Utilizing MicroGenetic Algorithm for Optimal Design of Permanent-Magnet-Assisted WFSM for Traction Machines

Author:

Seo Han-Soo1,Park Chan-Bae1ORCID,Kim Seong-Hwi2,Lei Gang3ORCID,Guo Youguang3ORCID,Lee Hyung-Woo1

Affiliation:

1. Department of Railway Vehicle & Operation System Engineering, Korea National University of Transportation, 157, Cheoldobangmulgwan-ro, Uiwang-si 16106, Republic of Korea

2. Department of Electronic Engineering, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea

3. School of Electrical and Data Engineering, University of Technology Sydney, 15, Broadway, Ultimo, NSW 2007, Australia

Abstract

With increasing worries about the environment, there is a rising focus on saving energy in various industries. In the e-mobility industry of electric motors, permanent magnet synchronous motors (PMSMs) are widely utilized for saving energy due to their high-efficiency motor technologies. However, challenges like environmental degradation from rare earth development and difficulties in controlling magnetic field fluctuations persist. To address these issues, active research focuses on the wound field synchronous motor (WFSM), known for its ability to regulate field current efficiently across various speeds and operating conditions. Nevertheless, compared with other synchronous motors, the WFSM tends to exhibit relatively lower efficiency and torque density. Because the WFSM involves winding both the rotor and the stator, it results in increased copper and iron losses. In this article, a model that enhances torque density by inserting permanent magnets (PMs) into the rotor of the basic WFSM is proposed. This proposed model bolsters the d axis magnetic flux, thereby enhancing the motor’s overall performance while addressing environmental concerns related to rare-earth materials and potentially reducing manufacturing costs when compared with those of the PMSM. The research methodology involves a comprehensive sensitivity analysis to identify key design variables, followed by sampling using optimal Latin hypercube design (OLHD). A surrogate model is then constructed using the kriging interpolation technique, and the optimization process employs a micro-genetic algorithm (MGA) to derive the optimal model configuration. The algorithm was performed to minimize the use of PMs when the same torque as that of the basic WFSM is present, and to reduce torque ripple. Error assessment is conducted through comparisons with finite element method (FEM) simulations. The optimized permanent-magnet-assisted WFSM (PMa-WFSM) model improved efficiency by 1.08% when it was the same size as the basic WFSM, and the torque ripple decreased by 5.43%. The proposed PMa-WFSM derived from this article is expected to be suitable for use in the e-mobility industry as a replacement for PMSM.

Funder

Korea Institute of Energy Technology Evaluation and Planning

Publisher

MDPI AG

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