Parasitic Parameter Extraction and Identification Method for HFT Based on DC-DC Converter in EV Application

Dual active bridge (DAB) resonant converter is one of the most commonly used soft switched converters of the new electric vehicle (EV) energy system. One of the most essential parts of the DAB resonant converter, the high-frequency transformer (HFT) includes certain parasitic parameters that caused voltage and current oscillation, or ring to the DAB converter. These precise parasitic parameters of the HFT provide accurate information and are useful to the DAB converter control system design. However, they are not provided by the manufacturer. This study focuses on this prospect of information, proposing a novel parasitic parameter identification method for the HFT based on DAB converter. Moreover, a 40 kHz full-bridge resonant DAB converter prototype based on SiC MOSFETs and HFPT laboratory prototype is constructed to verify the effectiveness and feasibility of the proposed method. Simulation and experimental results verify that the proposed method is more cost-effective than the conventional way to measure via impedance (IMDP) analyzer, requires shorter simulation time than the traditional finite element analysis (FEA) method, while it is also more accurate has fast convergence than the traditional forgetting factor recursive least square (FFRLS) identification algorithm.