Instrumented electromagnetic generator: Optimized performance by automatic self-adaptation of the generator structure
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....
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Veröffentlicht in: | Mechanical systems and signal processing 2022-05, Vol.171, p.108898, Article 108898 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 0888-3270 1096-1216 |
DOI: | 10.1016/j.ymssp.2022.108898 |