Reduced-Order Thermal Behavioral Model Based on Diffusive Representation

The virtual prototyping of power electronic converters requires electrothermal models with various abstraction levels and easy identification. Numerous methods for the construction of compact thermal models have been presented in this paper. Few of them propose state-space models, where the model order can be controlled according to the necessity of the virtual prototyping analyses. Moreover, the model reduction methods require the experience of the engineer and previous calibration. Diffusive representation (DR) is proposed here as an original and efficient method to build compact thermal models as state-space models. The model reduction is obtained through the model parameter identification and/or the time horizon of the measurement data provided for the identification. Instead of eigenvalue elimination, the method enables to specify adequately inside the model the frequency domain wished for the virtual analysis at hand. The proposed method is particularly dedicated to the system optimization phases. Experimental and simulation results are in good agreement. The advantages and limitations of the DR are discussed in comparison to published methods.