Review and Analysis of Magnetic Energy Harvesters: A Case Study for Vehicular Applications

Enayati, Javad; Asef, Pedram

doi:10.1109/access.2022.3195052

Cited by 11 publications

(2 citation statements)

References 118 publications

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“…The energy is then released when the magnets move away -spring is stretched [10]. The spring force of the magnetic spring is nonlinear and highly depends on the magnetic properties of the magnetic spring components and their configuration [11]- [14]. In energy harvesting application magnetic spring is used as the mechanism that hold moving magnet inside the coil.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Model for Magnetic Flux Density Prediction in Magnetic Spring on the Vibration Generator

Lo Sciuto,

Bijak,

Kowalik

et al. 2024

IEEE Access

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The magnetic spring placed on vibration generator consists of top and bottom fixed magnets with a third magnet levitated between them. Nonlinear dynamic analysis appears in the magnetic flux density of the magnetic spring activated by the vibration generator. This paper is focused on fast data-driven and accurate model for the prediction of magnetic flux density using a deep neural network (DNN) in the form of a Long Short-Term Memory (LSTM). As the input and training data for LSTM are used: supply voltage of the vibration generator, its frequency and measured magnetic flux density. The magnetic flux density measurements of the magnetic spring have been recorded by three Hall effect sensors. The prediction of magnetic flux density in magnetic spring has given accurate results and good applicability for better characterization of the device in energy harvesting system.

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Section: Introductionmentioning

confidence: 99%

Deep Learning Model for Magnetic Flux Density Prediction in Magnetic Spring on the Vibration Generator

Lo Sciuto,

Bijak,

Kowalik

et al. 2024

IEEE Access

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“…The widespread use of batteries may harm the environment [7]. The key technology to provide green energy to the low-power electrical components embedded in public transportation is the energy harvesting (EH) technique [8], which can power electrical loads using the energy sources present in the operating environment [9][10][11]. A generic EH harvester is composed of an environmental energy source, a transducer, and an electrical power processing unit (PPU), as illustrated in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

A Bicycle-Embedded Electromagnetic Harvester for Providing Energy to Low-Power Electronic Devices

Urbina,

Baron,

Carvajal

et al. 2023

Electronics

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Bicycles are rapidly gaining popularity as a sustainable mode of transportation around the world. Furthermore, the smart bicycle paradigm enables increased use through the Internet of Things applications (e.g., GPS tracking systems). This new paradigm introduces energy autonomy as a new challenge. The energy harvesting technology can capture the energy present in the cycling environment (e.g., kinetic or solar) to give this autonomy. The kinetic energy source is more stable and dense in this environment. There are several wheel kinetic harvesters on the market, ranging from low-complexity dynamos used to power bicycle lights to smart harvester systems that harvest kinetic energy while braking and cycling and store it for when it is needed to power sensors and other electronics loads. Perhaps the hub and the “bottle” dynamos are the most commercially successful systems because of their cost-effective design. Furthermore, the bottle generator is very inexpensive, yet it suffers from significant energy losses and is unreliable in wet weather due to mechanical friction and wheel slippage in the wheel/generator contact. This paper proposes a cost-effective bicycle harvester based on a novel kinetic-electromagnetic transducer. The proposed harvester allows for the generation and storage of harnessed kinetic energy to power low-power electronics loads when the user requires it (e.g., cell phone charging, lighting). The proposed harvester is made up of a power processing unit, a battery, and an optimized transducer based on a Halbach magnet array. An extensive full-wave electromagnetic simulation was used to evaluate the proposed transducer. Circuit simulation was also used to validate the proposed power unit. The proposed harvester generates a simulated output power of 1.17 W with a power processing unit efficiency of 45.6% under a constant bicycle velocity of 30 km/h.

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A compact complementary split ring resonator (CSRR) based perfect metamaterial absorber for energy harvesting applications

Ullah

Islam

Hoque

et al. 2023

Engineering Science and Technology, an International Journal

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Review and Analysis of Magnetic Energy Harvesters: A Case Study for Vehicular Applications

Cited by 11 publications

References 118 publications

Deep Learning Model for Magnetic Flux Density Prediction in Magnetic Spring on the Vibration Generator

Deep Learning Model for Magnetic Flux Density Prediction in Magnetic Spring on the Vibration Generator

A Bicycle-Embedded Electromagnetic Harvester for Providing Energy to Low-Power Electronic Devices

A compact complementary split ring resonator (CSRR) based perfect metamaterial absorber for energy harvesting applications

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