Search Results (81)

In recent years, the need for autonomous underwater vehicles (AUVs) for offshore infrastructure maintenance and oceanographic surveillance has been prominently increasing. Continuous monitoring and surveillance are the essential tasks the AUVs are designed to perform. However, the long endurance of the AUV is a challenging task due to the limited size and capacity of the onboard battery. The conventional way of recharging using battery swapping or a wet mate connector limits the autonomy of the AUV. Underwater wireless power transfer (UWPT) technology seems to be a suitable alternative for overcoming the above limitations, which can provide autonomy to the AUV charging process. However, designing a UWPT system has its limitations in the marine environment and requires enough engineering studies of the different modules of the system. Different investigations are proposed in the literature on the UWPT system, both at the system level and circuit level. This article provides an overview of the latest advancements in the UWPT system and discusses marine power sources, power converter topologies, compensation topologies, and different types of magnetic couplers. The article also discusses the engineering challenges in designing a UWPT system, including eddy current loss and biofouling. The article also summarizes current research trends, potential challenges in UWPT, and future technological developments from prototypes to practical products and offers recommendations for further progress. Full article

Connected and Autonomous Electric Vehicles (CAEVs) and Uncrewed Aerial Vehicles (UAVs) are critical components of future Intelligent Transportation Systems (ITS), yet their deployment remains constrained by fragmented charging infrastructures and the lack of coordinated reservation and trip planning across static, dynamic wireless, and vehicle-to-vehicle (V2V) charging networks using magnetic resonance and laser-based power transfer. Existing solutions often struggle with misalignment sensitivity, unpredictable arrivals, and disconnected ground–aerial scheduling. This work introduces a three-layer architecture that integrates a handshake protocol for coordinated charging and billing, a misalignment correction algorithm for magnetic resonance and laser-based systems, and three scheduling strategies: Static Heuristic Charging Scheduling and Planning (SH-CSP), Dynamic Heuristic Charging Scheduling and Planning (DH-CSP), and the Safety, Scheduling, and Sustainability-Aware Feasibility-Enhanced Deep Deterministic Policy Gradient (SAFE-DDPG). SAFE-DDPG extends vanilla DDPG with feasibility-aware action filtering, prioritized replay, and adaptive exploration to enable real-time scheduling in heterogeneous and congested charging networks. Results show that SAFE-DDPG significantly improves scheduling efficiency, reducing average wait times by over 70% compared to DH-CSP and over 85% compared to SH-CSP, demonstrating its potential to support scalable and coordinated ground–aerial charging ecosystems. Full article

Wireless power transfer (WPT) has emerged as a key enabling technology for the large-scale adoption of electric vehicles (EVs), offering enhanced charging flexibility, improved safety, and seamless integration with intelligent transportation and renewable energy infrastructures. This paper presents a comprehensive review and technical synthesis of WPT technologies spanning both near-field and far-field domains, including inductive power transfer (IPT), magnetically coupled resonant WPT (MCR-WPT), capacitive power transfer (CPT), microwave power transfer (MPT), and laser wireless charging (LPT). Particular emphasis is placed on MCR-WPT, the most widely adopted approach for EV wireless charging, for which the coupler structures, resonant compensation networks, power converter architectures, and control strategies are systematically analyzed. The review further identifies that hybrid WPT architectures, adaptive compensation design and wide-coverage coupling mechanisms will be central to enabling high-power, long-distance, and misalignment-resilient wireless charging solutions for next-generation electric transportation systems. Full article

Buried, battery-free sensor nodes offer a promising solution for structural health monitoring, reducing maintenance and improving infrastructure sustainability by monitoring slow-varying parameters such as temperature and humidity, which do not require high sampling frequencies. This study shows the practical implementation of an autonomous LoRa node powered solely by RF energy harvested from a gateway using an 868 MHz rectenna and a custom energy management circuit charging a supercapacitor. Experimental characterization revealed that, with a single rectenna placed 40 cm from the gateway, communication intervals ranged from 58 min (+14 dBm) to 10 min (+20 dBm), clearly linking available RF power and energy management to achievable monitoring frequency. To further illustrate this, deploying a multi-element rectenna array enabled reliable node operation at distances greater than 10 m, demonstrating that the number of rectenna elements is the dominant factor governing harvested energy and the achievable operating range. Configuring the gateway as both a communication hub and an energy source further simplified deployment. These results highlight strategies for overcoming power delivery constraints in deeply embedded wireless sensing applications for civil structures. Full article

