Study on the relationship between assembly interference and deformation influence of axle hole assembly of electric vehicles motor core die based on BNPP

Jiahui Qian; Taotao Yang; Yigang Wang; Jianhong Wang

doi:10.1117/12.3054931

4 November 2024 Study on the relationship between assembly interference and deformation influence of axle hole assembly of electric vehicles motor core die based on BNPP

Jiahui Qian, Taotao Yang, Yigang Wang, Jianhong Wang

Author Affiliations +

Proceedings Volume 13420, Third International Conference on New Materials, Machinery, and Vehicle Engineering (NMMVE 2024); 1342015 (2024) https://doi.org/10.1117/12.3054931
Event: International Conference on New Materials, Machinery, and Vehicle Engineering 2024, 2024, Dalian, China

Abstract

This study investigates the position deviation in the assembly of iron core dies for new energy electric motors due to interference fit. A mapping model is established using a back propagation neural network (BPNN) to correlate the ideal die axial hole interference fit clearance with position deviation. Utilizing the joint simulation of Abaqus and Isight, a comprehensive set of geometric models with varying interference clearances is developed, generating data on center deviations for different sizes and clearances. A BPNN is trained with the template hole diameter and insert outer diameter as inputs, and the x-direction and y-direction center deviations of the insert cylindrical axis as outputs. This model is then applied to predict the deformation effects of the interference fit on assembly. The results show that this method can accurately and efficiently predict the deformation in ideal axial hole interference fit assemblies.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiahui Qian, Taotao Yang, Yigang Wang, and Jianhong Wang "Study on the relationship between assembly interference and deformation influence of axle hole assembly of electric vehicles motor core die based on BNPP", Proc. SPIE 13420, Third International Conference on New Materials, Machinery, and Vehicle Engineering (NMMVE 2024), 1342015 (4 November 2024); https://doi.org/10.1117/12.3054931

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