Browse Publications Technical Papers 2023-01-1612
2023-10-31

Evaluating Thermal Performance of Electric Motor with Hybrid Approach of 1D LPTN Model and 3D CHT Analysis 2023-01-1612

Electric Vehicles is the new trend in automotive industry and differentiator is electric motors which are taking over a conventional internal combustion engine. One of the major challenges with electric vehicles is the efficiency of E-drives, which is mainly affected by motor operating temperatures. Temperature affects the motor characteristics (torque vs speed), which could result in motor underperform or even fail to perform. Hence, it is critical to develop and design a methodology which can accurately predict the electric motor thermal behaviour in advance or try different iterations before getting in to a detailed and extensive analysis. The correct identification of temperatures inside the motor at different drive cycles, has always been a challenge. Experimental validation of motors gives accurate temperature measurements, but it has dependencies on prototypes which costs heavily, and feedback is not available at design stage. Another way is to have detailed 3D Simulations at early stage of design, but it is time consuming for model building and solving which delays the design phase. To solve this, a combined hybrid method of 1D Lumped Parameter Thermal Network (LPTN) approach and 3D Conjugate heat transfer (CHT) approach is proposed. In the proposed approach, detailed multidisciplinary discretized 1D LPTN model method is developed to predict temperature distribution for input drive cycles. 1D LPTN model has fidelity to analyse any drive cycle and incorporate electromagnetic, mechanical and friction generated heat losses which gives reasonably accurate temperature identification at faster solving rates. After identifying the worst cases based on 1D analysis, detailed 3D CHT finite element analysis is used to understand the temperature sweeps, rises and hot spots on the motor components at shortlisted drive cycle cases. This hybrid (1D LPTN and 3D CHT) approach, will help in early design stage by predicting motor temperatures quickly and efficiently, which saves product development time. In this Hybrid approach, the 1D and 3D thermal models are optimised and then validated with test data to establish the method.

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