In this study, we investigate a shielded capacitive power transfer (S-CPT) system that employs cast iron road covers as transmission electrodes for both dynamic and static charging of electric vehicles. Coupling capacitance was evaluated from S-parameters using copper, aluminum, ductile cast iron, structural steel, and carbon steel electrodes, with additional comparisons of ductile iron surface conditions (casting, machining, electrocoating). In a four-plate S-CPT system operating at 13.56 MHz, capacitance decreased with electrode spacing, yet ductile cast iron reached ~70 pF at 2 mm, demonstrating a performance comparable to that of copper and aluminum despite having higher resistivity and permeability. Power transmission experiments using a Ø330 mm cast iron cover meeting road load standards achieved 58% efficiency at 100 W, maintained around 40% efficiency at power levels above 200 W, and retained 45% efficiency under 200 mm lateral displacement, confirming robust dynamic performance. Simulations showed that shield electrodes enhance grounding, stabilize potential, and reduce return-path impedance. Finite element analysis confirmed that the ductile cast iron electrodes can withstand a 25-ton design load. The proposed S-CPT concept integrates an existing cast iron infrastructure with thin aluminum receiving plates, enabling high efficiency, mechanical durability, EMI mitigation, and reduced installation costs, offering a cost-effective approach to urban wireless charging. Full article

This study presents a bibliometric review of global research trends on electric vehicles (EVs) and urban tourism within the context of smart cities, emphasizing the economic and policy dimensions of sustainable mobility and infrastructure investment. Drawing from 593 publications indexed in the Web of Science from 2005 to April 2025, the analysis explores document types, leading research areas, alignment with Sustainable Development Goals (SDGs), influential authors, and highly cited works. A keyword co-occurrence analysis reveals six major thematic clusters, highlighting key topics such as EV adoption behavior, renewable energy policy, wireless charging technology, and semiconductor innovation. Engineering and physics emerged as dominant research areas, with SDG 7 (Affordable and Clean Energy) and SDG 11 (Sustainable Cities and Communities) most frequently represented. The findings underline a growing interdisciplinary effort to integrate EV technologies with urban tourism through smart, carbon-neutral transport systems, supported by policy frameworks, green investment incentives, and digital infrastructure. This review identifies research gaps and opportunities to advance energy-efficient, economically viable, and tourism-oriented mobility solutions in smart cities by mapping the current knowledge landscape. Full article

The accelerated growth of the transport sector has increased oil consumption and greenhouse gas (GHG) emissions, intensifying global environmental challenges. The electrification of transportation has emerged as a key strategy to achieve sustainability targets, with electric vehicles (EVs) expected to account for 50% of global car sales by 2035. However, widespread adoption requires smart infrastructure capable of enabling dynamic in-motion charging. In this context, Electric Road Systems (ERSs), particularly those based on Wireless Power Transfer (WPT) technologies, offer a promising solution by transferring energy between road-embedded transmitters and vehicle-mounted receivers. This study assesses the structural response and service life of conventional and electrified asphalt pavement sections representative of the Spanish road network. Several standard pavement configurations were analyzed under heavy traffic (dual axles, 13 tons) using a hybrid approach combining mechanistic–empirical multilayer modeling and three-dimensional Finite Element Method (FEM) simulations. The electrified designs integrate prefabricated charging units (CUs) placed at a 9 cm depth, disrupting the structural continuity of the pavement. The results reveal stress concentrations at the CU–asphalt interface and service life reductions of up to 50% in semiflexible pavements. Semirigid sections performed better, with average reductions close to 40%. These findings are based on numerical simulations of standard Spanish sections and do not include experimental validation. Full article

