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Multi-Objective Optimization of Yokeless and Segmented Armature Machine for In-Wheel Traction Applications Based on the Taguchi Method

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posted on 2024-06-10, 10:46 authored by Liang Su, Guangchen Wang, Yuan Gao, Pericle Zanchetta, Hengliang Zhang
For electrical machines with complex structures, the design space of parameters can be large with high dimensions during optimization. Considering the calculation cost and time consumption, it is hard to optimize all the design parameters at the same time. Therefore, in that situation, sensitivity analysis of these design parameters is usually used to sort out crucial parameters. In this paper, the sensitivity analysis-based Taguchi method is applied to optimize the axial-flux permanent magnet (AFPM) machine with yokeless and segmented armature (YASA) topology for an in-wheel traction system. According to the key parameters and their sensitivity analysis, the optimal machine scheme to meet the performance requirements can be formed. In this case study, the machine performance is improved significantly after optimization. Lastly, the experimental results verify the accuracy of the model used in this study.

History

Author affiliation

College of Science & Engineering Engineering

Version

  • VoR (Version of Record)

Published in

Machines

Volume

12

Issue

4

Pagination

221

Publisher

MDPI AG

eissn

2075-1702

Copyright date

2024

Available date

2024-06-10

Language

en

Deposited by

Dr Yuan Gao

Deposit date

2024-06-07

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