Resonant frequency tuning strategies for vibration-based energy harvesters

Lin Dong, Frank T. Fisher

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Vibration-based energy harvesting has been widely investigated to as a means to generate low levels of electrical energy for applications such as wireless sensor networks. However, due to the fact that vibration from the environment is typically random and varies with different magnitudes and frequencies, it is a challenge to implement frequency matching in order to maximize the power output of the energy harvester with a wider frequency bandwidth for applications where there is a time-dependent, varying source frequency. Possible solutions of frequency matching include widening the bandwidth of the energy harvesters themselves in order to implement frequency matching and to perform resonance-based tuning approach, the latter of which shows the most promise to implement a frequency matching design. Here three tuning strategies are discussed. First a two-dimensional resonant frequency tuning technique for the cantilever-geometry energy harvesting device which extended previous 1D tuning approaches was developed. This 2D approach could be used in applications where space constraints impact the available design space of the energy harvester. In addition, two novel resonant frequency tuning approaches (tuning via mechanical stretch and tuning via applied bias voltage, respectively) for electroactive polymer (EAP) membrane-based geometry energy harvesters was proposed, such that the resulting changes in membrane tension were used to tune the device for applications targeting variable ambient frequency environments.

Original languageEnglish (US)
Title of host publicationDevelopment and Characterization of Multifunctional Materials; Mechanics and Behavior of Active Materials; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791858257
DOIs
StatePublished - 2017
Externally publishedYes
EventASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2017 - Snowbird, United States
Duration: Sep 18 2017Sep 20 2017

Publication series

NameASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2017
Volume1

Conference

ConferenceASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2017
Country/TerritoryUnited States
CitySnowbird
Period9/18/179/20/17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction
  • Mechanics of Materials

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