Multi-objective optimization of a Brushless Hybrid Excitation Synchronous Generator Using Axial Excitation

• Published in: 2023 IEEE 6th Student Conference on Electric Machines and Systems (SCEMS) pp. 1 - 7
• Main Authors: Yan, Daqiang, Yu, Junyue, Zhu, Shushu, Liu, Chuang, Wang, Kai
• Format: Conference Proceeding
• Language: English
• Published: IEEE 07.12.2023
• Subjects: genetic algorithm; multi-objective optimization; response surface method; the hybrid excitation synchronous generator
• ISSN: 2771-7577
• DOI: 10.1109/SCEMS60579.2023.10379297

The hybrid excitation synchronous generator has the advantages of flexible air-gap magnetic field adjustment and high power density. The multi-objective optimization of a brushless hybrid excitation synchronous generator using axial excitation is studied in this paper. The stator core loss, total harmonic distortion (THD) of output current and flux modulation coefficient are the optimization objectives of the generator. The sensitivity of the structural parameters is analyzed by Taguchi method and divided into two levels. Based on the hierarchical strategy, response surface method, genetic algorithm and single parameter scanning method are used for multi-objective optimization. In addition, the scheme is compared with the optimization scheme based on the conventional response surface model. By comparing the optimization results of the two schemes, the structural parameters with the best optimization performance of the generator are finally determined. Finally, the feasibility and effectiveness of the optimization method are verified by the three-dimensional finite element simulation.