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Analytical modelling and optimization of a piezoelectric cantilever energy harvester with in-span sttachment

Homayouni-Amlashi, Abbas and Mohand-Ousaid, Abdenbi and Rakotondrabe, Micky Analytical modelling and optimization of a piezoelectric cantilever energy harvester with in-span sttachment. (2020) Micromachines. Special issue : "Piezoelectric Nanogenerators for Micro-Energy and Self-Powered Sensors", 11 (6).

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Official URL: https://doi.org/10.3390/mi11060591


In this paper, the location of masses and of a piezoelectric patch for energy harvesting reported onto a vibrating cantilever beam is studied and optimized. To this aim, a genetic algorithm is adapted and utilized to optimize the voltage amplitude generated by the piezoelectric patches by choosing attachment mass, attachment mass moment of inertia, attachment location, piezoelectric patch location and force location on the beam as parameters. While an analytical approach is proposed to evaluate the voltage amplitude, a multi-layer perceptron neural network is trained by the derived characteristic matrix to obtain an approximate function for natural frequencies based on the attachment parameters. The trained network is then used in the core of genetic algorithm to find the best optimization variables for any excitation frequency. Numerical simulation by COMSOL Multiphysics finite element software validates the calculated voltage by analytical approach. The optimization method successfully matches the natural frequency of the beam with the excitation frequency which therefore maximizes the output energy. On the other hand, the superiority of the optimized design over the conventional configuration in harvesting the energy at high frequency excitation is also approved.

Item Type:Article
Additional Information:c 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
HAL Id:hal-03120197
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Ecole Nationale Supérieure de Mécanique et des Microtechniques - ENSMM (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Other partners > Université de Franche-Comté (FRANCE)
Other partners > Université de Technologie de Belfort-Montbéliard - UTBM (FRANCE)
Other partners > Université Bourgogne Franche-Comté - UBFC (FRANCE)
Laboratory name:
Deposited On:11 Jan 2021 15:51

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