A Self-Tuning Algorithm for Misalignment Detection and Efficiency Optimization in Double-Sided LCC-Based DWPT Systems

Achieving high efficiency in dynamic wireless power transfer (DWPT) systems has always been a critical challenge, particularly in applications such as electric vehicle (EV) charging. This challenge becomes even more profound under coil misalignment, which significantly impacts power transfer efficiency and system performance. Hence, this article presents a self-tuning, misalignment-tolerant algorithm to maximize the efficiency in DWPT systems utilizing double-sided LCC compensation networks. Unlike previous studies that primarily focus on resistive loads, this work addresses realistic scenarios involving battery loads with both resistive and reactive characteristics. In addition, it tackles misalignment during dynamic EV charging by integrating a novel misalignment detection technique and an innovative efficiency optimization algorithm. The proposed method utilizes real-time analysis of the harmonic spectrum of the primary-side current, specifically the ratio of the third harmonic to the fundamental harmonic ( ${I}_{p}^{\mathrm {\mathrm {3rd}}}/{I}_{p}^{\mathrm {\mathrm {1st}}}$ ), to detect misalignment and determine the coupling factor without the need for additional hardware and communication links. By employing the derived analytical equations, the algorithm dynamically adjusts the switching frequency and phase shift of the front-end inverter to achieve maximum efficiency. The proposed approach is validated through MATLAB simulations, and its practical feasibility is demonstrated using an experimental 1.8 kW DWPT setup, achieving significant efficiency improvements under varying load and alignment conditions.