A Novel DC-bias Current Suppression Strategy for DAB Converter under TPS Modulation

The presence of DC bias in the inductor current poses significant risks, such as overcurrent, increased power loss, and potential saturation of the transformer in dual active bridge (DAB) converters, which are operating under triple-phase-shift (TPS) modulation. Traditional modeling methods typically necessitate conducting both steady-state and transient analyses of converters to derive the transient variables. However, it is challenging to derive analytical solutions using traditional modeling approaches. In this context, this article presents an Artificial Neural Network (ANN) aided method to address the DC-bias eliminating method of the inductor current for DAB converter. Moreover, the transient state between two steady state is adopted and the transient variables, including duty cycle and phase shift, are generated by two ANNs, which would be trained separately according to the superposition theorem. Finally, experimental results are presented to verify the effectiveness of the proposed method.