Jia, Yu, Yan, Jize, Du, Sijun, Feng, Tao, Fidler, Paul, Middleton, Campbell, Soga, Kenichi and Seshia, Ashwin A. (2018) Real world assessment of an auto-parametric electromagnetic vibration energy harvester. Journal of Intelligent Materials Systems and Structures, 29 (7), 1481-1499. (doi:10.1177/1045389X17740964).
Abstract
The convention within the field of vibration energy harvesting has revolved around designing resonators with natural frequencies that match single fixed frequency sinusoidal input. However, real world vibrations can be random, multi-frequency, broadband and time-varying in nature. Building upon previous work on auto-parametric resonance, this fundamentally different resonant approach can harness vibration from multiple axes and has the potential to achieve higher power density as well as wider frequency bandwidth. This article presents the power response of a packaged auto-parametric VEH prototype (practical operational volume of ∼126 cm−3) towards various real world vibration sources including vibration of a bridge, a compressor motor as well as an automobile. At auto-parametric resonance (driven at 23.5 Hz and 1 grms), the prototype can output a peak of 78.9 mW and 4.5 Hz of −3dB bandwidth. Furthermore, up to ∼1 mW of average power output was observed from the harvester on the Forth Road Bridge. The harvested electrical energy from various real world sources were used to power up a power conditioning circuit, a wireless sensor mote, a micro-electromechanical system accelerometer and other low-power sensors. This demonstrates the concept of self-sustaining vibration powered wireless sensor systems in real world scenarios, to potentially realise maintenance-free autonomous structural health and condition monitoring.
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- Faculties (pre 2018 reorg) > Faculty of Physical Sciences and Engineering (pre 2018 reorg) > Electronics & Computer Science (pre 2018 reorg) > Smart Electronic Materials & Systems (pre 2018 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg) > Smart Electronic Materials & Systems (pre 2018 reorg)
School of Electronics and Computer Science > Electronics & Computer Science (pre 2018 reorg) > Smart Electronic Materials & Systems (pre 2018 reorg) - Faculties (pre 2011 reorg) > Faculty of Engineering Science & Maths (pre 2011 reorg) > Electronics & Computer Science (pre 2011 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Electronics and Computer Science > Electronics & Computer Science (pre 2011 reorg)
School of Electronics and Computer Science > Electronics & Computer Science (pre 2011 reorg)
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