Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.701091
Title: Development of vibration-based multi-resonance energy harvesters using piezoelectric materials
Author: Xiong, Xingyu
ISNI:       0000 0004 5990 0767
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2014
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Abstract:
The development of self-powered wireless sensor networks for structural and machinery health monitoring has attracted considerable attention in the research field during the last decade. Since the low-duty-cycle wireless sensor networks have significantly reduced the power requirements to the range of tens to hundreds of microwatts, it is possible to harvest environmental energy as the power supply instead of using batteries. Vibration energy harvesting using piezoelectric materials has become the most popular technique, which has a good potential to generate adequate power. However, there is a limitation for the conventional beam-shaped harvester designs in real applications due to their limited bandwidth. In order to overcome this limitation, the essential objective of this thesis is to develop harvesters with multi-resonance structures. The multi-resonance harvester with good broadband performance can achieve close resonance frequencies and relatively large power output in each vibration mode. The main tasks and contributions of this thesis are summarised as follows: • A parametric analysis is presented to determine how the modal structural and electromechanical performances of cantilevered beam harvesters are affected by two modal factors designated as mass ratio and electromechanical coupling coefficient (EMCC). The modal performance of using rectangular, convergent and divergent tapered configurations with and without extra masses are systematically analysed by geometric variation using the finite element analysis (FEA) software ABAQUS. • A modal approach using the two modal factors to evaluate the modal performance of harvesters is introduced and a configurational optimization strategy based on the modal approach is developed to pre-select the configurations of multi-resonance harvesters with better modal structural performance and close resonance frequencies in multiple modes. Using this optimization strategy obviates the need to run the full analysis at the first stage. • A novel two-layer stacked harvester, which consists of a base cantilevered beam that is connected to an upper beam by a rigid mass, is developed. By altering the dimensions and the locations of the masses, the two-layer harvester can generate two close resonance frequencies with relatively large power output. The effects of using rectangular, convergent and divergent tapered beam configurations are systematically analysed. • Multi-layer stacked harvesters with up to five layers are developed. The three-layer harvesters with different mass positions, which can generate three close resonance frequencies, are optimized using the configurational optimization strategy. • A novel doubly-clamped multi-layer harvester, which is able to generate five close resonance frequencies with relatively large power output, is developed and thoroughly analysed. • An experimental study of the multi-layer stacked harvester is presented to validate the simulated results and the configurational optimization strategy. • An experimental study of the two-layer stacked harvester using high performance single crystal piezoelectric material PIMNT is presented. The harvester using PIMNT can generate nearly 10 times larger power output and 3.5 times wider bandwidth than using PZT. Besides, by modifying the location of the piezoelectric layer, anti-resonances between two adjacent modes can be eliminated.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.701091  DOI: Not available
Keywords: Vibration energy harvesting ; Piezoelectric energy harvesting ; Broadband performance ; Multi-resonance harvesters ; Modal approach ; Configurational optimization
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