This paper introduces a novel analytical model for the accurate inductance calculation of rounded rectangular coils in wireless power transfer systems (WPTSs). Comprehensive analysis is conducted for the rounded rectangular coil and a new parametric model is proposed to precisely define its structure. A new inductance calculation model is proposed for the rounded rectangular coils based on Neumann's formula and the obtained parametric structure model. The Geometric Mean Distance method is introduced to reduce the complexity and difficulty of self-inductance modeling. The image current method is adopted to achieve accurate inductance modeling for rounded rectangular coils with ferrite plates. Finally, the accuracy of the proposed analytical model is validated and compared with two other traditional methods. It turns out that the proposed models can achieve high calculation accuracy in self-inductance and mutual inductance calculation. The proposed model exhibits the merits of high accuracy and fast calculation speed which makes it promising for future coil designing and optimization.

The circular coil is extensively employed in different wireless power transfer (WPT) applications due to its simple structure and satisfactory magnetic coupling capabilities. Different analytical models have been proposed to calculate the inductance of circular coils and some of them have achieved relatively high accuracies for coreless circular coils. However, the influence of ferrite plates is not fully considered in these studies, thus limiting their application potential. Therefore, a new analytical model and practical calculation method of circular coil's inductance are proposed in this paper. First, the parametric structure model for circular coils is derived, and the analytical inductance model is proposed based on Neumann's Formula. Second, the image current method is adopted to calculate the inductances of circular coils when ferrite plates are added to WPT systems. Then, a new Feedforward Neural Netweork (FNN) model is designed and trained to improve the computation accuracy of the proposed analytical inductance model for different circular coils in WPT systems. The proposed model exhibits exceptional precision and stability, which makes it promising in coil designing and optimization for diverse applications.

Despite the widespread use of resonant converters in various applications, their analysis and design still necessitate a solid comprehension of the converter's operating principle and nonlinear behavior, which can be a significant manpower burden. To alleviate this issue and free us from repetitive work, this paper proposes a zero-knowledge artificial neural network (ZANN)-based waveform and critical parameter calculator for resonant converters. A normalized resonant network is employed to generate adequate data for training the ZANN. The ZANN can identify the essential characteristics of different resonant networks based on the configuration of hyperparameters. The accuracy of the calculator is verified using a 3-kW 480-V CLLC prototype. The results show that the accuracy of the root-mean-square (RMS) values is less than 5%, while the accuracy for the peak values is less than 20%.