X-Ray Computed Tomography Derived Turn Bundle Shapes and Transposition in Volume Manufactured Multistrand Random Windings

To accommodate the development of power-dense electrical machines that employ multistrand random windings, there has been sustained interest in the statistical simulation of the variable strand transpositions that occur in as-manufactured windings. However, the development and calibration of such methodologies is challenging due to the lack of data concerning realistic strand transpositions. This paper aims to overcome this lack of data through performing X-ray Computed Tomography (XCT) of a multistrand random winding coil extracted from an electric vehicle traction motor stator. By tracing each parallel strand in the winding through the XCT-derived data, turn bundle shapes and behaviours were identified that are not routinely accounted for in the statistical simulation of strand transpositions. Consequently, the data presented in this paper presents guidance to support the future development of strand transposition and AC loss variability simulation methods.

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Published
2025-04-09
DOI
https://doi.org/10.1109/wemdcd61816.2025.11014200
Primary Topic
Non-Destructive Testing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

X-Ray Computed Tomography Derived Turn Bundle Shapes and Transposition in Volume Manufactured Multistrand Random Windings

Nick Simpson, Phil Mellor, Joshua Hoole, Elizabeth Martin‐Silverstone
Non-Destructive Testing Techniques
article

X-Ray Computed Tomography Derived Turn Bundle Shapes and Transposition in Volume Manufactured Multistrand Random Windings

Nick Simpson, Phil Mellor, Joshua Hoole, Elizabeth Martin‐Silverstone
article en

Abstract

To accommodate the development of power-dense electrical machines that employ multistrand random windings, there has been sustained interest in the statistical simulation of the variable strand transpositions that occur in as-manufactured windings. However, the development and calibration of such methodologies is challenging due to the lack of data concerning realistic strand transpositions. This paper aims to overcome this lack of data through performing X-ray Computed Tomography (XCT) of a multistrand random winding coil extracted from an electric vehicle traction motor stator. By tracing each parallel strand in the winding through the XCT-derived data, turn bundle shapes and behaviours were identified that are not routinely accounted for in the statistical simulation of strand transpositions. Consequently, the data presented in this paper presents guidance to support the future development of strand transposition and AC loss variability simulation methods.

University of Bristol (GB)
University of Bristol
Affordable and clean energy
Openalex Percentile: Top 87%
Non-Destructive Testing Techniques
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