*WINNER* Novel Ferrite-core Metamaterial and AI-based Coil Parameter Optimization for Efficient Wireless Power Transfer

Abstract

The adoption of wireless power transfer (WPT) is affected by limitation in power transfer distance, low transfer power (TP) and power transfer efficiency (PTE). However, the discovery of metamaterials (MTM), has proven a viable solution. The inherent magneto-inductive wave and negative refractive index of MTM engender evanescent wave amplification within its vicinity, creating a high-density magnetic field, high mutual inductance and a convergence of the flux lines at the receiver. To this end, we present a novel WPT model based on a working combination of layered DD coil (LDD) and Ferrite-core based metamaterial (FC). The Ferrite-core comprises an inner and outer radius r_i and R_o respectively. It is situated at the center of the LDD and in between its individual layers. A low frequency simulation of the proposed WPT model based on finite element analysis is carried out in ANSYS Maxwell. Simulation results show the proposed FC generates higher mutual inductance and power received than a conventional WPT design. By increasing the start radius of the LDD coil and maintaining a constant inter-layer distance, an improved performance of the proposed WPT system is achieved. Further, it is observed that the proposed WPT system realizes higher mutual inductance and TP with a small core radius than large core radii, thus presenting cost saving benefits in material fabrication. Optimization of coil parameters was performed in MATLAB to improve the amount of power received and enhance the PTE. The MATLAB results were cross verified with Lt-spice result, and both show close agreement.