Lindsay M. Miller

Lindsay Miller, PhD 2012
Advisor: Paul Wright

Passively Self-Tuning Beam-Mass System for Frequency-Insensitive Vibration Energy Harvesting for Wireless Sensor Networks

There is a growing demand for autonomous wireless sensor networks, especially as power requirements for radio transmitters and microprocessors decrease. For applications such as smart buildings and smart manufacturing—where sensor nodes must be remotely located, widely distributed, numerous and low-maintenance, and flexibility in node placement is desired—energy harvesting to power the sensor nodes is appealing. Ambient vibrations are a ubiquitous source of
energy in the built environment, even where solar or thermal energy are not consistently available. When a piezoelectric cantilever is mounted on a vibration source, such as a motor or HVAC duct, it experiences deformation that in turn generates a voltage potential. Energy harvesters, combined with a battery and capacitor that can be trickle-charged, have the potential to provide wireless sensor nodes with a continuously replenishable power supply. MEMS piezoelectric vibration energy harvesters with resonance frequencies 31-232 Hz have been fabricated, characterized, and tested on ambient vibration sources in the machine room of a large building (see photos). The best device had an average power output of 1.8 nW. An optimization was then conducted, finding that 1-10 μW can be produced from a harvester 1 cm2 in area with optimized dimensions. Still, this result is unsatisfactory because the energy harvester only produces power at its resonance frequency (see plot) while we would like it to produce power at any frequency within a specified range. Current research is focused on developing a passively self-tuning beam mass system in order to develop an energy harvester whose performance is insensitive to the frequency of the ambient vibrations to be harvested. Preliminary experiments have shown promising results and mathematical modeling is nearly complete, which will provide a more rich understanding of the dynamic system.

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