Wireless Power Transfer Technique Research Articles

An improved deep Q-network approach for charging sequence scheduling with optimal mobile charging cost and charging efficiency in wireless rechargeable sensor networks

Mobile charging is a practical solution to overcome energy constraints in wireless rechargeable sensor networks (WRSNs). It utilizes a mobile charger (MC) to charge sensors based on the wireless power transfer technique via a charging scheduling scheme. However, how to schedule MC to achieve higher charging efficiency with less mobile charging cost, while ensuring network functionality remains a challenge. Specifically, the mobile charging cost is the total energy consumed by the MC during the charging task. This paper studies the charging sequence scheduling problem with optimal mobile charging cost and charging efficiency (CSCE), considering dynamic changes in sensor energy consumption. Moreover, we model the CSCE as a multi-objective mixed integer nonlinear programming. To address this issue, we propose an improved deep Q network approach for CSCE (IDQN-CSCE), where the MC acts as an agent to explore the WRSN and determine a charging policy based on the charging demand of sensors. IDQN-CSCE employs Q-learning and deep Q-networks (DQN) to train the Q-table and DQN network simultaneously. Charging actions are selected based on probability, and the probability of using Q-learning decreases as iteration steps increase. Additionally, we design a novel reward function consisting of a weighted sum of rewards and penalties fed back by the environment after performing a charging action. Simulation results show that IDQN-CSCE achieves higher charging efficiency than other baseline approaches with less mobile charging cost.

Combined‐harmonics wireless power transfer system

AbstractA technique for wireless power transfer (WPT) efficiency improvement by a proper design of the excitation waveform is presented. This improvement is obtained on the one hand by a combined‐harmonics excitation, and on the other hand by exploiting multiple‐resonance coupled resonators. In contrast to wireless communications, there is no constraint on the linearity of the transmitter and receiver in a WPT system. Therefore, the impact of the excitation waveform on the power transfer efficiency with the help of an analytical model is investigated. An optimum excitation waveform is determined to maximise the power transfer efficiency. Thereafter, the authors concentrate on designing a multiple‐resonance coupled resonator system that is consistent with the determined excitation waveform. This work introduces a non‐uniform spiral resonator for controlling the self‐resonant frequencies, which is consistent with the required excitation waveform. The performance of the designed coupled resonators is then evaluated using a 3D finite‐element method and experiments. The numerical simulation and experimental results are in good agreement, verifying the validity of our design.

A DDPG-based energy efficient federated learning algorithm with SWIPT and MC-NOMA

Federated learning (FL) has emerged as a promising distributed machine learning technique. It has the potential to play a key role in future Internet of Things (IoT) networks by ensuring the security and privacy of user data combined with efficient utilization of communication resources. This paper addresses the challenge of maximizing energy efficiency in FL systems. We employed simultaneous wireless information and power transfer (SWIPT) and multi-carrier non-orthogonal multiple access (MC-NOMA) techniques. Also, we jointly optimized power allocation and central processing unit (CPU) resource allocation to minimize latency-constrained energy consumption. We formulated an optimization problem using a Markov decision process (MDP) and utilized a deep deterministic policy gradient (DDPG) reinforcement learning algorithm to solve our MDP problem. We tested the proposed algorithm through extensive simulations and confirmed it converges in a stable manner and provides enhanced energy efficiency compared to conventional schemes.

Powering Implanted Devices Wirelessly Using Spider-Web Coil

Implantable biomedical (IBM) systems and biomedical sensors can improve life quality, identify sickness, monitor biological signs, and replace the function of malfunctioning organs. However, these devices compel continuous battery power, which can be limited by the battery's capacity and lifetime, reducing the device's effectiveness. The wireless power transfer (WPT) technique, specifically magnetic resonator coupling (MRC), was utilized to address the limited battery capacity of IBMs. By using WPT–MRC, the device can obtain power wirelessly, thereby reducing the need for frequent battery replacements and increasing the device's potential. In this research, spider-web coil (S-WC) based MRC–WPT was conceived and carried out experimentally to enhance low-power IBM's rechargeable battery usage time. The presented S-WC–MRC–WPT design uses series–parallel (S–P) configuration to power the IBM. Both transmitter and receiver coils exhibit an operating oscillation frequency of 6.78 MHz. The paper reports on experiments performed in the laboratory to assess the performance of the proposed design in terms of output DC at three different resistive loads and transmission distances with alignment conditions among the receiver and the transmitter coils. Various transfer distances ranging from 10 to 100 mm were investigated to analyze the DC output current (Idc). Specifically, under a 30 V voltage source (VS) and a transfer distance of 20 mm, the DC output current was observed to be 330, 321, and 313 mA at resistive loads of 50, 100, and 150 Ω, respectively.

