Numerically-based Reduced-order Thermal Modeling of Traction Motors
Artikel i vetenskaplig tidskrift, 2021
This paper presents an approach based on numerical reduced-order modeling to analyze the thermal behavior of electric traction motors. In this study, a single conjugate heat transfer analysis provides the possibility to accurately predict thermal performances by incorporating both computational fluid dynamic and heat transfer modules. Then, the developed model is used as the basis for deriving a fast reduced-order model of the traction motor enabling prediction of motor thermal behaviour in duty cycles with a high number of operating points. All the results achieved are verified using flow and temperature measurements carried out on a traction motor designed and built for a traction application. A good agreement between the measured and estimated values of flows and temperatures is achieved while keeping the computation time within a reasonable range for both the full-order and reduced-order conjugate heat transfer models. The optimized full-order model can be run in minutes and the reduced-order model computation time is less than one second per operating point. The transient simulation based on reduced-order model is conducted and both the learning phase and validation results are well illustrated. It is shown than the deviation of the reduced-order model in estimating the motor thermal performance is less than one Celsius degree from the full-order model.