Interdigitated cantilever array topology for low frequency MEMS vibration energy harvesting

Abstract

Micro-fabricated vibration energy harvesters enable merits such as miniaturisation, economies of scale for manufacturing, and ease of integration with semiconductor IC technologies. However, the frequency range of ambient vibration is generally low (10's Hz to 100's Hz). Existing MEMS vibration energy harvesters that target these frequencies typically are in the centimetre scale range. This sacrifices the miniaturisation aspect as well as introducing new challenges in packaging and integration for the unconventionally large MEMS devices. This paper proposes a new interdigitated fork cantilever array topology, which allows for up to about a third reduction in resonant frequency compared to the classical cantilever topology, for the same design area and without compromising on power optimisation. Further resonant frequency reduction is also possible, but at the expense of power optimisation. This opens up design flexibility to achieve low frequency MEMS resonators that are more suitable to practically target ambient vibration, without sacrificing the aforementioned merits of MEMS technology.

Publication DOI: https://doi.org/10.1088/1742-6596/1052/1/012097
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: 03 Jun 2024 07:38
Date Deposited: 13 Nov 2019 10:14
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Related URLs: https://iopscie ... 6/1052/1/012097 (Publisher URL)
PURE Output Type: Conference article
Published Date: 2018-01-01
Published Online Date: 2017-11-14
Accepted Date: 2017-01-01
Authors: Jia, Yu (ORCID Profile 0000-0001-9640-1666)
Arroyo, Emmanuelle
Du, Sijun
Seshia, Ashwin A

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