Search Results (42)

Lithium-ion battery (LIB) wireless charging using inductive power transfer (IPT) represents a transformative pathway for transportation electrification. While applications in railway systems remain limited, early studies highlight significant promises for implementation. This paper presents a hybrid energy-supply framework integrating LIB, inductive battery charging (BC) charging, and battery swapping (BS) to support a 20 km heritage trolley excursion between Belmont and Gastonia, NC. A kinematic simulation was developed to estimate traction energy demand, yielding 56 kWh per trip, or 112 kWh for two daily round trips. Finite element analysis (FEA) was conducted to design an LCL-s compensated 3 kW IPT system. Two transmitter configurations were evaluated: W–I ferrite cores (peak coupling ~0.22) and magnetic concrete slabs (~0.20). Although ferrite offers higher efficiency, magnetic concrete demonstrates superior durability and integration potential. Simulation results indicate that wireless charging alone, whether static or dynamic, is insufficient; similarly, a single daily BS strategy provides only 96 kWh. Seven BC-BS hybridization scenarios were evaluated, showing that mid-day swaps combined with either static or dynamic IPT produce a 12–16 kWh surplus. The most practical approach is a one-pack swap supplemented by uniformly distributed static pads, providing energy neutrality. This hybrid pathway ensures operational sufficiency, structural resilience, and compatibility with heritage rail preservation. Full article

This paper addresses the critical challenge of deploying a minimum number of wireless charging pads (WCPs) in obstacle-rich, large-scale Wireless Rechargeable Sensor Networks (WRSNs) to sustain drone operations. We assume a single base station, stationary sensors, convex polygonal obstacles that drones must avoid, and that both the base station and WCPs provide unlimited energy. To solve this, we propose the Outside-to-Inside Onion-Peeling (OIOP) strategy, a novel two-stage algorithm that prioritizes the coverage of the most remote sensors first and then refines the deployment by removing redundant pads while strictly adhering to obstacle constraints. Simulation results demonstrate OIOP’s superior efficiency: it reduces the number of required pads by approximately 10.83% ± 1.30% and 12.16% ± 1.59% compared to state-of-the-art methods (SMC and MC) and achieves execution times that are 58.02% ± 2.44% and 72.09% ± 2.88% faster, respectively. The algorithm also exhibits remarkable robustness, showing the smallest performance degradation as obstacle density increases. Full article

Wireless power transfer systems (WPTSs) are critical for efficient and reliable electric vehicle (EV) charging, but challenges such as misalignment and coupling variations limit their performance. This paper addresses a proposed design approach for WPTSs by optimizing the following two widely used coil types: ring and spiral circular coils. An analytical estimation of inductive characteristics is conducted to establish a foundation for system optimization. The study framework focuses on coil geometrical parameters and relative placements, accounting for horizontal, vertical, and angular misalignments to ensure a consistent performance under varying coupling conditions. COMSOL simulations accurately determine inductive parameters, validating the theoretical analysis for a 200 W charging coil prototype. Experimental investigations of coupling coefficients for coreless and cored charging pads highlight the superior performance of the Square I-Core-based spiral winding configuration in enhancing the coupling coefficient while ensuring that it remains below the critical value required for stable system operation. The agreement between the analytical results, simulation data, and experimental findings underscores the reliability of the proposed design approach. Full article

