Parameter Identification with Particle Filtering Algorithm for Deadbeat Control in DAB Converter

Deadbeat control has been applied in dual-active-bridge (DAB) converters for achieving effectively voltage regulation. However, conventional deadbeat control relies on the precise values of model parameters. To improve the robustness of conventional deadbeat control, a parameter identification method based on particle filtering (PF) algorithm is proposed in this article for DAB converters, where the series inductor and output capacitor will be identified in real time. From deadbeat control, the state equation and observation equation of PF algorithm are constructed to guide the particle swarm to iteration, thereby obtaining the identification of model parameters. Finally, the simulation also proves the PF algorithm’s recognition accuracy when the series inductor and output capacitor parameters mismatch.