| 在几何结构设计中采用遗传算法优化横向磁场永磁电机的转矩波形 |
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| 引用本文： | M.Vinogradski U.Werner B.Orlik. 在几何结构设计中采用遗传算法优化横向磁场永磁电机的转矩波形[J]. 电力电子, 2005, 3(3): 35-39 |
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| 作者姓名： | M.Vinogradski U.Werner B.Orlik |
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| 作者单位： | [1]Institute for Electrical Drives, Power Electronics and Devices, University of Bremen, Bremen, Germany |
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| 摘 要： | 在制造横向磁场永磁电机（TFPM）电机之前，应确定最大转矩的波形。通过调整TFPM电机的各项几何参数，可以使电机达到其最大转矩。一种基于人工智能的最优化方法可以使得每个极间隔都获得理想的转矩波形。本文给出了一种用于优化TFPM几何参数的遗传算法，该算法同样适用于其它结构的电机。
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| 关 键 词： | 永磁电机 最大转矩 算法优化 几何参数 横向磁场 结构设计 遗传算法 波形 最优化方法 |
Genetic Algorithms Used for Geometrical Structure Design of Transverse Flux Permanent Magnet Motors to Optimize the Torque Wave Form |
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| M.Vinogradski;U.Werner;B.Orlik. Genetic Algorithms Used for Geometrical Structure Design of Transverse Flux Permanent Magnet Motors to Optimize the Torque Wave Form[J]. Power Electronics, 2005, 3(3): 35-39 |
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| Authors: | M.Vinogradski U.Werner B.Orlik |
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| Abstract: | It is possible to determine the waveform and maximum value of the torque before the TFPM motor will be built. The geometrical parameters of the TFPM motor will be varied in such a way that the maximum torque can be achieved. In order to obtain a desired torque waveform in every single pole pitch, an optimization method based on artificial intelligence can be used. This work explains how a genetic algorithm can be applied in order to optimize the geometry of a TFPM. This algorithm can be applied to any other motor structure. |
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