A Wide Input Range All-NMOS Rectifier With Gate Voltage Boosting Technique for Wireless Power Transfer

This brief presents an all-NMOS RF-DC rectifier with a wide high power conversion efficiency (high-PCE) input power range by utilizing gate voltage boosting technique (GVBT). The all-NMOS architecture combines the benefits of crosscoupled and GVBT-based diode-like rectifiers for maximum electron mobility and reduced the conduction losses. The GVBT applied to rectifying transistors not only reduces the reverse leakage current, but also enhances the conductivity. As a result, the PCE and the input power range are improved simultaneously. The proposed rectifier is fabricated with a 0.18-lm standard CMOS technology. The measurement results show that the all-NMOS rectifier achieves 57.6% PCE, -14.8 dBm sensitivity and large than 20 dB high-PCE input power range with a 10 kΩ load.

Recent advances in wireless power transfer technologies for electric vehicles

In today’s society where electric vehicles are widely used, it is particularly important to make electric vehicles more efficient and convenient to charge. Wireless power transfer technology is becoming increasingly popular as a new type of charging technology. Different from conventional charging strategies, wireless power transfer becomes a hot topic in industry and academia due to the application possibility. It can not be ignored that this technology can also effectively reduce energy consumption. And the technology contributes to improve some environmental issues. Without doubt that it is a kind of beneficial clean energy source in today’s society. In this paper, the state-of-the-art wireless power transfer technologies are comprehensively review in terms of operation characteristics and optimization strategies. Meanwhile, a comparative analysis is given with different application scenarios, including the cost and power conversion efficiency. At the same time, the future perspectives for developing the wireless power transfer techniques are given.

An Empirical Survey on Various Power Transfer Techniques in Electrical Vehicle using Wireless Mode

This study examines the current condition of the wireless power transfer (WPT) techniques in electric vehicle. The pros and downsides of wireless power transfer are explored, as well as its classification, application, trend, benefits and impact on society. It also offers a comparison of prior research in transfer the power wireless, pointing out upcoming different kind of method, topologies, statement, and optimization methods implemented for boost the efficiency of performance of the electric vehicle system and directing researchers in the appropriate direction for future research.

Walk-to-Charge Technology: Exploring Efficient Energy Harvesting Solutions for Smart Electronics

Wearable sensors offer great potential in sports, fitness, and medicine. However, their limited battery life poses a major obstacle to their widespread use. This paper explores various energy solutions to extend the battery life of wearable sensors. The first part of the paper focuses on hardware improvements for wearable sensors, such as employing low-power sensors, energy- efficient microcontrollers, and power management circuits. The second part discusses the utilization of solar, thermal, and kinetic energy harvesting techniques to power wearable sensors. These methods aim to harness energy from the environment to supplement or replace battery power. The third part examines wireless power transfer techniques like radio frequency and magnetic resonance, which enable continuous power supply to wearable sensors without the need for physical connections. Software optimization is also highlighted as a crucial aspect in reducing energy consumption. This involves developing efficient algorithms for data processing and transmission, as well as implementing sleep and wake-up modes to minimize power usage during idle periods. Furthermore, the paper emphasizes the importance of user interaction and behavior in improving energy efficiency. It suggests the development of user-friendly interfaces and providing users with feedback on their energy usage.

