Research Area:  Wireless Sensor Networks
This thesis discusses the impact of the super capacitor size on the performance of the mobile battery-less RF energy harvesting system. The choice of super capacitor is crucial in mobile systems. The small super capacitor 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 super capacitors 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 super capacitors 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 super capacitors according to available ambient RF energy. Extensive simulation and experiments evaluated the proposed method. The proposed system showed 40% and 80% efficiency over single super capacitor system in terms of the amount of harvested energy and sensor coverage.
Name of the Researcher:  Bilal Munir
Name of the Supervisor(s):  Vladimir Dyo
Year of Completion:  2020
University:  University of Bedfordshire
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