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Design and Optimization of Hybrid Excitation Synchronous Machine Based on Multi-objective Genetic Algorithm

机译:基于多目标遗传算法的混合励磁同步机的设计与优化

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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.
机译:为提高常规混合励磁同步机(HESM)的电磁性能,提出了一种基于多目标遗传算法(MOGA)的机器优化方法。关键思想是通过优化永磁体(PM)的换档角度来改善扭矩叠加,从而最大化平均输出扭矩。多目标全球优化方法用于全面改善扭矩并降低扭矩脉动和PM的量。通过有限元方法(FEM)验证了优化方案的有效性,结果表明,与传统模型相比,优化模型具有更高的平均输出扭矩和单位PM扭矩,以及更低的扭矩脉动。

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