Investigation of wireless power transfer applications with a focus on renewable energy

Chhawchharia, Saransch; Sahoo, Sarat Kumar; Balamurugan, M.; Sukchai, Sukruedee; Yanine, Fernando

doi:10.1016/j.rser.2018.04.101

Cited by 49 publications

(23 citation statements)

References 105 publications

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“…Therefore, it is essential to restore the energy of sensor nodes to equilibrate and extend the network lifetime [ 4 ]. At present, there are three categories of solutions existing for the energy replenishment of the sensor nodes, namely energy harvesting [ 5 ], wireless energy transfer (WET) [ 6 ] and sensor node replacement [ 7 ]. Several researchers have used energy harvesting techniques to empower the energy supply towards the sensor nodes, such as solar energy [ 8 ] and wind energy [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks

Sandrine

Xia

Umar

et al. 2022

Sensors

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Nowadays, wireless energy transfer (WET) is a new strategy that has the potential to essentially resolve energy and lifespan issues in a wireless sensor network (WSN). We investigate the process of a wireless energy transfer-based wireless sensor network via a wireless mobile charging device (WMCD) and develop a periodic charging scheme to keep the network operative. This paper aims to reduce the overall system energy consumption and total distance traveled, and increase the ratio of charging device vacation time. We propose an energy renewable management system based on particle swarm optimization (ERMS-PSO) to achieve energy savings based on an investigation of the total energy consumption. In this new strategy, we introduce two sets of energies called emin (minimum energy level) and ethresh (threshold energy level). When the first node reaches the emin, it will inform the base station, which will calculate all nodes that fall under ethresh and send a WMCD to charge them in one cycle. These settled energy levels help to manage when a sensor node needs to be charged before reaching the general minimum energy in the node and will help the network to operate for a long time without failing. In contrast to previous schemes in which the wireless mobile charging device visited and charged all nodes for each cycle, in our strategy, the charging device should visit only a few nodes that use more energy than others. Mathematical outcomes demonstrate that our proposed strategy can considerably reduce the total energy consumption and distance traveled by the charging device and increase its vacation time ratio while retaining performance, and ERMS-PSO is more practical for real-world networks because it can keep the network operational with less complexity than other schemes.

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Section: Introductionmentioning

confidence: 99%

On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks

Sandrine

Xia

Umar

et al. 2022

Sensors

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“…Drones are expected to be the strength of smart flying as they could act as the first respondent to any emergency that may arise. However, they have a huge limitation of having very low-power densities, an inability to sustain longer flight times, and hovering in the wrong directions that cause loss of power [16]. To optimize energy transfer performance, the misalignment transmission distance between the transmitter and receiver coils is the main limitation of magnetic resonator coupling (MRC) methods, which are sensitive to transmitting and receiving coil alignment.…”

Section: Introductionmentioning

confidence: 99%

Wireless Drone Charging Station Using Class-E Power Amplifier in Vertical Alignment and Lateral Misalignment Conditions

et al. 2022

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Recent major advancements in drone charging station design are related to the differences in coil design between the material (copper or aluminum) and inner thickness (diameter design) to address power transfer optimization and increased efficiency. The designs are normally challenged with reduced weight on the drone’s side, which can lead to reduced payload or misalignment position issues between receiver and transmitter, limiting the performance of wireless charging. In this work, the coil combination was tested in vertical alignment from 2 cm to 50 cm, and in lateral misalignment positions that were stretched across 2, 5, 8, 10, and 15 cm ranges. Simulated and experimental results demonstrated improved transfer distances when the drone battery load was 100 Ω. With the proposed design, the vertical transfer power that was achieved was 21.12 W, 0.460 A, with 81.5% transfer efficiency, while the maximum lateral misalignment air gap that was achieved was 2 cm with 19.22 W and 74.15% efficiency. This study provides evidence that the developed circuit that is based on magnetic resonant coupling (MRC) is an effective technique towards improving power transfer efficiency across different remote and unmanned Internet of Things (IoT) applications, including drones for radiation monitoring and smart agriculture.

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“…Wireless energy transfer (WET) is not a novel method to transfer electricity from the source to the load, and this method is backed to 1888 when Heinrich Hertz experimented evidence of radio wave by using a spark gap radio transmitter and 1899 when Nikola Tesla showed the experiment in transmitting high AC voltage by using inductive and capacitive coupling method in Colorado [1]. The experiment was a success but poorly received by the community.…”

Section: Introductionmentioning

confidence: 99%

“…The widely used technique in daily and practical application is near field such as mobile charging or small-scale electronics devices [4]. Currently, the WET application is moving toward technology to support vehicle charging [14] and renewable energy [1][15] [16], which are demanded due to the current increment of electric vehicles and renewable energy technology.…”

Section: Introductionmentioning

confidence: 99%

The impact of Nodes Distance on Wireless Energy Transfer System

Risma

Dewi

Oktarina

2020

KINETIK

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Wireless energy transfer (WET) reemerges as the method for transmitting electric power without the necessity to deal with cable losses and an aesthetically pleasing environment. The problem with WET is how to maintain magnetic induction as the distance gets further. This paper investigates the impact of nodes distance on the WET system. The experimental results show that the most effective distance among transmitter, nodes, and receiver are 4 cm. The measurement is taken with and without load. The without load application give that for node 1; the results are 6 V, 110 mA, and 2.85 mT for voltage, current, and magnetic flux, respectively. At the application of 2 nodes, the voltage is 6.8 V, the current is 0.124 mA, and the magnetic flux is 3.83 mT, and at three nodes installation, it is 7 V, 134 mA, and 3.83 mT. During the application of 3-Watt and 5-Watt lamp, at 4 cm distance, the power received is 1.66 W and 3.66 W at 3-Watt and 5-Watt lamp for one node, 1.84 W, and 3.84 for two nodes, and 1.93 W and 3.93 for three nodes. The experimental results show that the transmitted signal can be prolonged by installing nodes. Even though this study shows that 4 cm is the most effective, it is possible to increase up to 20 cm to power a 3-Watt lamp and 5-Watt lamp.

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Investigation of wireless power transfer applications with a focus on renewable energy

Cited by 49 publications

References 105 publications

On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks

On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks

Wireless Drone Charging Station Using Class-E Power Amplifier in Vertical Alignment and Lateral Misalignment Conditions

The impact of Nodes Distance on Wireless Energy Transfer System

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