scholarly journals Nonlinear multimodal electromagnetic device for vibration energy harvesting

2019 ◽  
Vol 286 ◽  
pp. 01003
Author(s):  
K. Aouali ◽  
Z. Zergoune ◽  
N. Kacem ◽  
E. Mrabet ◽  
N. Bouhaddi ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Periodic System ◽  
Vibration Energy ◽  
Large Displacements ◽  
Multimodal Approach ◽  
Arc Length ◽  
Energy Localization ◽  
Governing Equations ◽  
Vibration Energy Harvesting ◽  
Weakly Coupled

A multimodal vibration energy harvesting in a periodic system is proposed. The multimodal approach and the nonlinearity are implemented in order to improve the performances of the studied device. The periodic system, based on electromagnetic transduction, consists of two weakly coupled magnets mechanically guided by two elastic beams. The quasi-periodic system is obtained by varying the mass of one of the moving magnets which leads to the vibration energy localization in regions close to the imperfections. This phenomenon is exploited to maximize the harvested energy. The mechanical nonlinearity is introduced by considering large displacements of the beams. The system is modeled by two coupled forced Duffing equations. The governing equations are solved using finite difference method combined with arc-length method. It is shown that the introduction of the nonlinearity leads to the enlargement of the bandwidth and the increase of the amplitude of the vibration.

scholarly journals Effect of the localization on the response of a quasi-periodic electromagnetic oscillator array for vibration energy harvesting

2018 ◽  
Vol 241 ◽  
pp. 01003 ◽  
Author(s):  
Kaouthar Aouali ◽  
Najib Kacem ◽  
Elyes Mrabet ◽  
Noureddine Bouhaddi ◽  
Mohamed Haddar
Keyword(s):  
Energy Harvesting ◽  
Periodic System ◽  
Vibration Energy ◽  
Multimodal Approach ◽  
Energy Localization ◽  
Mechanical Stiffness ◽  
Vibration Energy Harvesting ◽  
Weakly Coupled ◽  
Electromagnetic Transduction ◽  
Electromagnetic Oscillator

Vibration energy harvesting by exploiting the multimodal approach in a quasi-periodic system is proposed. The quasi-periodic system, based on electromagnetic transduction, consists of two weakly coupled magnets mechanically guided by two elastic beams. Mistuning is achieved by varying the mechanical stiffness of one of the beams. These imperfections will lead to the vibration energy localization in regions close to the imperfections which will be exploited to maximize the harvested energy.

Exploiting Nonlinear Dynamics and Energy Localization to Enhance the Performances of an Electromagnetic Vibration Energy Harvester

2019 ◽  
Author(s):  
Kaouthar Aouali ◽  
Najib Kacem ◽  
Noureddine Bouhaddi ◽  
Elyes Mrabet ◽  
Mohamed Haddar
Keyword(s):  
Periodic System ◽  
Energy Harvester ◽  
Continuation Method ◽  
Vibration Energy ◽  
Arc Length ◽  
Energy Localization ◽  
Vibration Energy Harvester ◽  
Localization Phenomenon ◽  
Electromagnetic Vibration ◽  
Weakly Coupled

Abstract A multimodal electromagnetic vibration energy harvester based on a nonlinear quasi-periodic system is proposed. The multimodal approach and the nonlinearity are implemented in order to improve the output performances of the studied device. The present study investigates a periodic system composed of two weakly coupled magnets and mechanically guided by two elastic beams. The quasi-periodic system is obtained by varying the mass of one of the moving magnets which leads to the vibration energy localization in regions close to the imperfections introduced. This phenomenon is exploited to maximize the harvested energy. The mechanical nonlinearity is introduced by considering large displacements of the beams which is also investigated to maximize the harvested energy and to enlarge the bandwidth of the device. The quasi-periodic system is modeled by two coupled forced Duffing equations, which are solved using finite difference method combined with arc-length continuation method. The obtained results of the mass mistuning are analyzed and discussed in depth. It is shown that the introduction of the nonlinearity and the functionalization of the energy localization phenomenon lead to the enlargement of the bandwidth and the increase of the vibration amplitudes.

