In wireless power transfer (WPT) systems, inverters are used to achieve high‐frequency conversion of DC/AC, and their conversion efficiency and working frequency are key factors affecting the system’s power transfer efficiency. In practical applications, many hardware issues, such as power transistor shutdown and loss, are the main reasons that affect the inverter conversion efficiency. On the other hand, the working frequency of WPT systems ranges from hundreds of kHz to a few MHz, and traditional voltage and current phasor estimation requires a very high sampling rate which is difficult to achieve. To overcome these limitations, this paper introduces a phase‐shifting full bridge inverter using a zero‐voltage switching (ZVS) soft switching technology to optimize the conversion efficiency of the inverter. Meanwhile, apparent power is introduced to detect the operating frequency and phase angle. Combined with an FPGA soft switching control strategy, this approach allows for the quick adjustment of the driving pulse of MOS transistors, as well as the voltage and current at the transmitting end, to a completely symmetrical state in real‐time, effectively suppressing frequency offset and achieving efficient frequency tracking control and maximum efficiency tracking (MET) control of the WPT system. Through simulation and experiments, the ZVS soft switching technology has been achieved with the inverter control strategy, leading to improved conversion efficiency. The frequency offset that can be corrected can reach 0.1 Hz using the apparent power detection method, and the maximum transfer efficiency of the WPT system can reach 91%.

With the application of electrical equipment, magnetically coupled resonant (MCR) wireless power transfer (WPT) technology has become an effective means to improve equipment intelligence. The MCR-WPT system is a loosely coupled system, and the resonant frequency may be split or detuned due to the changes of load or transferring distance, resulting in the system transfer efficiency (TE) greatly reduced. To solve the problems of limited speed and accuracy in the existing frequency tracking methods, this paper analyzes the relation between the detuning rate and the system TE, proposing an adaptive frequency tracking control method based on fuzzy radial basis function neural network control. The neural network outputs proportion–integration–differentiation parameters to adjust the inverter drive circuit, and the frequency of inverter drive circuit is adjusted nonlinearly in real time to ensure the accurate frequency tracking of the MCR-WPT system. The simulation and experimental results show that the proposed method can enhance the tracking ability of the resonant frequency, and effectively improve the system TE.