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MEMS electrostatic micropower generator for low frequency operation

Mitcheson, P.D., Miao, P., Stark, B.H., Yeatman, E.M., Holmes, A.S., Green, T.C.·2004·Sensors and Actuators A: Physical

Abstract

This paper describes the analysis, simulation and testing of a microengineered motion-driven power generator, suitable for application in sensors within or worn on the human body. Micro-generators capable of powering sensors have previously been reported, but these have required high frequency mechanical vibrations to excite a resonant structure. However, body-driven movements are slow and irregular, with large displacements, and hence do not effectively couple energy into such generators. The device presented here uses an alternative, non-resonant operating mode. Analysis of this generator shows its potential for the application considered, and shows the possibility to optimise the design for particular conditions. An experimental prototype based on a variable parallel-plate capacitor operating in constant charge mode is described which confirms the analysis and simulation models. This prototype, when precharged to 30 V, develops an output voltage of 250 V, corresponding to 0.3J per cycle. The experimental test procedure and the instrumentation are also described.

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Metadata

Authors
Mitcheson, P. D., Miao, P., Stark, B. H., Yeatman, E. M., Holmes, A. S., & Green, T. C.
Venue
Sensors and Actuators A: Physical
Publisher
Elsevier BV
Published
2004-09
Volume
115
Issue
2-3
Pages
523-529
ISSN
0924-4247 (ISSN-L)
OpenAlex
W2110434860
Cited by
593
References
0
FWCI
21.39
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: MEMS electrostatic micropower generator for low frequency operation. https://app.cochat.ai/papers/10.1016/j.sna.2004.04.026
The paper
Mitcheson, P. D., Miao, P., Stark, B. H., Yeatman, E. M., Holmes, A. S., & Green, T. C. (2004). MEMS electrostatic micropower generator for low frequency operation. Sensors and Actuators A: Physical. https://doi.org/10.1016/j.sna.2004.04.026

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.