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Erschienen in: Microsystem Technologies 12/2017

16.03.2017 | Technical Paper

Analytical modeling and optimization of electret-based microgenerators under sinusoidal excitations

verfasst von: Cuong C. Nguyen, Damith C. Ranasinghe, Said F. Al-Sarawi

Erschienen in: Microsystem Technologies | Ausgabe 12/2017

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Abstract

Small scale electrostatic energy harvesters or microgenerators have attracted much interest due to their compatibility with micro-electro-mechanical-system (MEMS) fabrication processes and the possibility to energize wireless sensors and actuators through harvesting movement or vibration from surrounding environment. Several analytical models have been developed to estimate the performance of electret-based microgenerators. However, most of these studies focused on constant-speed rotations, while in practice, mechanical stimuli resemble sinusoidal vibrations. Consequently, a combination of finite element modeling and numerical methods has been the primary approach to analyze and optimize the performance of electret-based microgenerators. Both approaches are time-consuming, costly and more importantly, limit the understanding of design trade-offs involved. In this paper, we present an analytical model that accurately predicts the output voltage and effective power generated by electret-based microgenerators under small sinusoidal excitations. The developed model is validated using numerical simulations that show a good agreement with measured results published in the literature. We also employ the analytical model to optimize the microgenerator by investigating the effects of electret thickness, air gap spacing between the two plates of the microgenerator, and electret surface potential with respect to material properties.

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Metadaten
Titel
Analytical modeling and optimization of electret-based microgenerators under sinusoidal excitations
verfasst von
Cuong C. Nguyen
Damith C. Ranasinghe
Said F. Al-Sarawi
Publikationsdatum
16.03.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Microsystem Technologies / Ausgabe 12/2017
Print ISSN: 0946-7076
Elektronische ISSN: 1432-1858
DOI
https://doi.org/10.1007/s00542-017-3349-1

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