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Advances in Acoustics and Vibration
Volume 2013 (2013), Article ID 241025, 12 pages
Research Article

Experimental Analysis of a Piezoelectric Energy Harvesting System for Harmonic, Random, and Sine on Random Vibration

Health Monitoring and Radio Frequency Sensing Team, Pacific Northwest National Laboratory, P.O. Box 999, Richland, WA 99352, USA

Received 17 April 2013; Revised 28 June 2013; Accepted 1 July 2013

Academic Editor: K. M. Liew

Copyright © 2013 Jackson W. Cryns et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Harvesting power with a piezoelectric vibration powered generator using a full-wave rectifier conditioning circuit is experimentally compared for varying sinusoidal, random, and sine on random (SOR) input vibration scenarios; the implications of source vibration characteristics on harvester design are discussed. The rise in popularity of harvesting energy from ambient vibrations has made compact, energy dense piezoelectric generators commercially available. Much of the available literature focuses on maximizing harvested power through nonlinear processing circuits that require accurate knowledge of generator internal mechanical and electrical characteristics and idealization of the input vibration source, which cannot be assumed in general application. Variations in source vibration and load resistance are explored for a commercially available piezoelectric generator. The results agree with numerical and theoretical predictions in the previous literature for optimal power harvesting in sinusoidal and flat broadband vibration scenarios. Going beyond idealized steady-state sinusoidal and flat random vibration input, experimental SOR testing allows for more accurate representation of real world ambient vibration. It is shown that characteristic interactions from more complex vibration sources significantly alter power generation and processing requirements by varying harvested power, shifting optimal conditioning impedance, inducing voltage fluctuations, and ultimately rendering idealized sinusoidal and random analyses incorrect.