Mathematical Model of Dual-Active-Bridge Converters for Control and Hardware-in-the-Loop Applications

This work presents an integrated methodology for modeling, parameter tuning, and experimental emulation of Dual Active Bridge (DAB) converters aimed at detailed simulation, control design, and real-time emulation. This is needed to bridge the gap between theoretical modeling and practical implementation, enabling accurate prediction of converter behavior under realistic operating conditions and facilitating the development of control strategies. The study begins with the derivation of a nonlinear model including parasitic elements and transformer characteristics, enabling accurate representation of the converter’s dynamics across operating conditions. To address deviations caused by component tolerances, the model parameters are calibrated using a multi-algorithm optimization framework based on Particle Swarm Optimization, Grey Wolf Optimizer, Secretary Bird Optimization, and Whale Optimization, where the error between predicted and experimental waveforms is minimized. The comparative analysis allows selecting the most suitable optimization strategy based on statistical analyses. The model is also discretized and implemented on a Hardware-in-the-Loop (HIL) platform based on a high-performance microcontroller, enabling real-time emulation of the converter as a digital twin. Moreover, a control-oriented version of the model is presented and used to design a voltage controller, which is subsequently tested in both the HIL environment and on a real DAB converter prototype. Experimental results report differences between HIL and real prototype below 3.9% for currents and 4.45% for voltages in multiple operation conditions, demonstrating an accurate representation of the real power system. This methodology ensures low errors between theoretical, simulated, and experimental behavior, providing a framework for accurate modeling and controller design of DAB converters.