Real-Time Coupling Coefficient Estimation for Inductive Power Transfer Systems

Loosely coupled transformers are commonly used in inductive power transfer (IPT) systems which are inevitable part of electrified transportation. Since efficiency of these systems is mainly dependent on alignment of primary (ground side) and secondary (vehicle side) coils, estimation of coupling coefficient has a significant impact on the performance of IPT chargers. However, despite the requisite need for a plausible estimation algorithm, the lack of a simple, optimal and unsusceptible to noise algorithm is noticeable. In this paper, we introduce a new online optimal prediction method for IPT systems allowing a precise real time estimation of the coupling coefficient in the presence of measurement noises and system uncertainties. Using IPT system dynamics, the estimation scheme is proposed based on Kalman filter algorithm. This algorithm is optimal, tractable and robust and its estimation are promising as simulation results reveal.