Air Gap Magnetic flux Optimization of Halbach Permanent Magnet Motor

DOI

10.2991/amms-17.2017.94How to use a DOI?

Keywords

halbach array; permanent magnet motor; finite element method; genetic algorithm; taguchi algorithm; pattern search algorithm

Abstract

This paper built a finite element model of the Halbach permanent magnet motor, whose accuracy was verified by comparing the output phase back-electromotive force of the model with that of the prototype motor. Keeping other parameters constant as far as possible, we investigated five variables one by one to find out the law how these variables affect air gap magnetic flux, which is a basis for further optimization research. After a new variable named Cost constructed to reflect the distortion ratio of air gap magnetic flux, this paper performed some optimization experiments by studying five parameters of the motor using Taguchi Algorithm, Genetic Algorithm and Pattern Search Algorithm. On the basis of summarizing the advantages and disadvantages of these Algorithms, we proposed two kinds of novel hybrid optimization Algorithms, which are named as Taguchi-Pattern Search Algorithm and Genetic-Pattern Search Algorithm, and proved the validity and practicability by experiments and finite element calculations.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xinsheng Zhan
AU  - Zhi Ji
AU  - Xiping Bao
PY  - 2017/11
DA  - 2017/11
TI  - Air Gap Magnetic flux Optimization of Halbach Permanent Magnet Motor
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 430
EP  - 438
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.94
DO  - 10.2991/amms-17.2017.94
ID  - Zhan2017/11
ER  -