastic resonance was developed. The framework is unified in the sense that it can be applied to all systems independently of dimensionality, topology or parameter dependence. A comprehensive simulation program was created to test and evaluate the developed theory. The numerical tests verified the model as a correct representation of stochastic resonance in higher dimensional systems. The work detailed herein represents the preliminary steps of a larger effort aimed at the development of a computer-aided-design environment geared towards simulation of noise-driven, non-linear systems. These numerical tools could prove critical for the design and optimization of non-linear energy harvester devices.
