This paper proposes a machine learning (ML)–based design for a load-independent (LI) wireless power transfer (WPT) system. The fundamental concept of the proposed design strategy is to solve an optimization problem for achieving high-frequency LI operation by full numerical computations. An evaluation function for optimization is formulated, taking into account output voltage regulation against load variations and high power-delivery efficiency. The developed optimization software provides the best parameter set of coupling coil parameters and circuit-component values. In addition, the ML-based optimization finds the optimal parameter set from parameters outside the range that it had considered to be common sense, which is an unexpected but valuable result. The WPT system, designed through the proposed method, achieved ideal LI operation in the experiments. The quantitative agreements between experimental and numerical waveforms substantiate the validity of the proposed design.

In this paper, a WPT system that can switch between constant current (CC) and constant voltage (CV) in a single circuit is proposed. In the proposed WPT system, the CC and CV modes are achieved by varying the on-duty ratio of the buck converter. In addition, the proposed system also keeps the zero-voltage switching against coil misalignment and load variations without any information feedback from the rectifier to the inverter. This is because the load-independent behavior is built into the proposed system. The experimental results are consistent with the analytical predictions, which show the validity of the proposed circuit design strategy and the derived analytical expressions. Under rated conditions, the output power was 36.9 W and the power conversion efficiency was 86 % at the operating frequency of 6.78 MHz.

In this research, we propose a variable-gain load-independent class-E rectifier with fixed input reactance for wireless power transfer (WPT) system. Featuring an adjusting network, the proposed rectifier can adjust its voltage gain to maintain a constant output voltage against load variations and coil misalignment, eliminating the need for additional regulators. Based on equations derived from circuit analysis, we present a design method to achieve the zero-voltage switching (ZVS) condition, ensuring high efficiency even at multi-MHz frequencies. Additionally, the input reactance of the proposed rectifier remains fixed, which is beneficial for maintaining ZVS of the inverter. To validate the design method, a WPT system at 6.78 MHz was built. The experimental results confirmed the successful voltage-gain adjustment to compensate for coil misalignment. Furthermore, load-independent ZVS and fixed input reactance were achieved, demonstrating the effectiveness of the proposed rectifier.

This paper proposes a machine learning (ML)-based design for a load-independent (LI) wireless power transfer (WPT) system. The proposed design strategy formulates the WPT design as an optimization problem and solves it by fully-numerical computation to achieve high-frequency LI operation. A multi-objective evaluation function is given to achieve the LI operation, which evaluates output voltage, power-delivery efficiency, and total harmonic distortion. The class-EF WPT system designed using the proposed method achieved narrower output voltage variations and higher power-delivery efficiency than the analysis-based design system. Additionally, the proposed design algorithm identifies parameter sets that were never found through the analysis-based design. Namely, only a small amount of current flows through the previous harmonic resonant filter of the class-EF inverter. These results demonstrate the potential of ML-based design in the field of power electronics.

This paper proposes the load-independent (LI) class-E frequency multiplier along with a unified circuit analysis method with the LI class-E amplifier. A circuit-parameter determination strategy is presented to achieve LI operation and maximum power output capability at the rated condition. We designed the class-E amplifier and frequency doubler using the unified analytical expressions. Both the implemented circuits achieved the LI operation, namely constant output voltage amplitude and zero-voltage switching against load variations without any control. The experimental results showed quantitative agreements with the analysis results, namely waveforms and power conversion efficiency, which indicates the validity of the derived analytical expressions and design procedure.

This paper presents a simulator-based design-optimization software for high-frequency power-electronics circuits, which consists of the heuristic algorithm, magnetic-component design tool, and commercial simulator, SPICE. Because we can use the SPICE component library, the software suggests high-accurate design results, and the experimental adjustments can be reduced. Besides, by using the heuristic algorithm, the optimization algorithm converges stably. The magnetic-component design tool provides a precise estimation of the power losses, which is important for high-frequency power-electronics circuit designs. As an example, we design the class-DE inverter by applying the developed software, which shows the usefulness of the software.

This study proposes a self-tuned series resonant power oscillator capable of load-independent operation. The proposed power oscillator has a self-tuning feedback loop that provides a gate-driving voltage with a constant phase shift and amplitude. Therefore, it is robust against component tolerances in a series resonant filter. It is also robust against load variations owing to its load-independent design. Consequently, it maintains a high-efficiency and constant AC output against load variations and component tolerances. Experimental results demonstrated the effectiveness of the proposed power oscillator.