Magnetically Levitated Autoparametric Broadband Vibration Energy Harvesting

Abstract

Some of the lingering challenges within the current paradigm of vibration energy harvesting (VEH) involve narrow operational frequency range and the inevitable non-resonant response from broadband noise excitations. Such VEHs are only suitable for limited applications with fixed sinusoidal vibration, and fail to capture a large spectrum of the real world vibration. Various arraying designs, frequency tuning schemes and nonlinear vibratory approaches have only yielded modest enhancements. To fundamentally address this, the paper proposes and explores the potentials in using highly nonlinear magnetic spring force to activate an autoparametric oscillator, in order to realize an inherently broadband resonant system. Analytical and numerical modelling illustrate that high spring nonlinearity derived from magnetic levitation helps to promote the 2:1 internal frequency matching required to activate parametric resonance. At the right internal parameters, the resulting system can intrinsically exhibit semi-resonant response regardless of the bandwidth of the input vibration, including broadband white noise excitation.

Publication DOI: https://doi.org/10.1088/1742-6596/773/1/012006
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences
Additional Information: Content from this work may be used under the terms of theCreative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd
Publication ISSN: 1742-6596
Last Modified: 20 May 2024 07:29
Date Deposited: 13 Nov 2019 10:34
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Related URLs: https://iopscie ... 96/773/1/012006 (Publisher URL)
PURE Output Type: Conference article
Published Date: 2016-12-06
Accepted Date: 2016-01-01
Authors: Kurmann, Lukas
Jia, Yu (ORCID Profile 0000-0001-9640-1666)
Manoli, Yiannos
Woias, Peter

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