Automated electromagnetic generator with self-adaptive structure by coil switching

• Autor(a) principal: Vidal, João V.
• Data de Publicação: 2022
• Outros Autores: Rolo, Pedro, Carneiro, Pedro M. R., Peres, Inês, Kholkin, Andrei L., Santos, Marco P. Soares dos
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/35342
• topic: Energy harvesting; Self-powering; Electromagnetic generator; Magnetic levitation; Adaptive generator; Non-linear resonance

Self-powered electronic devices have been widely sought after in the last few years demanding efficient harvesting of locally available forms of energy. Electromagnetic generators are suitable contenders for powering both small-scale and large-scale devices due to their widespread availability and customizability. New promising magnet levitation architectures for mechanical vibration energy harvesting offer low production and maintenance costs, as well as a wide array of designs. They also exhibit complex non-linear and hysteretic resonant behaviors. Nonetheless, their performance is typically optimized towards external excitations with very specific characteristics. In this study, we theoretically and experimentally prove the concept of an instrumented self-adaptive levitation generator with on/off coil switching employing an accelerometer, transmission gate switches and a processing system. This adaptable system is able to periodically turn off coils not contributing to the generated electromotive forces for certain frequencies and amplitudes of the input excitations. Taking the power consumption of instrumentation into account, power gains up to ≈ 26% were achieved for harmonic inputs with randomly time changing frequencies and amplitudes. Using a prototype generator with 140.7 cm^3, output average powers of up to 1.79 W (i.e., 12.7 kW/m^3) were extracted for optimal electrical loads under non-linear resonant conditions. Significant increases in electric power efficiencies were achieved as well. These promising results should pave the way towards intelligent self-adapting energy generators.