In recent years, a key problem in wireless sensor networks has been how to effectively deploy the minimum number of wireless charging pads while establishing at least one feasible charging path from the base station. This ensures that the unmanned aerial vehicle can reach and recharge all sensor nodes from the BS. Previous works have often employed greedy algorithms to solve the optimal deployment problem, treating coverage and connectivity as interdependent properties. This has led to excessive constraints on the placement of wireless charging pads, as each newly added charging pad has to satisfy both properties at the same time. Additionally, previous works have overlooked the critical issue of avoiding the occurrence of isolated sensor nodes in uncovered fragmented regions, in deployment. Failing to address this issue requires additional deployment costs to compensate for uncovered nodes. To overcome these limitations, in this work, we propose a sink-outward strategy wireless charging pad deployment algorithm, which deploys charging pads layer by layer from the innermost region outward, prioritizing coverage before connectivity. The proposed sink-outward max covering (SMC) consists of two key steps: initial pad deployment and optimization. The simulation results show that the proposed method SMC combined with the optimization step, called reducing pads by reallocating pads partially (RPRAP), achieves a reduction in pad count of 10.6–19.8% compared with the methods used in previous works, and the execution time demonstrated in previous works is several to tens of times longer than that of SMC combined with RPRAP. Moreover, the proposed redundant pad removal step, RPRAP, not only removes more redundant pads than the methods used in previous works but also drastically reduces processing time in large-scale wireless sensor networks with many redundant pads. Full article

The aim of this work is the design of a 200 W transmitting coil for a high-power wireless power transfer (WPT) system based on magnetic resonant coupling (MRC) to charge the battery of a drone in 1 h equipped with a WPT receiving coil integrated into the landing gear. This innovative solution is based on the use of the landing gear as the receiving coil, thereby obviating the need for an additional component (e.g., separate receiving coil). The proposed landing gear is fabricated from aluminum, to reduce weight, and to improve mechanical robustness and electrical performance. Consequently, the design reduces overall weight and system complexity while minimizing potential destabilization of the drone’s flight dynamics. However, a specific design of the primary coil is required to ensure high efficiency even in case of an inaccurate landing of the drone on a ground pad. To this aim, a double-D configuration is here proposed and optimized for the transmitting coil, while a double coil receiver in combination with a charge controller that uses a maximum power point tracking (MPPT) algorithm is integrated into the landing gear. The results obtained from the simulations demonstrate that the proposed WPT system has excellent electrical efficiency and very high tolerance to coil misalignment in terms of the coupling coefficient due to imprecise landing. The transmission efficiency of the final test prototype can reach 95% with a coupling coefficient of k = 0.16, and it can drop to a minimum of 85% when misalignment occurs resulting in k = 0.06. Full article

The rapid adoption of electric vehicles (EVs) and the increasing reliance on renewable energy sources necessitate innovative charging infrastructure solutions to address key challenges in energy efficiency, grid stability, and sustainable transportation. Dynamic wireless charging systems, which enable EVs to charge while in motion, offer a transformative approach to mitigating range anxiety and optimizing energy utilization. However, these systems face significant operational challenges, including dynamic traffic conditions, uncertain EV arrival patterns, energy transfer efficiency variations, and renewable energy intermittency. This paper proposes a novel quantum computing-assisted optimization framework for the modeling, operation, and control of wireless dynamic charging infrastructure in urban highway networks. Specifically, we leverage Variational Quantum Algorithms (VQAs) to address the high-dimensional, multi-objective optimization problem associated with real-time energy dispatch, charging pad utilization, and traffic flow coordination. The mathematical modeling framework captures critical aspects of the system, including power balance constraints, state-of-charge (SOC) dynamics, stochastic vehicle arrivals, and charging efficiency degradation due to vehicle misalignment and speed variations. The proposed methodology integrates quantum-inspired optimization techniques with classical distributionally robust optimization (DRO) principles, ensuring adaptability to system uncertainties while maintaining computational efficiency. A comprehensive case study is conducted on a 50 km urban highway network equipped with 20 charging pad segments, supporting an average traffic flow of 10,000 EVs per day. The results demonstrate that the proposed quantum-assisted approach significantly enhances energy efficiency, reducing energy losses by up to 18% compared to classical optimization methods. Moreover, traffic-aware adaptive charging strategies improve SOC recovery by 25% during peak congestion periods while ensuring equitable energy allocation among different vehicle types. The framework also facilitates a 30% increase in renewable energy utilization, aligning energy dispatch with periods of high solar and wind generation. Key insights from the case study highlight the critical impact of vehicle alignment, speed variations, and congestion on wireless charging performance, emphasizing the need for intelligent scheduling and real-time optimization. The findings contribute to advancing the integration of quantum computing into sustainable transportation planning, offering a scalable and robust solution for next-generation EV charging infrastructure. Full article

