Research Papers

Chaotification as a Means of Broadband Energy Harvesting With Piezoelectric Materials

[+] Author and Article Information
Daniel Geiyer

Department of Mechanical and
Aerospace Engineering,
University of Central Florida,
Orlando, FL 32816
e-mail: daniel.geiyer@knights.ucf.edu

Jeffrey L. Kauffman

Department of Mechanical and
Aerospace Engineering,
University of Central Florida,
Orlando, FL 32816
e-mail: JLKauffman@ucf.edu

1Corresponding author.

Contributed by the Technical Committee on Vibration and Sound of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received November 10, 2014; final manuscript received March 3, 2015; published online April 27, 2015. Assoc. Editor: Mohammed Daqaq.

J. Vib. Acoust 137(5), 051005 (Oct 01, 2015) (8 pages) Paper No: VIB-14-1435; doi: 10.1115/1.4030024 History: Received November 10, 2014; Revised March 03, 2015; Online April 27, 2015

Component miniaturization and reduced power requirements in sensors have enabled growth in the field of low-power ambient vibration energy harvesting. This work aims to increase bandwidth and power output beyond current techniques by inducing chaotic nonlinear phenomena and applying a low-power controller based on the method of Ott, Grebogi, and Yorke (OGY) to stabilize a chosen periodic orbit. Previously, researchers used a nonlinear piezomagnetoelastic beam in search of a large amplitude broadband voltage response, but chaos was strictly avoided. These large amplitude responses can deteriorate over time into low energy chaotic oscillations. Including chaos as a desirable property allows small perturbations to alter the behavior of a system dramatically, improving the dynamic response for energy harvesting. The nonlinear piezomagnetoelastic beam element described by a Duffing oscillator is extended to embrace chaotic motion more actively. By driving motion along a chaotic attractor, even single frequency excitation results in a theoretically infinite number of unstable periodic orbits that can be stabilized using small control inputs. The chosen orbit will be accessible from a large range of excitation frequencies and can be dynamically changed in real-time, potentially expanding the bandwidth of operation.

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Fig. 2

Piezomagnetoelastic beam configuration

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Fig. 1

Example of using a small perturbation to stabilize a periodic orbit

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Fig. 3

Time series and Poincaré section comparison of discrete (L) and continuous (R) counterparts

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Fig. 4

First return map (n = 1) for tip displacement of the augmented Duffing oscillator

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Fig. 5

OGY control applied to the piezomagnetoelastic beam. (a) Time series response with OGY control and (b) phase portrait with the stabilized orbit.

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Fig. 6

Poincaré section of the controlled response

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Fig. 7

Orbit comparison with (a) the large amplitude response, (b) the phase portrait of the chaotic uncontrolled system, (c) the controlled chaotic orbit, and (d) the representative linear harvester



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