Dynamic Improvement of Direct Inductive Power Transfer Systems Using Adaptive Model Predictive-Based Phase Shift Control

Abstract

In this paper, an adaptive model predictive (AMP)-based phase shift control is proposed to improve the dynamic performance of inductive power transfer (IPT) systems. The proposed control is inherited from the conventional model predictive control (MPC) with the prominent characteristics of time-domain design and easy implementation, while incorporating an adaptive mechanism for the step change of the control input (phase shift angle) to ensure both accuracy and fast transient performance. The step change of the phase shift angle is automatically magnified for fast dynamic tracking and dwindled for tracking accuracy at steady states. The settling time of the dynamics can be precisely designed based on the equations of the proposed control. Both simulation and experiments validate the dynamic improvement of the proposed AMP-based phase shift control over the conventional proportional-integral (PI)-based phase shift control. The advantages of adopting adaptive step change over fixed step change for the phase shift angle are also revealed by empirical verifications.