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Design and Optimization of Hybrid Excitation Synchronous Machine Based on Multi-objective Genetic Algorithm
- Authors
- Yang, Z.; Zhao, W.; Liu, Y.; Wang, X.; Kwon, B.-I.
- Issue Date
- 2020
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- finite element method; hybrid excitation synchronous machine; multi-objective genetic algorithm torque superposition
- Citation
- 2020 IEEE Student Conference on Electric Machines and Systems, SCEMS 2020, pp.124 - 129
- Indexed
- SCOPUS
- Journal Title
- 2020 IEEE Student Conference on Electric Machines and Systems, SCEMS 2020
- Start Page
- 124
- End Page
- 129
- ISSN
- 0000-0000
- Abstract
- To improve the electromagnetic performance of conventional hybrid excitation synchronous machine (HESM), a machine optimization method based on multi-objective genetic algorithm (MOGA) is proposed. The key idea is to improve the torque superposition by optimizing the shifting angle of permanent magnet (PM), thus to maximize the average output torque. The multi-objective global optimization method is used to comprehensively improve the torque and reduce the torque ripple and the amount of PMs. The effectiveness of the optimization scheme is verified by the finite element method (FEM), and the results show that the optimized model has higher average output torque and unit PM torque, as well as lower torque ripple when compared with the conventional model. © 2020 IEEE.
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