Piezoelectric energy harvester based on bi-stable hybrid symmetric laminate
Source abstract
Abstract
Abstract A bi-stable piezoelectric energy harvester (BPEH) based on bi-stable hybrid symmetric laminate (BHSL) is proposed for energy harvesting. Due to its large deformation and low actuation, BPEH has better energy harvesting performance at low frequencies compared with traditional resonance cantilever-type energy harvester. Two types of stacking sequence and two types of piezoelectric ceramics (PZT) shapes with identical area were considered, and four types of BPEHs were designed. The stable configurations of the BPEHs and the stress states of PZT bonded on the surface of the BSHL were simulated and analyzed by finite element analysis. In addition, the four types of BPEHs were fabricated and experimentally evaluated. The BPEHs were actuated by hand shaking to transition between the two stable configurations. Using this method, the voltage outputs and power outputs were measured at two frequencies (2 Hz and 5 Hz). The results demonstrate that the BPEHs exhibited high output power because the PZTs on their surface were fully utilized due to their double curved shape and uniform deformations. The generated powers from the BPEHs were significantly higher than that observed from a similar sized cantilever-type piezoelectric harvester. Simultaneously, the influences of stacking sequence and shape of PZT on the energy harvesting performance were evaluated. The BPEHs with the second stacking sequence generated higher power than those of first stacking sequence, and the rectangular PZT performed better compared to the square. The measured maximum power output generated by the BPEH with the second stacking sequence and rectangular PZT was 37 mW at 5 Hz.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Innovative Energy Harvesting Technologies · Advanced Sensor and Energy Harvesting Materials · Energy Harvesting in Wireless Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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