Energy Modeling of Wearable Intelligent Batteryless Health Monitoring System with Thermal-Vibrational Hybrid Harvester

Sharone, Molly
A unified model is developed in this thesis with a thermal-vibrational hybrid energy harvester and a wearable intelligent batteryless health monitoring system for accurate prediction of energy flow from generation to consumption. Analytical models are developed first based on environmental conditions, energy conversion parameters, geometry, and datasheet specifications. Data from literature is utilized from multiple energy harvesters, interface electronics, the intelligent sensor nodes and monitored patients to tune correlation factors for model accuracy. The resulting system level framework, named HeMeS, effectively enables the development of wearable batteryless sensor systems across a large design space by investigating tradeoffs among operation conditions, processing and transmission performance, size, and cost. Multiple threads of analysis have been successfully showcased using HeMeS to demonstrate convergence to an optimized autonomous (batteryless) system design with hybrid thermal and vibrational energy harvesting under a variety of environment, cost, size and patient constraints applicable to different health monitoring WBAN nodes.


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Citation Formats
M. Sharone, “Energy Modeling of Wearable Intelligent Batteryless Health Monitoring System with Thermal-Vibrational Hybrid Harvester,” M.S. - Master of Science, Middle East Technical University, 2021.