Enhancing UAV communication links with Reconfigurable intelligent surfaces

Reconfigurable intelligent surfaces (RIS) have emerged as a prominent and widely debated solution to enhance the energy efficiency of wireless communications. This article explores the potential of combining RIS with unmanned aerial vehicles (UAVs)-RIS, to provide on-demand deployment services in dynamic environments. However, the energy limitations of battery-powered UAVs can curtail the advantages of UAV-RIS systems. To address this challenge and enhance the durability of UAV-RIS deployments, we introduce an energy harvesting technique for simultaneous wireless information and power transfer (SWIPT) coupled with optimized resource allocation and energy harvesting from incoming radio frequency (RF) signals. In contrast to previous research, our approach involves the division of passive reflected arrays across geometric space, facilitating simultaneous information transfer and energy harvesting. Additionally, we are developing deep Q-network (DQN) and deep deterministic policy gradient (DDPG) techniques to dynamically allocate UAV-RIS resources in both temporal and spatial dimensions. This allocation maximizes the overall harvested energy while upholding communication quality for every user. Our simulation results conclusively demonstrate the substantial superiority of the proposed UAV-RIS SWIPT system over the benchmark.

Load and Coupling Variations Analysis of Capacitive Power Transfer at 6.78MHz Operating Frequency for Biomedical Implantable Device

This paper presents the design and analysis of load and coupling variations for a current Wireless Power Transfer (WPT) technique, known as Capacitive Power Transfer (CPT). Due to its strength, CPT becomes an effective and essential alternative to conservative technique, which is Inductive Power Transfer (IPT). It can compete IPT in industrial demand since it has a small number of component usage, uncomplicated topology, increases electromagnetic interference (EMI) shielding performance and robust to surrounding metallic elements. Class E power amplifier with the presence of π1b matching resonant circuit is applied in this work as a high frequency ac power source since it has the ability to perform dc-to-ac inversion efficiently. It supports the CPT system to attain a maximum power transmission. MATLAB software is used to design and simulate the CPT circuit; and the analysis is made up from the results. This proposed system able to generate 1W of output power by maintaining up to 98% efficiency at 6.78MHz operating frequency for Biomedical Implantable Device application. The analysis of load variation is in the range of 50Ω until 1kΩ; meanwhile for coupling variation is between 1mm to 15mm.

Multi-coil wireless power transfer (WPT) technique for boosting efficiency in large air gap systems

An energy-efficient high-powermulti-coil wireless power transfer system (WPT) has been studied in this paper. The proposed system was first analyzed and examined using theoretical modeling; this was followed by finite element analysis and circuit simulation to confirm the goal. As the air gap between the transmitter and receiver coils widens, the coupling coefficient of a WPT system will drop. A large-air-gap WPT system’s coupling coefficient can be raised by adding relay coils between the transmitting and receiving coils. On the other hand, an increased coupling coefficient improves the system’s overall power transfer efficiency. The suggested multi-coil system, which has an air gap of 15 cm and a lateral misalignment of 3 cm between the transmitting and receiving coils, has been simulated and verified using the Maxwell 3-D finite element tool and Ansys Simplorer circuit simulation software.

Latency Minimization for IRS-Aided NOMA MEC Systems With WPT-Enabled IoT Devices

Mobile edge computing (MEC) and intelligent reflecting surface (IRS) are envisioned as two promising technologies that enable massive connectivity in the future Internet of Things (IoT) networks. MEC allows IoT devices (IDs) to offload their computation intensive tasks, and thus, can prolong their lifespan. In contrast, the IRS can enhance the channel condition between IDs and the access points (APs), which are colocated with the MEC server. Wireless power transfer technique enabling energy harvesting for IDs helps realizing sustainable IoT network. This paper applies IRS in a multi-ID MEC system for better latency performance. We first propose a multiple access scheme with hybrid frequency division and non-orthogonal access technologies and then design a timing protocol for the IDs. Based on the above design, we study the latency optimization problem with joint optimization of power allocation, the IRS phase shift matrix, and uplink and downlink beamformer under maximum power constraint for the IDs and AP. To tackle the formulated multi-variable non-convex problem, we split the target problem into several sub-problems and provide a nearoptimal low-complexity ID clustering scheme. Afterwards, we derive optimal solutions to these sub-problems, and a lowcomplexity fast-convergence alternating algorithm is proposed to minimize the overall latency. Presented simulation results verify the convergence of the alternating algorithm, and its superiority over the benchmarks.

