Self- and Mutual-Inductance Cross-Validation of Multi-Turn, Multi-Layer Square Coils for Dynamic Wireless Charging of Electric Vehicles

Abstract

Dynamic Wireless Power Transfer (DWPT) has high potential to overcome electric vehicles’ battery issues of size and range and to achieve fully autonomous driving. Accurately extracting the self- and mutual-inductance of the coils is essential for controlling and optimizing the overall performance of the DWPT system under real driving conditions. Due to the limited space for coil installation at the bottom of the vehicles, multi-turn, multi-layer square coils are proposed to maximize the space utilization of the DWPT system. For the first time, this paper presents a theoretical model for calculating the self- and mutual-inductance and the coupling coefficients of multi-turn, multi-layer square coils. Taking a four-turn, four-layer square coil as an example, the model is cross-validated by 3D coil modelling and simulation, as well as practical measurements. A theoretical–experimental verification is further conducted to indirectly corroborate the cross-validated coupling coefficients of the two coils. On average, the normalized root mean square errors of the resultant self-inductance and coupling coefficients of two identical coils are 1.04% and 4.29%, respectively. Specifically, for the selected case, normalized root mean square errors of the zero-phase angle frequencies of the system under different misalignment situations average out at 1.32%.