Two-level Topology Optimization based on a Metaheuristic Method and Morphological Reconstruction

被引:1
|
作者
Ruzbehi, Shabnam [1 ]
Hahn, Ingo [1 ]
机构
[1] Univ Erlangen Nurnberg, Inst Elect Drives & Machines, Erlangen, Germany
关键词
Morphological Reconstruction; Binary Genetic Algorithm; topology optimization; Actuators;
D O I
10.1109/IECON48115.2021.9589937
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper offers a Topology Optimization (TO) method to replace conventional parameter optimization, which is a common method for electrical machine's or electromagnetic device's design optimization. In most of the final designs gained with TO, there are challenges in the manufacturing process using the nowadays available manufacturing technologies. Therefore, this work investigated the approach on two tasks, in the first level a global optimization method, called Enhanced Binary Genetic Algorithm is applied to the design domain. After optimization with this meta-heuristic method, some holes inside the structure or some spread iron cells appear. This drawback will be improved in the second level by one of the image processing methods, called Morphological Reconstruction, to gain a smoother shape to reduce the manufacturing complexities while reaching reasonable technical characteristics. The goal is to find a lighter weight of the structure while preserving the force in a suited amount. The proposed method is applied to an E-core actuator as a case study. After using the proposed hybrid optimization method, air cells appear around some parts of the actuator's coil, which are used to extend the copper areas, so that the magnetic force considerably increases. In general, it is possible to extend the method to different active parts of the electrical machines.
引用
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页数:5
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