In this paper, an electromagnetic micro generator is proposed to scavenge low frequency environmental vibrations and convert it into electrical power. The proposed micro generator is composed of cantilever beam, magnet and coil which is connected to a resistance load. Mechanical vibrations bend the beam and force the magnet to oscillate inside coil cross section. This phenomenon induces current in the coil and generates output electrical power. Dimensions and structure of the micro generator is optimized and output power and power density is modified. Consequently, mechanical vibrations could be converted into electrical power. Impact of different parameters such as coil turns, mechanical vibration amplitude, air gap, coil diameter and shape of magnet and coil on output power is studied. Geometrical and electrical optimizations for the proposed power harvester is performed. An innovative configuration for coil and magnet structure is proposed. At a constant special volume, number of coil and magnet composition is varied to find the optimum number of composition. So, the structure of the micro generator for 100 turn coil is optimized. Finally, the optimum design is proposed. The obtained results demonstrate that output power could be increased to 419.98 µW. For validation of the simulation results, a prototype with two types of coils are fabricated; to estimate the practical parameters. The type of utilized magnet is NdFeB grade of N42. The resonant frequency of the beam practically is measured to be 5.61 Hz. Open circuit voltage amplitude for 100 turn and 200 turn coil is measured to be approximately 39.2 mV and 76 mV, respectively. The measured output power is 8.42 µW and 20.91 µW which is delivered to optimal resistance load of 10 Ω and 18 Ω, respectively. The obtained simulation results are approximately confirming the achieved practical results.
Electromagnetic Micro Generator Mechanical vibration Electrical power Resonant frequency Low frequency environmental vibrations
Primary Language | English |
---|---|
Subjects | Artificial Intelligence (Other) |
Journal Section | Articles |
Authors | |
Publication Date | September 28, 2023 |
Published in Issue | Year 2023 Volume: 7 Issue: 3 |