Accurate Time-Efficient Thermal Modeling and Discretization Methodology Applied to Electric Machines

Abstract

The increasing power density of electric machines for electric vehicles necessitates accurate thermal analysis in design and real-time condition monitoring through simulations with computation times not exceeding one minute. Existing thermal models are either accurate and complex while requiring large computation times or they are fast but lack accuracy. To address these challenges, a novel hybrid modeling methodology is proposed, combining 3D lumped parameter thermal networks with thermal resistances extracted from 2D finite element models (FEM) to reduce computation demands while preserving accuracy. Further, a methodology is introduced to define the thermal network discretization for a desired threshold accuracy while minimizing computation time. Analysis of this discretization methodology demonstrates that the desired accuracy can be reliably achieved with limited computational effort. Verification of the modeling methodology against 3D FEM in OpenFOAM shows key component temperature deviations of less than 0.67 °C in steady-state simulations and 0.75 °C in transient simulations, comparable to the 3D FEM uncertainty of 0.39 °C. The computation times for steady-state and transient simulations are 18.3 s and 43.5 s respectively compared to 44 h and 175 h for 3D FEM. This highlights the time efficiency of the proposed methodology while maintaining accuracy for key component temperatures.