Design Optimization of Axial Flux Motor by Genetic Algorithm

• Main Authors: Chun-Chih Tseng, 曾群智
• Other Authors: 楊勝明
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/fuqygq

碩士 === 國立臺北科技大學 === 電機工程系 === 106 === This thesis investigates design optimization of an axial flux permanent magnet synchronous motor. Comparing to traditional radial flux motor, axial flux motor have the advantages of higher power density, torque density and space utilization. A finite element analysis software is used for machine design and performance analysis. The specification and dimensions of the initial design model is based on a 5.0 kW axial flux machine produced by EMRAX. After the initial design, machine structure parameters such as PM width, shoe width, and core high selected as the control variables for sensitivity analysis and single variable optimization. Motor output torque, power density, and lower torque ripple are chosen as the optimization objectives. After the preliminary optimization, variables with greater influences to the objectives were selected for multi-variable optimization using genetic algorithms. The final finite element calculation results show that, comparing the proposed optimized design to the initial design, motor output torque and power density increased 5.8% and 15.6%, respectively, and torque ripple reduced 51.2%.