Wireless Power Transfer in Electric Vehicles: A Review on Compensation Topologies, Coil Structures, and Safety Aspects

The scarce availability of non-renewable sources and the staggering amount of pollution have inevitably provoked many countries to opt for renewable sources. Thence, invariably, more renewable energy-based applications are hoarded by market stakeholders. Compared to all spheres of renewable energy applications, a considerable part of the energy is pulled into transportation. Wireless power transfer techniques play a significant role in charging infrastructure, considering the current development and advancement in the automotive industry. It will promise to overcome the widely known drawbacks of wired charging in electric vehicles. The effectiveness of wireless charging depends on coil design, compensation techniques, and the airgap between the coils. However, coil misalignment, improper compensation topologies, and magnetic materials reduce the efficacy. We can improve efficacy by overcoming the problems mentioned above and optimizing charging distance, time, and battery size. This paper comprehensively discussed the various electric vehicle charging technologies in conjunction with common charging standards, a list of factors affecting the charging environment, and the significance of misalignment problems. Furthermore, this review paper has explored the suitable coil design structure and different compensation techniques for an efficient wireless charging network.

The Fifth Bioelectronic Medicine Summit Hosted by the Feinstein Institutes for Medical Research (Manhasset, NY) and Columbia Engineering (NY, NY) at The Garden City Hotel, Garden City, NY 11530 on October 11-12th, 2022- Bioelectronic Medicine: Today’s Tools, Tomorrow’s Therapies

The Fifth Bioelectronic Medicine Summit Hosted by the Feinstein Institutes for Medical Research (Manhasset, NY) and Columbia Engineering (NY, NY) at The Garden City Hotel, Garden City, NY 11530 on October 11-12th, 2022- Bioelectronic Medicine: Today’s Tools, Tomorrow’s Therapies

Autonomous Resonant Frequency Tuner for a 6.78MHz Inductive Coupling Wireless Power Transfer System to Stably Maximize Repeater Current

Recently, the resonant inductive coupling wireless power transfer (RIC-WPT) technique is being widely used to charge small IoT devices dispersed in a wide area, e. g., an office desk and warehouse rack. In this application, the repeater is utilized to expand the chargeable area without an additional AC power source. The repeater comprises a LC resonator commonly with a high-quality factor to induce large current in the repeater coil. However, this causes the problem that the repeater performance is highly susceptible to the variation in its resonant frequency due to the manufacturing tolerance of coil inductance and resonant capacitance as well as the variation of the magnetic coupling between the transmitter and repeater coils. To solve this problem, a previous study has proposed a concept of the autonomous resonant frequency tuning circuit to stably maximize repeater coil current, although this study implemented a part of this control system as a practical circuit. This paper aims to develop a complete autonomous resonant frequency tuning circuit that implements the aforementioned concept. The proposed circuit adjusts the resonant frequencies of the transmitter and repeater by utilizing the Automatic Tuning Assist Circuits. These frequencies are optimized using the infrared wireless signal communication from the transmitter to the repeater. Along with the operating principle of the proposed circuit, this study presents detailed circuit design as well as the experimental results, which verified the stable autonomous maximization of the repeater coil current against the variation in the resonant frequency of the repeater resonator.

An Improved Energy Saving Technique for Wireless Power Transfer in Near Field Communication Systems

In this work, an improved communication algorithm was developed to reduce energy wastage in a Near Field Communication (NFC) system using dynamic field Strength scaling technique. With a variable resistor in the reader coil, the field strength of the system was scaled in real-time by adjusting the value of the resistor in relation to distance. This system was tested with the advanced design system's Application Extension Language (AEL) and simulated on Advanced Digital Technology. The results showed a responsive change in the magnetic field when the two scenarios (with and without optimization) were simulated. There was a 66% change in energy transfer within the time frame referenced. Results further indicated that the adoption of the proposed algorithm could help engineers to design a more effective NFC system.

