Data-Driven Modeling of Zero Voltage Switching of Non-Resonant DAB Converters under TPS Modulation

DAB converters under triple phase shift (TPS) modulation can broaden the zero voltage switching (ZVS) range to improve efficiency and noise robustness. Conventionally, the piecewise approach and harmonic approach are two commonly used approaches to build analytical models for ZVS conditions under this modulation strategy. However, both two approaches fail to achieve good modeling accuracy as well as low computational cost simultaneously due to heavy human dependence. To solve this problem, this digest proposes a data-driven modeling approach for ZVS analysis (DM-ZVS) for non-resonant DAB converters under the TPS modulation strategy. The data-driven modeling process is conducted with the random forest algorithm automatically using ZVS performance data from simulation tools, greatly mitigating human dependence to improve accuracy and computational efficiency. With the trained data-driven classification model of ZVS, the optimal TPS modulation parameters can be found to ensure the full ZVS range. A design case is given, and 1 kW hardware experiments comprehensively validate the feasibility of the proposed DM-ZVS.