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A Novel Hybrid Technique for Thermal Analysis of Permanent Magnet Synchronous Motor Used in Electric Vehicle Application
Technical Paper
2020-01-0464
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Due to high torque and power density, permanent magnet synchronous motor (PMSM) has become the most viable candidate for electric vehicle (EV) traction application. However, to obtain such high torque and power density within a compact motor structure can cause a significant temperature rise within the motor while operating. As a result of high temperature rise, permanent magnet demagnetization may even occur within the motor. Thus, PMSM is susceptible to thermal instability. Therefore, to ensure thermal stability during varying operating conditions, thermal analysis is a mandatory procedure in addition to electromagnetic analysis during the design phase of the motor. In this paper, a computationally efficient numerical finite element analysis (FEA) process has been proposed for thermal analysis of PMSM. The proposed method is a hybrid technique in which analytical lumped parameter thermal network (LPTN) strategies are utilized to a certain extent to characterize the unaddressed heat flow from shaft to housing through bearing and endcap in 2D FEA. Further, a unique air gap creation strategy has been implemented to address the air gap convection heat transfer more accurately in FEA. The main goal of the proposed method is to make the thermal analysis process computationally more efficient for motor temperature prediction by keeping the proper balance between simplification and accuracy of the process. Later, the proposed method has been used to analyze the thermal performance of a newly designed interior PMSM prototype for EV application. Finally, the temperature results from the proposed method have been compared with conventional FEA, LPTN and CFD to demonstrate the improvements.
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Roy, P., Towhidi, M., Ahmed, F., Mukundan, S. et al., "A Novel Hybrid Technique for Thermal Analysis of Permanent Magnet Synchronous Motor Used in Electric Vehicle Application," SAE Technical Paper 2020-01-0464, 2020, https://doi.org/10.4271/2020-01-0464.Data Sets - Support Documents
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