User Scheduling and Trajectory Optimization for Energy-Efficient IRS-UAV Networks With SWIPT

This paper investigates user scheduling and trajectory optimization for a network supported by an intelligent reflecting surface (IRS) mounted on an unmanned aerial vehicle (UAV). The IRS is powered via the simultaneous wireless information and power transfer (SWIPT) technique. The IRS boosts users uplink signals to improve the network longevity and energy efficiency. It simultaneously harvests energy with a non-linear energy harvesting circuit and reflects the incident signals by controlling its reflection coefficients and phase shifts. The trajectory of the UAV impacts the efficiency of these operations. We minimize the maximum energy consumption of all users by joint optimization of user scheduling, UAV trajectory/velocity, and IRS phase shifts/reflection coefficients while guaranteeing each user minimum required data rate and harvested energy of the IRS. We first derive a closed-form solution for the IRS phase shifts and then address the non-convexity of the critical problem. Finally, we propose an alternating optimization (AO) algorithm to optimize the remaining variables iteratively. We demonstrate the gains over several benchmarks. For instance, with a 50-element IRS, min-max energy consumption can be as low as 0.0404 (Joule), a 7.13% improvement over the No IRS case (achieving 0.0435 (Joule)). We also show that IRS-UAV without EH performs best at the cost of circuit power consumption of the IRS (a 20% improvement over the No IRS case).

A Temporal and Spatial Priority With Global Cost Recharging Scheduling in Wireless Rechargeable Sensor Networks

Wireless power transfer technique provides a new and promising method for alleviating the limited energy capacity problem, thus receiving much attention. However, previous works usually consider temporal, spatial, or both factors of the current selected node greedily without taking the residual moving distance of the remaining nodes into consideration. Surely, it is not easy to precisely estimate the residual moving distance of the remaining nodes before knowing their exact order in the scheduling path. In this work, the authors are the first to propose the concept of the residual moving distance (cost) and create a mathematical model to roughly estimate the cost of a given node set. Moreover, they design a temporal and spatial priority charging scheduling algorithm with additional considering the global cost (TSPG). Simulation results demonstrate that TSPG outperforms earliest deadline first scheduling algorithm and revised earliest deadline first scheduling algorithm. Moreover, the proposed new model for estimating moving distance in the residual area has all relative error below 9%.

Envisioning the future by encountering cables and adopting wireless - Power supply and charging

This paper discusses the importance of Wireless Power Transfer (WPT) in a rapidly changing world. The goal is to introduce new technologies that can transfer power without the hassle of connecting cords for every single work, making devices more portable with less wear and tear, and providing an uninterrupted supply of electricity in every region. Wireless Power Transfer plays a key role in bringing change to the usage of the latest or pre-existing technology with a lot of conveniences and within a short time. The paper sheds light on recent progress in Wireless Power Transfer techniques, wireless charging, new possibilities for the future in the field of Wireless Power Transfer, and the development of business merchandise. This technique has provided promising ways to overcome the energy restriction of conventionally transportable devices. The techniques of Wireless Power Transfer will provide a way of making the dream come true of supplying 24/7 electricity not only in cities but also in remote areas, which will help in the development of every village and town that is currently not in the mainstream. The paper provides a summary of Wireless Power Transfer techniques, major developments in technical fields, and the recent advancements in networking applications. It highlights the potential of Wireless Power Transfer to revolutionize the way to use technology and the benefits it can bring to individuals and countries.

Optimization of Resource Allocation in Unmanned Aerial Vehicles Based on Swarm Intelligence Algorithms

Due to their adaptability, Unmanned Aerial Vehicles (UAVs) play an essential role in the Internet of Things (IoT). Using wireless power transfer (WPT) techniques, an UAV can be supplied with energy while in flight, thereby extending the lifetime of this energy-constrained device. This paper investigates the optimization of resource allocation in light of the fact that power transfer and data transmission cannot be performed simultaneously. In this paper, we propose an optimization strategy for the resource allocation of UAVs in sensor communication networks. It is a practical solution to the problem of marine sensor networks that are located far from shore and have limited power. A corresponding system model is summarized based on the scenario and existing theoretical works. The minimum throughput-maximizing object is then formulated as an optimization problem. As swarm intelligence algorithms are utilized effectively in numerous fields, this paper chose to solve the formed optimization problem using the Harris Hawks Optimization and Whale Optimization Algorithms. This paper introduces a method for translating multi-decisions into a row vector in order to adapt swarm intelligence algorithms to the problem, as joint time and energy optimization have two sets of variables. The proposed method performs well in terms of stability and duration. Finally, performance is evaluated through numerical experiments. Simulation results demonstrate that the proposed method performs admirably in the given scenario.