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Design optimization of magnetic gears using mesh adjustable finite-element algorithm for improved torque

机译:使用网格可调有限元算法的电磁齿轮设计优化,以提高扭矩

摘要

Magnetic gears (MGs) are devices which operate through the interaction of magnetic fields produced by multipole magnets to transmit torque with high efficiency. Compared with mechanical gears, it requires no moving contact for the force transmission, hence there are no mechanical fatigue and no mechanical loss and less acoustic noise. There is no need for lubrication and hence MG requires minimal maintenance. However, the heavy use of permanent magnetic (PM) materials leads to a high production cost. In this paper, a novel mesh adjustable finite-element algorithm is proposed to optimize the magnetic gear dimensions in order to maximize the torque output for a given amount of PMs. With the proposed mesh adjustable finite-element algorithm, the coordinates of mesh nodes are moved according to dimensional changes, without compromising the mesh quality. The merit is that no re-mesh is required during the process of optimization, which can significantly reduce the computing time while retaining the robustness of the algorithm. By combining the proposed approach with particle swarm optimization (PSO) algorithm, a reliable convergence to the finding of global optimum is achieved. This proposed method is applied to optimize the dimensions of a coaxial magnetic gear with surface mounted PMs. Optimal results confirm the validity and effectiveness of the proposed algorithm.
机译:电磁齿轮(MGs)是一种通过多极磁体产生的磁场的相互作用进行操作以高效传递扭矩的装置。与机械齿轮相比,它不需要动接触来传递力,因此没有机械疲劳,无机械损耗和较少的噪音。无需润滑,因此MG需要的维护最少。然而,大量使用永磁(PM)材料导致高生产成本。在本文中,提出了一种新颖的网格可调有限元算法,以优化电磁齿轮尺寸,从而在给定数量的PM情况下最大化扭矩输出。利用提出的网格可调有限元算法,网格节点的坐标根据尺寸变化而移动,而不会损害网格质量。优点是在优化过程中不需要重新网格划分,这可以显着减少计算时间,同时保持算法的鲁棒性。通过将提出的方法与粒子群优化算法相结合,实现了全局最优解的可靠收敛。应用该方法可以优化带有表面安装式永磁电机的同轴电磁齿轮的尺寸。最优结果证实了所提算法的有效性和有效性。

著录项

  • 作者

    Niu S; Chen N; Ho SL; Fu WN;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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