Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/33311
Title: | Instrumented electromagnetic generator: optimized performance by automatic self-adaptation of the generator structure |
Author: | Carneiro, Pedro M. R. Vidal, João V. Rolo, Pedro Peres, Inês Ferreira, Jorge A. F. Kholkin, Andrei L. Santos, Marco P. Soares dos |
Keywords: | Energy generation Self-powering Electromagnetic generator Magnetic levitation Adaptive generator Resonance tuning |
Issue Date: | 15-May-2022 |
Publisher: | Elsevier |
Abstract: | Electromagnetic generators are widely used to power both small-scale and large-scale devices. They are suitable to operate as self-powering technologies, allowing customizable upscaling and downscaling, ensuring low production and maintenance costs, and even able to integrate into hybrid solutions. As their architectures are well-suited to power a broad range of multifunctional devices, their performance optimization is a research topic of utmost importance. Their performance, strongly dependent on the frequency and amplitude of mechanical excitations and hysteretic behaviors, still needs to be improved. In this paper, a theoretical and experimental study is provided to demonstrate the effectiveness of a new concept of self-adaptive electromagnetic generator. An instrumented generator using a magnetic levitation architecture was implemented using a stepper motor, an accelerometer and a processing system. Self-adaptability was realized by changing the generator’s effective length and resonance frequency as a function of the mechanical excitation characteristics. Considering the power consumption of instrumentation, output power gains around 30% were achieved under conditions of harmonic inputs with time changing frequencies and amplitudes. These are very promising results that highlight the potential of self-adaptive energy harvesting technologies for opening new research directions towards the emerging of a new line of highly sophisticated autonomous generators. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/33311 |
DOI: | 10.1016/j.ymssp.2022.108898 |
ISSN: | 0888-3270 |
Publisher Version: | https://www.sciencedirect.com/science/article/pii/S0888327022000863 |
Appears in Collections: | TEMA - Artigos CICECO - Artigos DFis - Artigos DEM - Artigos I3N-FSCOSD - Artigos |
Files in This Item:
File | Description | Size | Format | |
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Manuscript.pdf | 2.97 MB | Adobe PDF |
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