Electric vehicles (EVs) wireless charging is enabled by inductive power transfer (IPT) technology, which eliminates the need for physical connections between the vehicle and the charging station, allowing power to be transmitted without the use of cables. However, in the present wireless charging equipment, the power transfer still needs to be improved. In this work, we present a power transfer structure using a unique “DD circular (DDC) power pad”, which mitigates the two major obstacles of wireless EV charging, due to the mitigating power of electromagnetic field (EMF) leakage emissions and the increase in misalignment tolerance. We present a DDC power pad structure, which integrates features from both double D(DD) and circular power pads. We first build a three-dimensional electromagnetic model based on the DDC structure. A detailed analysis is performed of the electromagnetic characteristics, and the device parameters regarding the power transfer efficiency, coupling coefficient, and mutual inductance are also presented to evaluate the overall performance. Then, we examine the performance of the DDC power pad under various horizontal and vertical misalignment circumstances. The coupling coefficients and mutual inductance, as two essential factors for effective power transmission under dynamic circumstances, are investigated. The findings of misalignment effects on coupling efficiency indicate that the misalignment does not compromise the DDC pad’s robust performance. Therefore, our DDC power pad structure has a better electromagnetic characteristic and a higher misalignment tolerance than conventional circular and DD pads. In general, the DDC structure we present makes it a promising solution for wireless EV charging systems and has good application prospects. Full article

Inductive wireless power transfer (IWPT) with stable output power and high efficiency is a major challenge for charging electric vehicles (EVs). This paper, for the first time, develops a robust IWPT system using a circular pad (CP) and double-D pad (DDP) with a self-oscillating controlled inverter (SOCI), which offers high steady output power and transfer efficiency under magnetic coupling variations simply with feedback from the transmitter-side current. The compact 2CP and 2DDP magnetic couplers with single identical coils are robust to self- and mutual-inductance variations, so the IWPT system exhibits greater robustness at increased transfer distances (air gaps), as well as in the presence of lateral and rotational misalignments between the two magnetic pads, compared to couplers using nonidentical transmitting primary (TP) and receiving secondary (RS) pads and numerous decoupled coils on the RS pad. Based on a thorough analysis and experimental study, the proposed 1 kW IWPT system with 2CP and 2DDP couplers with up to a 20 cm air gap achieves constant output power with 93% and 92% constant transfer efficiency, respectively. The 2CP with a 15 cm air gap and the 2DDP with a 20 cm air gap, with up to 12 cm lateral misalignment, can tolerate coupling variations. Full article

Recent advancements in Dynamic Wireless Power Transfer (DWPT) have highlighted the need for further research, particularly in the area of modelling and simulation techniques. As the power transferred between charging pads depends on vehicle position, the load profile of the DWPT is therefore a function of the vehicle’s movement which is dependent on user behaviour and is inherently stochastic. For DWPT, these events involve high instantaneous power and are short in duration. To better understand the impact of DWPT, accurate models are required to test control systems and potential solutions. Additionally, these systems require high-frequency simulation for DWPT, which results in long simulation times during development. This paper presents a simplified model for circuit components that eliminates high-frequency switching elements, enabling the use of larger simulation time steps and significantly reducing simulation time. By applying circuit analysis and calculating equivalent impedances, the model provides average circuit values that effectively represent waveform amplitudes without the need to simulate instantaneous, high-frequency variations. To ensure the efficiency of grid-connected simulations and achieve a level of accuracy that reflects the internal dynamics of wireless charging, subsystem simulations demonstrated significant time improvements at the cost of minimal accuracy loss. For DC/DC converters operating at 2 kHz, simulation time was reduced by 3× with only a 1% error. The DWPT subsystem, operating at 85 kHz, achieved an 18× reduction in simulation time with a 2.5% deviation. When combined, the full system resulted in a 30-fold reduction in simulation time with only a 6% deviation from the base model. Full article

