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New Insights into Wireless Power Transmission Systems
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New Insights into Wireless Power Transmission Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (20 April 2025) | Viewed by 1256

Special Issue Editors

Dr. Michele Quercio

E-Mail Website
Guest Editor
Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, 00146 Rome, Italy
Interests: artificial intelligence; wireless power transfer; electromagnetic shielding
Special Issues, Collections and Topics in MDPI journals
Dr. Antonino Laudani

E-Mail Website
Guest Editor
Department of Electrical, Electronic, and Computer Engineering (DIEEI), University of Catania, Catania, Italy
Interests: solar energy and photovoltaic systems; electrical power and energy system; artificial intelligence; renewable energy; smart grids and microgrids
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the latest advancements and research breakthroughs in Wireless Power Transmission (WPT) systems. As WPT technology continues to evolve, it holds significant potential for transforming various industries, enabling the efficient and contactless transfer of energy over distances. This Special Issue explores key innovations, including enhanced power transfer efficiency, novel materials, system integration, and emerging applications, such as electric vehicles, biomedical devices, and consumer electronics.

Key topics covered include, but are not limited to:

  • Innovative WPT techniques: New methodologies to improve efficiency and range, such as resonant inductive coupling, microwave transmission, and laser-based systems.
  • Power management and safety: Advances in optimizing power flow and ensuring the safety of users and devices.
  • Energy harvesting: Integration of WPT systems with energy harvesting technologies for sustainable and autonomous power solutions.
  • System integration and miniaturization: Improvements in compact and scalable designs for consumer and industrial use.
  • Applications and future trends: Emerging uses in transportation, robotics, healthcare, IoT, and smart cities, along with future directions for WPT research.
  • Electromagnetic Environment Analysis: Focusing on optimizing the compatibility of WPT systems within various electromagnetic environments to ensure efficient operation.

Dr. Michele Quercio
Dr. Antonino Laudani
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wireless power transmission (WPT)
  • energy harvesting
  • resonant inductive coupling
  • power transfer efficiency
  • system integration
  • electromagnetic compatibility

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Published Papers (4 papers)

