Abstract

Piezoelectric energy harvesters (PEHs) can be used as an additional power supply for a Structural Health Monitoring (SHM) system. Its design can be optimised for the best performance, however, the optimal design depends on the input vibration and locations. In this work, we extend an optimisation framework from our previous studies to include the effect of the PEH’s location, which uses the cantilevered PEH Kirchhoff–Love plate model discretised by IsoGeometric Analysis (IGA) and coupled with Particle Swarm Optimisation (PSO) algorithm to find the designs with maximum energy outputs for a large number of input acceleration histories, extracted from the recorded dynamic response data of a real cable-stayed bridge in Australia. Then, clustering and evaluation under 24-h excitation are performed to find several best PEHs for the entire bridge. By comparing the best PEH at all locations with a typical benchmark device, the substantial performance improvement brought by the optimisation framework of this work is verified. The comparison results show a significant energy harvesting enhancement of 1.6 times at the best locations, 2.4 times at A2 and A3, and 3.6 times at the edge girders, respectively. The results also reveal the variability of the best design at different locations of the same structure to maximise the energy harvesting of the entire bridge, and demonstrate the design rule that the fundamental frequency of the device can be tuned within a certain frequency range to improve the robustness of PEHs design. Additional studies are performed to explore the effect of location and traffic intensity on energy harvesting by analysing the optimal PEH design and location throughout the bridge structure. The results indicate that the key factors of maximising energy harvesting efficiency are related to the input excitation and the mode of vibration being excited. The position of maximum displacement in the vibration mode corresponds to the best location for energy harvesting. Also, the best device has a fundamental frequency close to the frequency of the corresponding vibration mode. In addition, the change of traffic intensity affects the amount of convertible mechanical energy and also directs the tuning of the fundamental frequency of the PEH to achieve the highest energy conversion.

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