Analytical Approach to Estimate Temperature Variations in Passively Cooled Train Inverters

The advent of silicon carbide (SiC) semiconductors in electric traction enables several benefits, including the shift to passive cooling. However, it requires a conjugate heat transfer analysis to understand the temperature distribution and variation. While steady-state solutions exist, transient conditions in rail vehicles remain challenging. This paper develops two analytical models to predict temperature distribution and variation, validated against numerical simulations. An electric motor model estimates power losses in the converter, defining heat dissipation. The complete model is tested under realistic drive cycles, linking operational conditions to power losses and free flow speed. The results show the model effectively captures temperature variations, with higher losses during acceleration and larger temperature surges of around 70 K at lower speeds. Furthermore, the temperature at the junction was observed to be 20 K higher than at the base position and to exceed 420 K at a more downstream location. Thus, the proposed method captures the temperature variations considering different physical effects with reasonable accuracy and significantly faster computation times than transient numerical simulations.