Broadband Vibration Energy Harvesting from Underground Trains for Self-Powered Condition Monitoring

Abstract

A broadband vibration energy harvester tailored for self-powered condition monitoring of underground trains is proposed and developed using mechanical non-linearity and integrated multi-mode vibration. A data-driven approach is adopted for harvester design using operational vibration data on a train bogie. The harvester is designed to be unobtrusive while exhibiting good performance in harvesting energy over a wide bandwidth. In this work, the on-site vibration data are first analysed with the design goals identified. Then, a broadband harvester is proposed, implemented and evaluated. The harvester consists of a pre-stretched hosting beam and a group of micro-beams with repulsive magnetic forces on their free ends. A multiple vibration-mode harvester with non-linear dynamics is obtained in such a design. This harvester exhibits good performance over a broad bandwidth in frequency sweep and pseudo-random tests, illustrating its capability in self-powered condition monitoring applications.