Microsystem Technologies

, Volume 23, Issue 12, pp 5855–5865 | Cite as

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

  • Cuong C. Nguyen
  • Damith C. Ranasinghe
  • Said F. Al-Sarawi
Technical Paper
  • 177 Downloads

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.

Notes

Acknowledgements

This work is supported by the Department of State Development: Collaboration Pathways Program-South Australia Government (CPP 39).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Centre for Biomedical Engineering, School of Electrical and Electronic EngineeringUniversity of AdelaideAdelaideAustralia
  2. 2.Auto-ID lab, School of Computer ScienceUniversity of AdelaideAdelaideAustralia

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