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Research

19 pages, 998 KiB  
Article
Neural Network Method for Distance Prediction and Impedance Matching of a Wireless Power Transfer System
by Lorenzo Sabino, Davide Milillo, Fabio Crescimbini and Francesco Riganti Fulginei
Appl. Sci. 2025, 15(11), 6351; https://doi.org/10.3390/app15116351 - 5 Jun 2025
Viewed by 158
Abstract
This study introduces a novel and versatile application of neural networks (NNs) to enhance two distinct aspects of Wireless Power Transfer (WPT) systems. First, a compact NN architecture is presented for accurate distance estimation and automated impedance matching in a WPT system. Trained [...] Read more.
This study introduces a novel and versatile application of neural networks (NNs) to enhance two distinct aspects of Wireless Power Transfer (WPT) systems. First, a compact NN architecture is presented for accurate distance estimation and automated impedance matching in a WPT system. Trained on either impedance measurements or scattering parameters acquired from the transmitter side, this NN effectively predicts the inter-coil distance and identifies optimal capacitance values for maximizing power transfer. Validation using both simulated and experimental data demonstrates consistently low prediction error rates. Second, a separate NN is employed to predict the optimal transmission frequency for minimizing the phase angle between voltage and current, thereby maximizing the power factor. This NN, validated on experimental data spanning various load conditions and inter-coil distances, achieves performance comparable to traditional PI control, but with significantly faster prediction speeds. This speed advantage is crucial for real-time applications and directly contributes to improved power efficiency. The results presented in this study, including the high accuracy of distance and capacitance prediction and the rapid determination of optimal frequencies for power factor maximization, showcase the significant potential of NNs for optimizing WPT systems. These findings open the way for more efficient, adaptable, and intelligent wireless energy transfer solutions, with potential applications ranging from dynamic charging of electric vehicles to real-time optimization of implantable medical devices. Full article
(This article belongs to the Special Issue New Insights into Wireless Power Transmission Systems)
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18 pages, 2565 KiB  
Article
Frequency Domain Model of a Resonant LCC-S Converter for High-Frequency Wireless Power Transfer Applications Considering Switching Losses in MOSFETs Bridge
by Vittorio Bertolini, Antonio Faba, Marco Dionigi and Ermanno Cardelli
Appl. Sci. 2025, 15(11), 5878; https://doi.org/10.3390/app15115878 - 23 May 2025
Viewed by 173
Abstract
A model for a fast and reliable evaluation of the impact of MOSFETs’ switching losses in the global performances of a high-frequency wireless power converter is proposed. The frequency domain model for an LCC-S wireless resonant converter is presented. The contribution of MOSFET [...] Read more.
A model for a fast and reliable evaluation of the impact of MOSFETs’ switching losses in the global performances of a high-frequency wireless power converter is proposed. The frequency domain model for an LCC-S wireless resonant converter is presented. The contribution of MOSFET behavior is counted considering a trapezoidal input voltage in the converter instead of the classic square wave or Pulse Width Modulation wave to take into account MOSFETs’ rise and fall times. These times are evaluated with a simplified first-order circuit able to model the MOSFET behavior during commutations. Two commercial MOSFETs have been integrated in the converter model. The predictions of the proposed approach are compared (for validation) with results coming from Simulink environment, where the converter behavior can be reproduced in a very realistic way. An evaluation of switching losses is presented, and the consequent impact on converter performances is evaluated by comparing the converter output voltage (and output power) predicted with the proposed model and that one is achievable by the converter considering ideal switches. The analysis has been performed considering different values of input voltage and load resistance. This approach can be easily generalized to every resonant converter topology. Full article
(This article belongs to the Special Issue New Insights into Wireless Power Transmission Systems)
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22 pages, 5534 KiB  
Article
Reduced-Order Nonlinear Envelope Modeling and Simulation of Resonant Inverter Driving Series Resistor–Inductor–Capacitor Load with Time-Varying Component Values
by Ohad Akler and Alon Kuperman
Appl. Sci. 2025, 15(8), 4502; https://doi.org/10.3390/app15084502 - 18 Apr 2025
Viewed by 284
Abstract
Envelope modeling is an efficient way to obtain the large-signal amplitude and phase dynamics of fast-varying sinusoidal signals required for, e.g., resonant frequency tracking or energy transfer rate regulation in power converters. In addition, the method eliminates fast-varying parameters from the model so [...] Read more.
Envelope modeling is an efficient way to obtain the large-signal amplitude and phase dynamics of fast-varying sinusoidal signals required for, e.g., resonant frequency tracking or energy transfer rate regulation in power converters. In addition, the method eliminates fast-varying parameters from the model so that the simulation time and memory requirements are reduced. This paper reveals the envelope-modeling process of a capacitor-powered resonant inverter feeding a time-varying series RLC load, often employed in pulsed-power applications. Such an arrangement is nontrivial since the system does not reach a steady state within a single pulse duration. Furthermore, model order reduction is carried out without performing linearization due to large variations in the expected operation point. As a result, a reduced-order nonlinear envelope model is derived and validated by simulations. Both the proposed modeling method and the derived model aim to simplify the challenging task of feedback controller design. Full article
(This article belongs to the Special Issue New Insights into Wireless Power Transmission Systems)
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18 pages, 889 KiB  
Article
Symbolic Regression Method for Estimating Distance Between Two Coils of an Inductive Wireless Power Transfer System
by Davide Milillo, Lorenzo Sabino, Rafiq Asghar and Francesco Riganti Fulginei
Appl. Sci. 2025, 15(7), 3668; https://doi.org/10.3390/app15073668 - 27 Mar 2025
Viewed by 302
Abstract
Symbolic regression (SR) has emerged as a powerful tool for the characterization of Wireless Power Transfer (WPT) systems, estimating the distance between coils and finding the relationship between frequency and phase so as to find the best frequency to increase the power factor. [...] Read more.
Symbolic regression (SR) has emerged as a powerful tool for the characterization of Wireless Power Transfer (WPT) systems, estimating the distance between coils and finding the relationship between frequency and phase so as to find the best frequency to increase the power factor. This study explores the application of SR on both simulated and experimental data, demonstrating its effectiveness with low prediction errors. SR employs a genetic algorithm to identify the analytical formula that best represents the input–output relationship, combining the strengths of traditional machine learning and analytical modeling. The results, with prediction errors of less than 1%, indicate that SR not only enhances predictive accuracy but also provides insights into the underlying physical principles governing WPT systems. This dual advantage positions SR as a valuable method for optimizing WPT applications, paving the way for further research and development in this field. Full article
(This article belongs to the Special Issue New Insights into Wireless Power Transmission Systems)
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