Multimaterial Topology Optimization of Electric Machines Based on Normalized Gaussian Network
Multimaterial Topology Optimization of Electric Machines Based on Normalized Gaussian Network
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DOI：
10.1109/tmag.2014.2359972
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发表时间：
2015-04
影响因子：
2.1
通讯作者：
Takahiro Sato;Kota Watanabe;H. Igarashi
中科院分区：
文献类型：
--
作者：
Takahiro Sato;Kota Watanabe;H. Igarashi
提出了一种基于归一化高斯网络的多材料模型拓扑优化方法。在这种方法中，可以确定由各种材料（如铁，磁性和非磁性材料）组成的机器的最佳形状。应用该方法对内置式永磁电机的平均转矩进行了优化设计，确定了电机的磁芯分布、磁栅分布和磁体分布。优化结果表明，使用尽可能少的磁体可以提高平均转矩。此外，还详细讨论了该方法的特点。
This paper presents a topology optimization method for multimaterial models based on the normalized Gaussian network. In this method, one can determine optimal shapes of machines that are composed of various materials, such as iron, magnetic, and non-magnetic material. The present method is applied to the optimization of the average torque for interior permanent magnet motor to determine the distributions of magnetic core and flux barrier as well as magnets. The optimization results show that average torque can be improved using as small amount of magnet as possible. In addition, the characteristic of the present method is discussed in detail.