Hybrid energy-storage system for mobile RF energy harvesting wireless sensors

Abstract

This thesis discusses the impact of the supercapacitor size on the performance of the mobile battery-less RF energy harvesting system. The choice of supercapacitor is crucial in mobile systems. The small supercapacitor can charge quickly and activate the sensor in a few seconds in the low-energy area but cannot provide a significant amount of energy to the sensor to do heavy energy tasks such as programming or communication with the base station. On the other hand, large supercapacitors have a sensor node for heavy energy tasks in a high-energy zone but may not be able to activate in a low energy zone. The proposed hybrid energy-storage system contains two supercapacitors of different sizes and a switching circuit. An adaptive-learning switching algorithm controls the switching circuit. This algorithm predicts the available source energy and the period that the sensor node will remain in the high-energy area. The algorithm dynamically switches between the supercapacitors according to available ambient RF energy. Extensive simulation and experiments evaluated the proposed method. The proposed system showed 40% and 80% efficiency over single supercapacitor system in terms of the amount of harvested energy and sensorcoverage.

Date of Award	Jul 2020
Original language	English
Awarding Institution	University of Bedfordshire
Supervisor	Vladimir Dyo (Supervisor) & Vitaly Schetinin (Second supervisor)