Geometry modeling method of a stator forming coil for permanent magnet traction motors in rail transit for manufacturing

Facing the comprehensive promotion of CR450, permanent magnet traction motors need to be applied in batches. In response to the swift trial production requirements of various stator forming coil models in manufacturing and considering the correlation between design and manufacturing parameters, we research the geometric model of stator forming coils for manufacturing. In this study, the geometry modeling technique of the stator forming coil is elucidated. The essential structures are precisely modeled via the analytical geometry method. A correlation model illustrating the relationship between the design parameters and the manufacturing parameters of these structures is established to consider the calculation error. We propose a 3D scanning structural feature modeling approach that extracts coil features and employs fitting methods to invert key structural model elements on point cloud datasets for experimental validation. Leveraging the point cloud model, the critical structural size computation method is deployed to calculate structural parameters. The results demonstrate that the comparative errors in the span width and height of the nose end between forward and reverse modeling are 0.45% and 2.6%, respectively. This addresses the issue of design parameters being challenging to accurately guide manufacturing and can offer effective support for the design and manufacturing assembly of stator forming coils with various model specifications.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Published
2024-10-05
DOI
https://doi.org/10.1177/09544062241285187
Citations
4
Primary Topic
Electric Power Systems and Control
Type
article
Field-Weighted Citation Impact
0.83
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article

Geometry modeling method of a stator forming coil for permanent magnet traction motors in rail transit for manufacturing

Jie Qin, Ao Hu, Weiye Li, Yuhe Wu et al.
4 citations
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Electric Power Systems and Control
0.83
article

Geometry modeling method of a stator forming coil for permanent magnet traction motors in rail transit for manufacturing

Jie Qin, Ao Hu, Weiye Li, Yuhe Wu, Jian Hu, Jun Xu
article en
4 citations

Abstract

Facing the comprehensive promotion of CR450, permanent magnet traction motors need to be applied in batches. In response to the swift trial production requirements of various stator forming coil models in manufacturing and considering the correlation between design and manufacturing parameters, we research the geometric model of stator forming coils for manufacturing. In this study, the geometry modeling technique of the stator forming coil is elucidated. The essential structures are precisely modeled via the analytical geometry method. A correlation model illustrating the relationship between the design parameters and the manufacturing parameters of these structures is established to consider the calculation error. We propose a 3D scanning structural feature modeling approach that extracts coil features and employs fitting methods to invert key structural model elements on point cloud datasets for experimental validation. Leveraging the point cloud model, the critical structural size computation method is deployed to calculate structural parameters. The results demonstrate that the comparative errors in the span width and height of the nose end between forward and reverse modeling are 0.45% and 2.6%, respectively. This addresses the issue of design parameters being challenging to accurately guide manufacturing and can offer effective support for the design and manufacturing assembly of stator forming coils with various model specifications.

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering ScienceVol. 239(2)
Wuhan University of Technology (CN)
Openalex Percentile: Top 26%
Electric Power Systems and Control
0.83
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