Analytical modeling and optimization of electret-based microgenerators under sinusoidal excitations
Date
2017
Authors
Nguyen, C.
Ranasinghe, D.
Al-Sarawi,
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Microsystem Technologies: micro and nanosystems information storage and processing systems, 2017; 23(12):5855-5865
Statement of Responsibility
Cuong C. Nguyen, Damith C. Ranasinghe, Said F. Al, Sarawi
Conference Name
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.
School/Discipline
Dissertation Note
Provenance
Description
Electret-based microgenerators under sinusoidal excitations: an analytical modeling
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© Springer-Verlag Berlin Heidelberg 2017