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Optimal Design of Interior Permanent Magnet Synchronous Motor Using Improved Genetic Algorithm

机译:基于改进遗传算法的永磁同步电动机优化设计。

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Genetic algorithm (GA) works on the principle of "survival of the fittest will win." It is not a mathematically guided solver. Therefore, it possesses an intrinsic flexibility and the freedom to choose a desirable solution according to the design specifications and can give the optimal solution though the objective is very hard optimization one. But, GA has an shortcoming. That is, GA is very fast at searching near optimal value but needs much time to converge to optimal value. In this paper, an improved GA is proposed to overcome the demerit of standard GA by adopting an adjusted fitness calculation and memory operator. And the improvement of proposed algorithm is verified by applying to sync function and the design of interior permanent magnet synchronous motor(IPMSM).
机译:遗传算法(GA)遵循“优胜劣汰将获胜”的原则。它不是数学指导的求解器。因此,它具有内在的灵活性,并且可以根据设计规范自由选择所需的解决方案,并且尽管目标是非常困难的优化,但却可以提供最佳解决方案。但是,GA有一个缺点。也就是说,GA在搜索接近最佳值时非常快,但是需要很多时间才能收敛到最佳值。本文提出了一种改进的遗传算法,通过采用调整后的适应度计算和记忆算子来克服标准遗传算法的缺点。通过将其应用于同步功能和室内永磁同步电动机(IPMSM)的设计,验证了所提出算法的改进。

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