Energy Harvesting from Triboelectric and Piezoelectric Nanogenerators for Self-Power Electronics

  • Fandi Jean

Student thesis: Master's Thesis

Abstract

In the current era of technology, with rapid developments in mobile devices and the Internet of Things (IoT), there is a heightened demand for sustainable energy sources. Energy harvesting presents itself as a compelling alternative, poised to diminish the reliance on conventional energy methods and decrease costs and maintenance needs. Among the various energy harvesting techniques, mechanical energy harvesting is particularly attractive due to its widespread availability and potential for conversion into electrical power. This provides a vast source of unused energy that may be transformed into electrical power. In the realm of mechanical energy conversion, Triboelectric and Electromagnetic Nanogenerators (TENGs and EMGs) stand out. These devices capture mechanical energy from the environment and convert it into a reliable option to energize low-power electronic devices. The study explores the capability of these nanogenerators to harness surrounding mechanical energy and convert it into a dependable electrical energy source for powering electronic devices. The research thoroughly examines the design, fabrication, and evaluation of TENGs and EMGs, focusing on the intricacies of selecting materials and configuring structures to improve their efficiency and effectiveness. The core of this study is developing a combined nanogenerator system that effectively integrates the distinct characteristics of TENG and EMGs synergistically. The combined system demonstrates enhanced performance compared to its predecessors by combining the high voltage generating capabilities of TENGs with the significant current output of EMGs. Moreover, the thesis explores potential future directions in energy management and storage technologies, focusing on tackling the persistent problem of impedance mismatch, which has long hindered the integration of TENGs and EMGs.
Date of Award8 May 2024
Original languageAmerican English
SupervisorBaker Mohammad (Supervisor)

Keywords

  • Energy harvesting
  • TENG
  • EMG
  • power management

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