An experimental and analytical piezoelectric energy harvesting from a simply supported beam with moving mass

Assadi, Hamed; Hamani, Iraj Dehghan; Tikani, Reza; Ziaei-Rad, Saeed

doi:10.1177/1045389x16633767

Cited by 16 publications

(5 citation statements)

References 16 publications

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“…In this section, the proposed multivariate recursive BLR method is applied to identify two mechanical systems with typical TV dynamics. The first example is a simply supported beam with moving mass, which can be viewed as a simplified model of the vehicle–bridge interaction system and has been widely studied for vibration control (Stancioiu and Ouyang, 2016), energy harvesting (Assadi et al, 2016; Dehghan Hamani et al, 2020), dynamic modeling (He, 2018), and system identification (Ma et al, 2018b; Zhang et al, 2019). The fluid–structure interaction systems with variable mass distribution widely exist in the field of aerospace applications, and the second example is a liquid-filled cylindrical structure with decreasing filling mass, which can be used to model and analyze the slender aerospace structure with decreasing fuel (Ma et al, 2020a).…”

Section: Experimental Applicationsmentioning

confidence: 99%

Multivariate recursive Bayesian linear regression and its applications to output-only identification of time-varying mechanical systems

Ding

2020

Journal of Vibration and Control

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This article focuses on the output-only recursive identification of time-varying systems by using parametric time-domain methods. A novel multivariate recursive Bayesian linear regression method is proposed based on the vector time-dependent autoregressive moving average model. The standard setup of univariate batch Bayesian linear regression is first extended to the multivariate case for multiple response signal modeling and further extended to the recursive case to meet the output-only recursive identification requirement of practical systems. A sliding window mechanism is finally applied to deemphasize data from the remote past and fix the computational complexity for each consecutive update, allowing the proposed method to be capable of tracking the time-varying dynamics online. The proposed multivariate recursive Bayesian linear regression method is first validated by a simple numerical system and subsequently applied to identify two mechanical systems with typical time-varying dynamics. Comparative identification results via Monte Carlo tests numerically and experimentally demonstrate the superior achievable accuracy and time-varying tracking capability of the proposed method.

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Section: Experimental Applicationsmentioning

confidence: 99%

Multivariate recursive Bayesian linear regression and its applications to output-only identification of time-varying mechanical systems

Ding

2020

Journal of Vibration and Control

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“…The vibration energy of the bridge can be converted into electrical energy by attaching a piece of piezoelectric (PZT) patch on the surface of the bridge. To evaluate the energy harvested from the bridge vibration, Assadi et al [7] derived the formulas for the simply supported beam excited by a traversing mass. The results obtained from the formulas were in good agreement with the experimental ones.…”

Section: Introductionmentioning

confidence: 99%

Harvest more bridge vibration energy by nonlinear multi-stable piezomagnetoelastic harvester

Zhou,

Huang,

Cao

et al. 2024

J. Phys. D: Appl. Phys.

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The idea of using bridge vibration energy to power node sensors is promising in solving the power problems of bridge health monitoring systems. This study proposes a piezomagnetoelastic harvester that tries utilizing nonlinear multi-stability to improve the harvesting performance of bridge vibration energy. The harvester can exhibit multi-stable behaviors due to the introduced nonlinear forces. The potential energy functions are derived and corresponding analyses are carried out. The results show that the tri-stable state of harvester can be obtained by adjusting the parameters related to magnetic forces. Its potential barriers are low and the distance between potential wells is large, so it can execute snap-through motion easily. The experimental study was carried out for different vehicle speeds. The results verify that the energy harvester in tri-stable state can generate the largest electric output over a wide range of vehicle speed. Moreover, it is proved that the tri-stable state can protect the harvester from excessive deformation and subsequent damage. Therefore, the tri-stable configuration has a potential advantage in bridge vibration energy harvesting and providing power for self-powered sensors.

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“…Lu et al [30] proposed a pin-based hybrid energy harvester combining a single-span buckled beam, a two-span buckled beam, and a two-span beam for broadband harvesting. Simply supported beams [31][32][33][34][35][36][37] are also commonly used and exhibit good strain distribution.…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of an Extended Simply Supported Beam Piezoelectric Energy Harvester

Tseng

2023

Sensors

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The harvesting efficiency of a cantilevered piezoelectric energy harvester is limited by its uneven strain distribution. Moreover, a cantilevered harvester requires a large workspace due to the large displacement of its free end. To address these issues, a novel piezoelectric energy harvester based on an extended simply supported beam is proposed. The proposed design features a simply supported piezoelectric main beam with an extended beam attached to its roller end and a tip mass to reduce the resonant frequency. The theoretical model of the proposed piezoelectric energy harvester is developed based on the Euler–Bernoulli beam theory. The model has been experimentally validated through the fabrication of a prototype. The extended beam and tip mass are adjusted to see their influence on the performance of the harvester. The resonant frequency can be maintained by shortening the extended beam and increasing the tip mass simultaneously. A shorter extend beam leads to a more even strain distribution in the piezoelectric layer, resulting in an enhanced output voltage. Moreover, the simulation results show that a torsional spring is installed on the roller joint which greatly influences the voltage output. The strain distribution becomes more even when proper compressive preload is applied on the main beam. Experiments have shown that the proposed design enhances the output power by 86% and reduces tip displacement by 63.2% compared to a traditional cantilevered harvester.

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An experimental and analytical piezoelectric energy harvesting from a simply supported beam with moving mass

Cited by 16 publications

References 16 publications

Multivariate recursive Bayesian linear regression and its applications to output-only identification of time-varying mechanical systems

Multivariate recursive Bayesian linear regression and its applications to output-only identification of time-varying mechanical systems

Harvest more bridge vibration energy by nonlinear multi-stable piezomagnetoelastic harvester

Design and Analysis of an Extended Simply Supported Beam Piezoelectric Energy Harvester

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