Optimization of the Performance of Bimorph Piezoelectric Energy Harvesters with Honeycomb Metamaterials Using Artificial Neural Networks and NSGA-II

Authors

  • Mohamed Taha Mhiri Université de Monastir, Ecole Nationale d’Ingénieurs de Monastir, Laboratoire de Génie Mécanique, LR99ES32, 5019, Monastir, Tunisie, Structural Mechanics and Coupled Systems Laboratory, Conservatoire National des Arts et Métiers, 292 rue Saint Martin, 75003, Paris, France
  • Walid Larbi Structural Mechanics and Coupled Systems Laboratory, Conservatoire National des Arts et Métiers, 292 rue Saint Martin, 75003, Paris, France
  • Mnaouar Chouchane Université de Monastir, Ecole Nationale d’Ingénieurs de Monastir, Laboratoire de Génie Mécanique, LR99ES32, 5019, Monastir, Tunisie
  • Mohamed Guerich De Vinci Higher Education, De Vinci Research Center, Paris, France

DOI:

https://doi.org/10.13052/ejcm2642-2085.34346

Keywords:

Piezoelectric vibration energy harvesting, metamaterial, artificial neural network, NSGA-II

Abstract

Honeycomb-based metamaterials have recently attracted considerable interest for their potential in energy-harvesting applications. In this paper, we focus on two types of bimorph harvesters incorporating honeycomb substrates with positive and negative Poisson’s ratios (PPR and NPR). The substrates are coupled with piezoceramic (PZT) layers to enable electromechanical conversion. To improve energy-harvesting efficiency, we propose an optimization framework that integrates finite element (FE) simulations for data generation, a pretrained neural network for rapid performance prediction and the NSGA-II evolutionary algorithm for multiobjective optimization. The proposed strategy enables the identification of optimal geometric parameters of the honeycomb cells, particularly for cantilever resonators where the fundamental vibration modes are critical and must be tuned to specific eigenfrequencies for engineering applications. The optimization is applied to an initially unoptimized bimorph harvester with a honeycomb substrate. The simulation results indicate that an optimized harvester with an NPR metamaterial substrate can increase the power-to-mass ratio at a resonance frequency of 160 Hz by approximately 14.72% compared to the unoptimized honeycomb harvester. Moreover, compared to a harvester with a solid substrate, the improvement reaches 5%. Furthermore, a life cycle analysis was conducted, showing that the honeycomb substrate can significantly increase the operational lifetime of the piezoceramic layer. This improvement arises because the honeycomb substrate reduces the equivalent stress on the active layer. At high acceleration levels, the predicted operational lifetime is enhanced by more than tenfold compared to the solid substrate, since the PZT material is brittle and lacks flexibility. This improvement is notable because it surpasses the typical lifespan of both standard button batteries and rechargeable batteries highlighting a strong potential of this design for future applications.

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Author Biographies

Mohamed Taha Mhiri, Université de Monastir, Ecole Nationale d’Ingénieurs de Monastir, Laboratoire de Génie Mécanique, LR99ES32, 5019, Monastir, Tunisie, Structural Mechanics and Coupled Systems Laboratory, Conservatoire National des Arts et Métiers, 292 rue Saint Martin, 75003, Paris, France

Mohamed Taha Mhiri is a PhD candidate in a dual doctoral program in mechanical engineering between the National Engineering School of Monastir (ENIM), Tunisia, and the National Conservatory of Arts and Crafts (CNAM), Paris, France. He earned his mechanical engineering degree from ENIM, Tunisia, in 2022. His research focuses on modelling and optimizing piezoelectric energy harvesters.

Walid Larbi, Structural Mechanics and Coupled Systems Laboratory, Conservatoire National des Arts et Métiers, 292 rue Saint Martin, 75003, Paris, France

Walid Larbi is Full Professor of Mechanics and Civil Engineering at the Conservatoire National des Arts et Métiers (CNAM), Paris, and a member of the LMSSC laboratory. His research interests include structural dynamics, non-linear seismic analysis, reduced-order modelling, and vibro-acoustics. He has authored more than 100 publications and supervised over 12 PhD theses. He is head of the CNAM BTP “Structures” programs, training over 70 engineers per year, and leads CNAM’s international activities in Lebanon, Morocco, and Tunisia. In 2024, he was named Knight in the French Order of Academic Palms.

Mnaouar Chouchane, Université de Monastir, Ecole Nationale d’Ingénieurs de Monastir, Laboratoire de Génie Mécanique, LR99ES32, 5019, Monastir, Tunisie

Mnaouar Chouchane is a Professor of Mechanical Engineering in the National School of Engineering in Monastir, Tunisia, where he has been a faculty member since 1990. He received an Engineering Degree from the University of Tunis in 1984 followed by a master’s degree in mechanical engineering from Washington University in Saint Louis, USA, in 1986 and a PhD from Georgia Institute of Technology, USA, in 1989. His research interests are in the area of vibration and acoustics of machines and structures and smart machines and structures with recent publications on piezoelectric harvesting and passive and active control of rotor vibration. He published more than 20 papers in peer reviewed journals and organized or co-organized the last five editions of the CMSM conference and co-edited the published conference proceedings.

Mohamed Guerich, De Vinci Higher Education, De Vinci Research Center, Paris, France

Mohamed Guerich is a Professor of Mechanical Engineering in the Ecole Supérieure d’Ingénieurs Léonard de Vinci (ESILV), France, since 2001. He received a Civil Engineering diploma and a research master’s degree in mechanical engineering from the Ecole Nationale d’Ingénieurs de Tunis (ENIT), Tunisia, in 1991 then a PhD from Université de Technologie de Compiègne (UTC), France, in 1991 followed by an Habilitation to Supervise Research (HDR) from UTC in 2019. His research focuses on the Vibro-Acoustic modelling of structures (Reductions, Damping, Optimizations) and Homogenization of Composite Materials. His recent publications concern the modelling and the optimization of a piezoelectric energy harvester. He has published 14 papers in peer reviewed journals and more than 30 Communications in international conferences with peer review and proceedings.

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Published

2026-02-26

How to Cite

Mhiri, M. T. ., Larbi, W. ., Chouchane, M. ., & Guerich, M. . (2026). Optimization of the Performance of Bimorph Piezoelectric Energy Harvesters with Honeycomb Metamaterials Using Artificial Neural Networks and NSGA-II. European Journal of Computational Mechanics, 34(3&4), 325–362. https://doi.org/10.13052/ejcm2642-2085.34346

Issue

2025: Vol 34 Iss 3&4

Section

ECCOMAS-MSF 2025: Multi-scale modeling & computations in solid & fluid mechanics