Efficient broadband vibration energy harvesting based on tuned non-linearity and energy localization

2020 ◽  
Vol 29 (10) ◽  
pp. 10LT01
Author(s):  
Kaouthar Aouali ◽  
Najib Kacem ◽  
Noureddine Bouhaddi ◽  
Elyes Mrabet ◽  
Mohamed Haddar
Keyword(s):  
Energy Harvesting ◽  
Vibration Energy ◽  
Energy Localization ◽  
Vibration Energy Harvesting

scholarly journals Experiment Investigation of Bistable Vibration Energy Harvesting with Random Wave Environment

2021 ◽  
Vol 11 (9) ◽  
pp. 3868
Author(s):  
Qiong Wu ◽  
Hairui Zhang ◽  
Jie Lian ◽  
Wei Zhao ◽  
Shijie Zhou ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Harvesting ◽  
Cantilever Beam ◽  
Large Scale ◽  
Low Frequency ◽  
Vibration Energy ◽  
Random Wave ◽  
Periodic Signal ◽  
Vibration Energy Harvesting ◽  
Motion Activity

The energy harvested from the renewable energy has been attracting a great potential as a source of electricity for many years; however, several challenges still exist limiting output performance, such as the package and low frequency of the wave. Here, this paper proposed a bistable vibration system for harvesting low-frequency renewable energy, the bistable vibration model consisting of an inverted cantilever beam with a mass block at the tip in a random wave environment and also develop a vibration energy harvesting system with a piezoelectric element attached to the surface of a cantilever beam. The experiment was carried out by simulating the random wave environment using the experimental equipment. The experiment result showed a mass block’s response vibration was indeed changed from a single stable vibration to a bistable oscillation when a random wave signal and a periodic signal were co-excited. It was shown that stochastic resonance phenomena can be activated reliably using the proposed bistable motion system, and, correspondingly, large-scale bistable responses can be generated to realize effective amplitude enlargement after input signals are received. Furthermore, as an important design factor, the influence of periodic excitation signals on the large-scale bistable motion activity was carefully discussed, and a solid foundation was laid for further practical energy harvesting applications.

Genetic algorithm- and finite element-based design and analysis of nonprismatic piezolaminated beam for optimal vibration energy harvesting

2015 ◽  
Vol 230 (14) ◽  
pp. 2532-2548 ◽  
Author(s):  
Alok Ranjan Biswal ◽  
Tarapada Roy ◽  
Rabindra Kumar Behera
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Energy Harvesting ◽  
Output Power ◽  
Governing Equation ◽  
Optimization Technique ◽  
Vibration Energy ◽  
Fe Model ◽  
Vibration Energy Harvesting ◽  
Real Coded Genetic Algorithm

The current article deals with finite element (FE)- and genetic algorithm (GA)-based vibration energy harvesting from a tapered piezolaminated cantilever beam. Euler–Bernoulli beam theory is used for modeling the various cross sections of the beam. The governing equation of motion is derived by using the Hamilton's principle. Two noded beam elements with two degrees of freedom at each node have been considered in order to solve the governing equation. The effect of structural damping has also been incorporated in the FE model. An electric interface is assumed to be connected to measure the voltage and output power in piezoelectric patch due to charge accumulation caused by vibration. The effects of taper (both in the width and height directions) on output power for three cases of shape variation (such as linear, parabolic and cubic) along with frequency and voltage are analyzed. A real-coded genetic algorithm-based constrained (such as ultimate stress and breakdown voltage) optimization technique has been formulated to determine the best possible design variables for optimal harvesting power. A comparative study is also carried out for output power by varying the cross section of the beam, and genetic algorithm-based optimization scheme shows the better results than that of available conventional trial and error methods.

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