Order-Reduced Nonlinear Semi-Analytical Multiphysics Model for Axial-Flux Motors

Electromagnetic-thermal analysis is crucial to guarantee the axial flux motors’ (AFMs) reliable operation as their compact size and poor heat dissipation conditions can lead to thermal limits. However, the conventional coupled analysis is extremely time-consuming, especially in 3-D analysis. To this end, a fast semi-analytical electromagnetic-thermal coupling calculation framework is proposed that couples a harmonic modeling method (HMM) with a lumped parameter thermal network (LPTN), incorporating heat transfer mechanisms including conduction, convection, and radiation. In the electromagnetic field analysis part, an order-reduced electromagnetic model is constructed using the HMM considering the nonlinearity of the iron core. Based on that, a bi-directional electromagnetic-thermal coupling analysis is realized, and the variation of electromagnetic properties with temperature, including copper conductivity, permanent magnet (PM) remanence, and the permeability of the iron core, are incorporated into the coupling analysis. Notably, the stator teeth are finely segmented in the electromagnetic model to accurately capture magnetic saturation effects under varying temperature conditions. Ultimately, the reliability and accuracy of the proposed method are verified through the finite element method (FEM) and prototype experiments. It is demonstrated that compared with FEM, the proposed framework has a satisfactory calculation efficiency and saves 98.4% of the computation time than FEM, making it suitable for preliminary motor design and optimization considering multiphysics influence.

Authors

Publication Details

Journal
IEEE Transactions on Transportation Electrification
Published
2025-02-18
DOI
https://doi.org/10.1109/tte.2025.3543230
Citations
1
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
0.73

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Order-Reduced Nonlinear Semi-Analytical Multiphysics Model for Axial-Flux Motors

Zhenxiao Yin, Hang Zhao, Xuyang Liu, Fang Li et al.
1 citations
IEEE Transactions on Transportation Electrification
Electric Motor Design and Analysis
0.73
article

Order-Reduced Nonlinear Semi-Analytical Multiphysics Model for Axial-Flux Motors

Zhenxiao Yin, Hang Zhao, Xuyang Liu, Fang Li, Xiangdong Su
article en
1 citations

Abstract

Electromagnetic-thermal analysis is crucial to guarantee the axial flux motors’ (AFMs) reliable operation as their compact size and poor heat dissipation conditions can lead to thermal limits. However, the conventional coupled analysis is extremely time-consuming, especially in 3-D analysis. To this end, a fast semi-analytical electromagnetic-thermal coupling calculation framework is proposed that couples a harmonic modeling method (HMM) with a lumped parameter thermal network (LPTN), incorporating heat transfer mechanisms including conduction, convection, and radiation. In the electromagnetic field analysis part, an order-reduced electromagnetic model is constructed using the HMM considering the nonlinearity of the iron core. Based on that, a bi-directional electromagnetic-thermal coupling analysis is realized, and the variation of electromagnetic properties with temperature, including copper conductivity, permanent magnet (PM) remanence, and the permeability of the iron core, are incorporated into the coupling analysis. Notably, the stator teeth are finely segmented in the electromagnetic model to accurately capture magnetic saturation effects under varying temperature conditions. Ultimately, the reliability and accuracy of the proposed method are verified through the finite element method (FEM) and prototype experiments. It is demonstrated that compared with FEM, the proposed framework has a satisfactory calculation efficiency and saves 98.4% of the computation time than FEM, making it suitable for preliminary motor design and optimization considering multiphysics influence.

IEEE Transactions on Transportation ElectrificationVol. 11(4)
National Natural Science Foundation of China
Openalex Percentile: Top 31%
Electric Motor Design and Analysis
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.