A Magnet-Slider Piezoelectric-Electromagnetic Energy Harvester Based on Passive Self-Tuning
Piezoelectric energy harvesters have received significant attention for powering sensor networks, particularly those employing self-tuning mechanisms to adapt to variations in the external excitation frequencies. This study proposes a magnet-slider piezoelectric–electromagnetic energy harvester (MS-PEEH) based on passive self-tuning. The device replaces conventional sliders and mechanical stoppers with sliding and fixed magnets, mitigating energy losses due to slider collisions and enhancing energy harvesting by incorporating a coil at the free end of the beam to capture energy from the sliding motion of the slider. An electromechanically coupled mathematical model of the system was developed and validated through numerical simulations and experimental results. Frequency sweep experiments revealed that, under a 0.4[Formula: see text]g excitation, the MS-PEEH achieved a 1[Formula: see text]051% increase in output power and a 100% wider operational bandwidth compared to a conventional piezoelectric harvester. The parametric analysis results indicate a strong positive correlation between the output performance and excitation acceleration amplitude with the optimal selection of the magnetic moment of the magnet, which is critical for performance enhancement. At an excitation of 0.3[Formula: see text]g and 7.6[Formula: see text]Hz, the MS-PEEH achieves a peak output power of 48.03[Formula: see text]mW. Furthermore, the device effectively powered an array of 40 LEDs, reliably powered a thermometer, and demonstrated superior charging performance in capacitor-charging experiments. As a self-tuning energy harvester tailored to low-frequency vibration environments, the MS-PEEH exhibits substantial application potential.
Authors
- Fujiang Cui (ORCID: https://orcid.org/0000-0002-1776-8652)
- X. F. Chen
- Peng Liu
Institutions
- Taiyuan University of Science and Technology (CN)
- Taiyuan University of Technology (CN)
Publication Details
- Journal
- International Journal of Structural Stability and Dynamics
- Published
- 2025-09-22
- DOI
- https://doi.org/10.1142/s0219455427500581
- Primary Topic
- Modular Robots and Swarm Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00