Multiobjective Optimization of a Tubular Coreless LPMSM Based on Adaptive Multiobjective Black Hole Algorithm

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

1 Scopus Citations
View graph of relations

Author(s)

  • Tao Wu
  • Zhenan Feng
  • Gang Lei
  • Youguang Guo
  • Jianguo Zhu
  • Xinmei Wang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)3901 - 3910
Journal / PublicationIEEE Transactions on Industrial Electronics
Volume67
Issue number5
Online published17 May 2019
Publication statusPublished - May 2020

Abstract

In most multi-objective optimization problems of electrical machines, the weighted function method is used to convert them into single-objective optimization problems. This paper applies a kind of new multi-objective evolutionary algorithms (MOEAs), called adaptive multi-objective black hole (AMOBH) algorithms, to achieve effective multi-objective optimization of a tubular coreless linear permanent magnet synchronous motor (LPMSM). To reduce the computation cost of the MOEAs, a one-layer analytical model (AM) is presented for the tubular coreless LPMSM in this paper. The accuracy of the simplified one-layer AM is verified by comparisons with multi-layer AM and finite element analysis (FEA) under different structure parameters. It is found that the simplified AM has good accuracy and can decrease the computation cost significantly. AMOBH algorithm is subsequently introduced. The optimal Pareto front with regard to thrust, copper loss and permanent magnet volume are analyzed, and more diversified optimization results are provided. The final Pareto solution can be selected directly by practical physical values according to the application requirements. Finally, a prototype is fabricated for the selected design; its experimental results are provided and compared with those of the FEA results.

Research Area(s)

  • Analytical method, linear permanent magnet synchronous motor (LPMSM), multiobjective optimization

Citation Format(s)

Multiobjective Optimization of a Tubular Coreless LPMSM Based on Adaptive Multiobjective Black Hole Algorithm. / Wu, Tao; Feng, Zhenan; Wu, Chong; Lei, Gang; Guo, Youguang; Zhu, Jianguo; Wang, Xinmei.

In: IEEE Transactions on Industrial Electronics, Vol. 67, No. 5, 05.2020, p. 3901 - 3910.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal