A C-HIL based data-driven DC-DC power electronics converter model for system-level studies.

We propose to exploit a Controller Hardware-In-the-Loop (C-HIL) digital twin of power electronics converters to acquire data for deriving a model that is usable in system-level studies. An enhanced neural network-based polytopic model (a black-box model) is used for this purpose. The choice of this model is motivated by its simplicity and the ability to conceal the converter’s topology and control algorithm within its structure, thus ensuring the data privacy of power electronics converter manufacturers. The capability of the proposed approach to capture the primary dynamics of converters is demonstrated, and the approach is validated on an industrial DC-DC power electronics converter.