This work analyzes the electric vehicle (EV) sales trends of plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs) and trends in the growth of Alternating Current (AC) and Direct Current (DC) charging infrastructure station scenarios in Europe and Italy. It offers a comprehensive view of market trends, technical developments, infrastructure development, and worldwide standardization initiatives for policymakers, researchers, and industry. A detailed classification of the charging technologies of EVs, i.e., conductive, wireless power transfer (WPT), battery swapping (BS), and different EV types, is presented. Finally, this work provides a comparative overview of charging standards and protocols, including the ones established by the Society of Automotive Engineers (SAE), International Electrotechnical Commission (IEC), and Standardization Administration of China (SAC), emphasizing interoperability and cross-border integration to accelerate the transition to clean transportation. Full article

Wireless power transfer (WPT) is recognized as a critical technology to advance carbon neutrality in transportation by alleviating charging challenges for electric vehicles and accelerating their adoption to replace fossil fuel. To ensure durability under traffic loads and harsh environments while avoiding vehicle obstructions, WPT primary circuits should be embedded within pavement structures rather than surface-mounted. This study systematically investigated the optimization of magnetite-modified asphalt material composition and thickness for enhancing electromagnetic coupling in WPT systems through integrated numerical and experimental approaches. A 3D finite element model (FEM) and a WPT platform with primary-side inductor–capacitor–capacitor (LCC) and secondary-side series (S) compensation were developed to assess the electromagnetic performance of magnetite content ranging from 0 to 25% and pavement thickness ranging from 30 to 70 mm. Results indicate that magnetite incorporation increased efficiency from 80.3 to 84.7% and coupling coefficients from 0.236 to 0.242, with power loss increasing by only 0.25 W. This enhancement is driven by improved equivalent permeability, which directly enhances magnetic coupling efficiency. A critical pavement thickness of 50 mm was identified, beyond which the reduction in transmission efficiency increased significantly due to magnetic flux dispersion. Additionally, the nonlinear increase in power loss is partially attributed to the significant rise in hysteresis and eddy current losses at elevated magnetite content levels. The proposed design framework, which focuses on 10% magnetite content and a total pavement thickness of 50 mm, achieves an optimal energy transfer efficiency. This approach contributes to sustainable infrastructure development for wireless charging applications. Full article

Electric vehicles (EVs) are becoming more widespread as we move toward a carbon-free society. However, challenges remain, such as the need for large batteries, the inconvenience of charging, and limited driving range. Dynamic optical wireless power transmission (D-OWPT) is considered a promising solution to these problems. This paper investigates the infrastructure configuration and feasibility of D-OWPT. To this end, a model of EV power consumption was created, and a simulator for D-OWPT was developed. Using this simulator, it was shown that placing light sources in low-speed sections is an effective method, and that continuous driving can be achieved by providing a light source with an output of about 20 kW, assuming a 50% of light irradiation section ratio. Since many of the conditions used in the analysis are achievable with existing technologies, these results demonstrate the high feasibility of D-OWPT. While the analysis presented in this study is based on simulation, the modeling parameters, including EV power consumption and OWPT system characteristics, are derived from actual vehicle specifications and experimental data reported in OWPT research. Although this study does not include physical implementation, the results present numerically validated conditions that are directly applicable to practical system design. This work is intended to serve as a theoretical foundation for the future development and prototyping of D-OWPT infrastructure. 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

Energy harvesting technology allows Internet of Things (IoT) devices to be powered continuously without needing battery charging or replacement. In addressing existing and emerging massive IoT energy supply challenges, this paper presents the design of multi-sourced multiple input and multiple output (MIMO) multiband hybrid wireless RF-perovskite photovoltaic energy harvesting subsystems for IoT application. The research findings evaluate the efficiency and power output of different RF configurations (1 to 16 antennas) within MIMO RF subsystems. A Delon quadruple rectifier in the RF energy harvesting system demonstrates a system-level power conversion efficiency of 51%. The research also explores the I-V and P-V characteristics of the adopted perovskite tandem cell. This results in an impressive array capable of producing 6.4 V and generating a maximum power of 650 mW. For the first time, the combined mathematical modelling of the system architecture is presented. The achieved efficiency of the combined system is 90% (for 8 MIMO) and 98% (for 16 MIMO) at 0 dBm input RF power. This novel study holds great promise for next-generation 5G/6G smart IoT passive electronics. Additionally, it establishes the hybrid RF-perovskite energy harvester as a promising, compact, and eco-friendly solution for efficiently powering IoT devices in smart cities. This work contributes to the development of sustainable, scalable, and smart energy solutions for IoT integration into smart city infrastructures. Full article