Inductive power transfer (IPT) technology is used in various applications owing to its safety features, robust environmental adaptability, and convenience. In some special applications, the charging pads are required to be as compact as possible to accommodate practical spatial requirements, and even size requirements dictate that the diameter of the charging pad matches the air gap. However, such requirements bring about a decrease in the transmission efficiency, power, and tolerance to misalignment of the system. In this paper, by comparing a double-sided inductor–capacitor–capacitor (LCC), double-sided inductor–capacitor–inductor (LCL), series–series (SS), and inductor–capacitor–capacitor–series (LCC-S) compensation topologies in IPT systems, we identified a double-sided LCC compensation topology that is suitable for weak coupling coefficients. Furthermore, this study modeled and simulated the typical parameters of coreless coils in circular power pads, such as the number of coil layers, turns, wire diameter, and wire spacing, to enhance the mutual inductance of the magnetic coupler during misalignment and long-distance transmission. A wireless charging system with 640 W output power was built, and the experimental results show that a maximum dc-dc efficiency of over 86% is achieved across a 200 mm air gap when the circular power pad with a diameter of 200 mm is well aligned. The experimental results show that using a suitable compensation topology and optimizing the charging pad parameters enables efficient IPT system operation when the coupling coefficient is 0.02. Full article

Foreign object debris (FOD) includes any unwanted and unintentional material lying on the charging lane or parking lots, posing a risk to the wireless charging system, the vehicle, or the people inside. FOD in an Electric Vehicle (EV) wireless charging system can cause problems, including decreased charging efficiency, safety risks, charging system damage, communication issues, and health risks. To address this problem, this paper proposes the deep learning object detection network approach of using YOLOv4 (You Only Look Once), which is a single-shot detector. Additionally, for real-time implementation, YOLOv4-Tiny is suggested, which is a compressed version of YOLOv4 designed for devices with low computational power. YOLOv4-Tiny enables faster inferences and facilitates the deployment of FOD detectors on edge devices. The algorithm is trained using the FOD dataset, consisting of images of common debris on runways or taxiways. Furthermore, utilizing the concept of transfer learning, the last few layers of the pre-trained YOLOv4 model are modified using the COCO (Common Objects in Context) dataset to transfer features to the new network and retrain the model on the FOD dataset. The results obtained using this YOLOv4 model yielded a precision rate of 99.05%, while the results from YOLOv4-Tiny achieved a precision rate of 97.74%, with an average inference time of 150 ms under the ambient light and weather conditions. Full article

The recent advancement in wireless power transmission (WPT) has led to the development of wireless rechargeable sensor networks (WRSNs), since this technology provides a means to replenish sensor nodes wirelessly, offering a solution to the energy challenges faced by WSNs. Most of the recent previous work has focused on charging sensor nodes using wireless charging vehicles (WCVs) equipped with high-capacity batteries and WPT devices. In these schemes, a vehicle can move close to a sensor node and wirelessly charge it without physical contact. While these schemes can mitigate the energy problem to some extent, they overlook two primary challenges of applied WCVs: off-road navigation and vehicle speed limitations. To overcome these challenges, previous work proposed a new WRSN model equipped with one drone coupled with several pads deployed to charge the drone when it cannot reach the subsequent stop. This wireless charging pad deployment aims to deploy the minimum number of pads so that at least one feasible routing path from the base station can be established for the drone to reach every SN in a given WRSN. The major weakness of previous studies is that they only consider deploying a wireless charging pad at the locations of the wireless sensor nodes. Their schemes are limited and constrained because usually every point in the deployed area can be considered to deploy a pad. Moreover, the deployed pads suggested by these schemes may not be able to meet the connected requirements due to sparse environments. In this work, we introduce a new scheme that utilizes the Quad-Tree concept to address the wireless charging pad deployment problem and reduce the number of deployed pads at the same time. Extensive simulations were conducted to illustrate the merits of the proposed schemes by comparing them with different previous schemes on maps of varying sizes. In the case of large maps, the proposed schemes surpassed all previous works, indicating that our approach is more suitable for large-scale network environments. Full article

