基于三维有限元分析(FEA)的两级代理辅助差分进化电机多目标优化。

N. Taran, D. Ionel, D. Dorrel
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引用次数: 0

摘要

电机设计中需要考虑许多参数,可以采用优化算法。在满足终止准则之前,通常需要进行数千次设计评估。虽然具有三维磁通路径(如轴向磁通和横向磁通)的机器不能用二维模型准确评估,但耗时的三维有限元分析(FEAs)是站不住脚的。一种解决方案是使用替代模型而不是3D有限元分析;然而,在较大的非线性搜索空间中,代理模型的精度会降低。另一种解决方案可以利用用最少设计评估次数找到全局最优的算法。这里提出了这两种解决方案的组合。
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Two-Level Surrogate-Assisted Differential Evolution Multi-ob-jective Optimization of Electric Machines Using 3D Finite Element Analysis (FEA).
Many parameters are considered in electric machine design and an optimization algorithm can be used. These usually need thousands of design evaluations before meeting the termination criterion. Time consuming 3D finite element analyses (FEAs) are not tenable although machines with 3D flux paths, such as axial flux and transverse flux, cannot be accurately evaluated with 2D models. One solution is to use surrogate models rather than 3D FEA; however, the accuracy of surrogate models reduces for a large and nonlinear search space. Another solution can utilize algorithms that find the global optima with a minimum number of design evaluations. A combination of these two solutions is proposed here.
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