Wireless Power Transfer
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 Journal metrics
Acceptance rate30%
Submission to final decision71 days
Acceptance to publication25 days
CiteScore3.900
Journal Citation Indicator-
Impact Factor-

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 Journal profile

Wireless Power Transfer publishes original research and industrial developments relating to wireless power.

 Editor spotlight

Chief Editor Professor Nuno Borges Carvalho is based at the University of Aveiro and his main research interests include software-defined radio front-ends, wireless power transmission, nonlinear distortion analysis in microwave/wireless circuits and systems, and measurement of nonlinear phenome

 Special Issues

We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

Latest Articles

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Research Article

Optimal Path Planning for Wireless Power Transfer Robot Using Area Division Deep Reinforcement Learning

This paper aims to solve the optimization problems in far-field wireless power transfer systems using deep reinforcement learning techniques. The Radio-Frequency (RF) wireless transmitter is mounted on a mobile robot, which patrols near the harvested energy-enabled Internet of Things (IoT) devices. The wireless transmitter intends to continuously cruise on the designated path in order to fairly charge all the stationary IoT devices in the shortest time. The Deep Q-Network (DQN) algorithm is applied to determine the optimal path for the robot to cruise on. When the number of IoT devices increases, the traditional DQN cannot converge to a closed-loop path or achieve the maximum reward. In order to solve these problems, an area division Deep Q-Network (AD-DQN) is invented. The algorithm can intelligently divide the complete charging field into several areas. In each area, the DQN algorithm is utilized to calculate the optimal path. After that, the segmented paths are combined to create a closed-loop path for the robot to cruise on, which can enable the robot to continuously charge all the IoT devices in the shortest time. The numerical results prove the superiority of the AD-DQN in optimizing the proposed wireless power transfer system.

Research Article

Intelligent Power Grid Video Surveillance Technology Based on Efficient Compression Algorithm Using Robust Particle Swarm Optimization

Companies that produce energy transmit it to any or all households via a power grid, which is a regulated power transmission hub that acts as a middleman. When a power grid fails, the whole area it serves is blacked out. To ensure smooth and effective functioning, a power grid monitoring system is required. Computer vision is among the most commonly utilized and active research applications in the world of video surveillance. Though a lot has been accomplished in the field of power grid surveillance, a more effective compression method is still required for large quantities of grid surveillance video data to be archived compactly and sent efficiently. Video compression has become increasingly essential with the advent of contemporary video processing algorithms. An algorithm’s efficacy in a power grid monitoring system depends on the rate at which video data is sent. A novel compression technique for video inputs from power grid monitoring equipment is described in this study. Due to a lack of redundancy in visual input, traditional techniques are unable to fulfill the current demand standards for modern technology. As a result, the volume of data that needs to be saved and handled in live time grows. Encoding frames and decreasing duplication in surveillance video using texture information similarity, the proposed technique overcomes the aforementioned problems by Robust Particle Swarm Optimization (RPSO) based run-length coding approach. Our solution surpasses other current and relevant existing algorithms based on experimental findings and assessments of different surveillance video sequences utilizing varied parameters. A massive collection of surveillance films was compressed at a 50% higher rate using the suggested approach than with existing methods.

Research Article

Optimization of a Two-Layer 3D Coil Structure with Uniform Magnetic Field

Conventional magnetically coupled resonant wireless power transfer systems are faced with resonant frequency splitting phenomena and impedance mismatch when a receiving coil is placed at misaligned position. These problems can be avoided by using uniform magnetic field distribution at receiving plane. In this paper, a novel 3D transmitting coil structure with improved uniform magnetic field distribution is proposed based on a developed optimization method. The goal is to maximize the average magnetic field strength and uniform magnetic field section of the receiving plane. Hence, figures of merit (FoM1 and FoM2) are introduced and defined as product of average magnetic field strength and length or surface along which uniform magnetic field is generated, respectively. The validity of the optimization method is verified through laboratory measurements performed on the fabricated coils driven by signal generator at operating frequency of 150 kHz. Depending on the allowed ripple value and predefined coil proportions, the proposed transmitting coil structure gives the uniform magnetic field distribution across 50% to 90% of the receiving plane.

Research Article

Inhomogeneous Winding for Loosely Coupled Transformers to Reduce Magnetic Loss

Wireless power transfer has been proved promising in various applications. The homogeneous winding method in loosely coupled transformers incurs unnecessary intense magnetic field distribution in the center and causes extra magnetic loss. An inhomogeneous winding method is proposed in this paper, and a relatively homogeneous magnetic field distribution inside the core is achieved. This paper investigated the magnetic loss of homogeneous winding and inhomogeneous winding for wireless power transfer. A theoretical model was built to evaluate magnetic loss under inhomogeneous winding. The coupling coefficient and magnetic loss were investigated individually and comparisons were made between different width ratio combinations. Theoretical analysis was validated in experiments.

Research Article

An Autonomous Wireless Sensor Node Based on Hybrid RF Solar Energy Harvesting

The widespread deployment of the Internet of Things (IoT) requires the development of new embedded systems, which will provide a diverse array of different intelligent functionalities. However, these devices must also meet environmental, maintenance, and longevity constraints, while maintaining extremely low-power consumption. In this work, a batteryless, low-power consumption, compact embedded system for IoT applications is presented. This system is capable of using a combination of hybrid solar and radiofrequency power sources and operates in the 900 MHz ISM band. It is capable of receiving OOK or ASK modulated data and measuring environmental data and can transmit information back to the requester using GFSK modulated data. The total consumption of the system during its sleep state is 920 nW. Minimum power required to operate is −15.1 dBm or 70 lux, when using only radiofrequency or solar powering, respectively. The system is fully designed with components off the shelf (COTS).

Research Article

Optimal Wireless Information and Power Transfer Using Deep Q-Network

In this paper, a multiantenna wireless transmitter communicates with an information receiver while radiating RF energy to surrounding energy harvesters. The channel between the transceivers is known to the transmitter, but the channels between the transmitter and the energy harvesters are unknown to the transmitter. By designing its transmit covariance matrix, the transmitter fully charges the energy buffers of all energy harvesters in the shortest amount of time while maintaining the target information rate toward the receiver. At the beginning of each time slot, the transmitter determines the particular beam pattern to transmit with. Throughout the whole charging process, the transmitter does not estimate the energy harvesting channel vectors. Due to the high complexity of the system, we propose a novel deep Q-network algorithm to determine the optimal transmission strategy for complex systems. Simulation results show that deep Q-network is superior to the existing algorithms in terms of the time consumption to fulfill the wireless charging process.

Wireless Power Transfer
Publishing Collaboration
More info
CUP logo
 Journal metrics
Acceptance rate30%
Submission to final decision71 days
Acceptance to publication25 days
CiteScore3.900
Journal Citation Indicator-
Impact Factor-
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.