Vehicle-to-vehicle dynamic wireless charging (V2V-DWC) represents a modern advancement in electrified transportation, where a specialized charging vehicle delivers power to another vehicle on the move. The rising popularity of this technology can be attributed to the gradual advancements in energy storage technologies and the scarcity of plug-in charging infrastructure. V2V wireless power transfer provides a solution for electric vehicles (EVs) to recharge their batteries while in transit. The existing literature confirms the empirical validation of this concept through analytical and experimental studies, yet the challenge of misalignment remains insufficiently explored. Achieving optimal power transfer in V2V systems necessitates precise alignment of the inductive coils. Lateral misalignment (LTM) occurs due to the deviation of the coils from the proper alignment, leading to significant energy losses. Additionally, the development of effective controllers to address the V2V misalignment problem remains inadequate. This study proposes the development of a neural network-based adaptive fuzzy logic controller (ANFIS) to alleviate the misalignment issues in V2V-DWC systems. A comparative analysis is conducted between the proposed ANFIS controller and the conventional fuzzy logic controller (FLC) to evaluate their performance across various degrees of LTM. The performance of the proposed ANFIS controller is evaluated through simulations in MATLAB/Simulink, supplemented by experimental testing. The results indicate that the proposed ANFIS controller surpasses the FLC in both simulation and experimental contexts in addressing the V2V misalignment challenge. Full article

In today’s era of rapid technological advancement, unmanned aerial vehicles (UAVs) are transforming sectors such as remote delivery, surveillance, and disaster response. However, challenges related to energy consumption and operational efficiency continue to hinder their broader adoption. To address these issues, this study proposes an integrated system design combining dynamic wireless charging (DWC), intelligent trip planning, and intelligent edge computing (IEC). The proposed system leverages IEC for local data processing to reduce latency and optimize energy management, 6G networks for real-time vehicle-to-infrastructure (V2I) communication, and DWC to enable efficient, on-the-go energy replenishment. Additionally, a dynamic arrival management algorithm is introduced to minimize UAV wait times to enhance operational efficiency. Simulations of this system demonstrated significant improvements: larger UAVs achieved an average charging efficiency of 91.2%, while smaller UAVs achieved 92.75%, with dynamic arrival management reducing wait times by an average of 1.5 min for smaller UAVs and 5.0 min for larger UAVs. These findings underscore the system’s effectiveness in optimizing UAV operations and charging efficiency. This integrated approach offers a scalable framework to enhance UAV capabilities and sets a benchmark for future advancements in operational efficiency and charging technology for urban and environmental applications. Full article

Field implementations of fully underground sensor networks face many practical challenges that have limited their overall adoption. Power management is a commonly cited issue, as operators are required to either repeatedly excavate batteries for recharging or develop complex underground power infrastructures. Prior works have proposed wireless inductive power transfer (IPT) as a potential solution to these power management issues, but misalignment is a persistent issue in IPT systems, particularly in applications involving moving vehicles or obscured (e.g., underground) coils. This paper presents an automated methodology to sense misalignments and align IPT coils using robotic actuators and sequential Monte Carlo methods. The misalignment of a Class EF inverter-driven IPT system was modeled by tracking changes as its coils move apart laterally and distally. These models were integrated with particle filters to estimate the location of a hidden coil in 3D, given a sequence of sensor measurements. During laboratory tests on a Cartesian robot, these algorithms aligned the IPT system within 1 cm (0.025 coil diameters) of peak lateral alignment. On average, the alignment algorithms required less than four sensor measurements for localization. After laboratory testing, this approach was implemented with an agricultural sensor platform at the Utah Agricultural Experiment Station in Kaysville, Utah. In this implementation, a buried sensor platform was successfully charged using an aboveground, vehicle-mounted transmitter. Overall, this work contributes to the field of underground sensor networks by successfully integrating a self-aligning wireless power delivery system with existing agricultural infrastructure. Furthermore, the alignment strategy presented in this work accomplishes coil misalignment correction without the need for complex sensor or coil architectures. Full article