A Direction Self-Tuning Two-Dimensional Piezoelectric Vibration Energy Harvester

Zhao, Haibo; Wei, Xiaoxiang; Zhong, Yiming; Wang, Peihong

doi:10.3390/s20010077

Cited by 19 publications

(9 citation statements)

References 30 publications

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“…Frequency conversion techniques consist of a primary system (frequency converter) that will affect the frequency up or down of the secondary system by using a coupling mechanism (geared, tapping, magnetic and topological contact) (Rizal et al, 2022; Shi et al, 2022). The self-tuning mechanisms use proof mass and spring varying the mass or/and stiffness of the system (Yu et al, 2020; Zhao et al, 2019). Other nonlinear techniques are mechanical stoppers (Chen et al, 2017b; Jiang et al, 2021) and mechanical load-induced/preload-induced models (Cao et al, 2020; Chen and Yan, 2020).…”

Section: Reviewmentioning

confidence: 99%

Recent advancements in piezoelectric energy harvesting for implantable medical devices

Upendra,

Panigrahi,

Singh

et al. 2023

Journal of Intelligent Material Systems and Structures

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Biomedical implantable devices like deep brain stimulators, implantable cardioverter-defibrillators and cardiac pacemakers are essential for treating the human heart and brain-related diseases. In the past few decades, a considerable amount of research has focused on improving bio-implant technologies. Conventional bio implant devices consist of an external generator like a battery to power the system, which requires replacement after a particular time. Therefore, in recent years, self-powered implants with various energy harvesting techniques have been proposed to avoid frequent surgery for battery replacement and to miniaturise the implant systems. However, the research communities have yet to explore all the limitations and possibilities of improvement on such energy-scavenging technologies, especially when the application is in vivo. Several aspects of recent developments in energy harvesting technologies feasible for biomedical implantable devices are reported systematically. A detailed review of piezoelectric energy harvester mechanism and miniaturisation, electric output and power management and biocompatibility of an energy harvester for implantable medical devices in vitro and in vivo environments. Furthermore, the piezoelectric energy harvester’s durability, packaging material, connection and evaluation criteria are discussed.

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Section: Reviewmentioning

confidence: 99%

Recent advancements in piezoelectric energy harvesting for implantable medical devices

Upendra,

Panigrahi,

Singh

et al. 2023

Journal of Intelligent Material Systems and Structures

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“…Due to the characteristics of ultra-low frequency in human motions, the vibration energy cannot be harvested efficiently by conventional piezoelectric energy harvester, human motion energy harvesting mainly adopts triboelectric [1,2], electromagnetic [3,4], thermoelectric [5,6] and other electromechanical mechanisms. In order to harvest ultra-low frequency vibration energy by piezoelectric mechanism, researchers have developed various energy conversion structures, such as magnetic coupling [7][8][9][10] is used to couple the external vibration energy into the piezoelectric cantilever beam, rolling beads are used to impact the piezoelectric patches in different directions [11], and a spring-mass system is used to sense the external vibration [12].…”

Section: Introductionmentioning

confidence: 99%

Magnetic coupled ultra-low frequency piezoelectric energy harvester for self-powered sensors

Li¹,

Han

Jiang

2022

J. Phys.: Conf. Ser.

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Harvesting human motion energy to power various sensors has attracted more and more attention of researchers. Aiming to harvest the ultra-low frequency vibration energy generated by human motion, this paper proposes a magnetic coupled scheme which consists of two flextensional transducers with two endmost magnets, a center magnet, and a tube. Through magnetic coupling effect, the ultra-low frequency vibration energy is amplified and effectively harvested, and the output voltage amplitude at 5Hz reaches 22V under the initial distance of 48mm and the acceleration of 1g. The output voltage amplitude of the harvester is related to the initial distance and excitation acceleration which are theoretically analyzed in this paper.

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“…They proposed such a model for functionality in wireless sensor networks (WSN) under stochastic excitations which is known as random vibrations. Zhao et al [22] proposed a novel 2D energy harvester with self-tuning capability. They studied the effects of the vibration direction over the performance of the harvester module.…”

Section: Introductionmentioning

confidence: 99%

Optimizing piezoelectric vibration-based energy harvester using numerical-analytical method and soft computing algorithms

Babaei

Parker

Moshaver

2022

Preprint

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Tuning and optimizing of piezoelectric vibration-based energy harvesters (PVEH) is essential to render sufficient amount of energy. As a modification to the tuning mass and dynamic magnifier of conventional PVEH, a novel integrated multisystem of cantilever-oscillator-spring is proposed in which the vibratory analysis discloses significant mutation in resonance frequency depending on the oscillator mass and spring constant values, showing hyper-tuning capability. Obtaining the maximum extractable amount of electric voltage is the ultimate goal which is an optimization problem with oscillator mass and spring stiffness as design parameters. The extended Hamilton’s principle along with the Galerkin modal decomposition techniques are adopted to find analytical-numerical response of the system undergoing harmonic base excitations. To optimize the voltage frequency response function (FRF), global evolutionary optimization algorithm is adopted. The closed-form voltage function is a hard-to-evaluate and computationally-expensive function. To overcome such issues, soft computing techniques is adopted. Using adaptive neuro fuzzy logic (ANFIS), a regressor model is designed to execute function evaluations in the genetic optimization procedure. Fuzzy inference system (FIS) is developed using 64 fuzzy ules derived from Gaussian and Gaussian-Bell shaped membership functions (MFs). Such a regressor model is utilized in the genetic algorithm launching with 200 iterations and 50 populations. It is observed that using roulette wheel, tournament, and random selection methods; rs= 100, rm= 2 are found as the optimal design parameter values. To validate the correctness of the implemented soft computing algorithm; the optimal voltage FRF is obtained using the closed-form analytical-numerical solution and compared with random case studies. It is shown that the nominated optimal values render the most obtainable amount of voltage. Eventually, it is inferable that the spring-mass subsystem integration with the cantilever energy harvester, drastically improves the amount of harnessed voltage. Furthermore, optimization of such integrated multi-system via soft computing techniques results in the maximum amount of harvestable voltage.

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A Direction Self-Tuning Two-Dimensional Piezoelectric Vibration Energy Harvester

Cited by 19 publications

References 30 publications

Recent advancements in piezoelectric energy harvesting for implantable medical devices

Recent advancements in piezoelectric energy harvesting for implantable medical devices

Magnetic coupled ultra-low frequency piezoelectric energy harvester for self-powered sensors

Optimizing piezoelectric vibration-based energy harvester using numerical-analytical method and soft computing algorithms

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