Dynamic wireless charging (DWC) has emerged as a viable approach to mitigate range anxiety by ensuring continuous and uninterrupted charging for electric vehicles in motion. DWC systems rely on the length of the transmitter, which can be categorized into long-track transmitters and segmented coil arrays. The segmented coil array, favored for its heightened efficiency and reduced electromagnetic interference, stands out as the preferred option. However, in such DWC systems, the need arises to detect the vehicle’s position, specifically to activate the transmitter coils aligned with the receiver pad and de-energize uncoupled transmitter coils. This paper introduces various machine learning algorithms for precise vehicle position determination, accommodating diverse ground clearances of electric vehicles and various speeds. Through testing eight different machine learning algorithms and comparing the results, the random forest algorithm emerged as superior, displaying the lowest error in predicting the actual position. Full article

In the context of inductive power transfer (IPT) for electric vehicle (EV) charging, the precise determination of the mutual inductance between the magnetic pads is of critical importance. The value of this inductance varies depending on the EV positioning, affecting the power transfer capability. Therefore, the precise determination of its value yields various advantages, particularly by contributing to the optimization of the charging process of the EV batteries, since it offers the possibility of adjusting the position of the vehicle depending on the level of misalignment. Within this framework, algorithms grounded in artificial intelligence (AI) techniques emerge as promising solutions. This research work revolves around the estimation of the mutual inductance in a wireless inductive power transfer system using a resonant converter topology, implemented in MATLAB/Simulink^® R2021b. The system output was developed to emulate the behavior of a battery charger. To estimate this parameter, an artificial neural network (ANN) was developed. Given the characteristics of the system, the features were chosen in a way that they could provide a clear indication to the ANN if the vehicle position changed, independently of the charging power. In the pursuit of creating a robust AI model, the training dataset contained approximately 1% of the available data. Upon the analysis of the results, it was verified that the largest estimation error observed was around 3%, occurring at the lowest charging power considered. Hence, it can be inferred that the proposed ANN exhibits the capability to accurately estimate the value of mutual inductance in this type of system. Full article

Wireless charging (WC) has gained popularity for the charging of electric vehicles in recent years of research, particularly dynamic wireless charging systems (DWCSs). Among the different topologies of DWCSs, this paper focuses on an inductively coupled wireless charging system (ICWCS). In this ICWCS, double-D (DD) coils create horizontal and vertical flux components between different pad configurations, which show optimal features in contrast to circular pad coils. In this work, the three-dimensional (3D) finite element technique (FEM) is used to establish the proposed design to observe the coupling coefficient, while the system design’s performance is evaluated using a circuit simulator. In the simulation, the proposed DD coil configuration is used for both the transmitter and receiver sides. It provides the maximum coupling coefficient and efficiency at perfect alignment when using an in-between air gap of 166 mm and six I-type ferrite bars on the transmitter side and five I-type ferrite bars on the receiver side. The coupling coefficient and system parameters, such as power and efficiency, are considered for different misalignments in the proposed configuration. The results of this work satisfy the Society of Automotive Engineers (SAE) J2954 Class 3 criteria. The best results obtained are on account of optimizing the ferrite core, which is achieved by varying its length and width. While varying the ferrite core’s dimensions, 0.2451, as the optimal k value, is obtained at the effective width and length of 57.5 mm and 400 mm, respectively. The simulation results of the Ansys Maxwell 3D software prove the feasibility of the proposed structure. Full article