A Comparative Study of Shape Optimization of SRM using Genetic Algorithm and Simulated Annealing
A Comparative Study of Shape Optimization of SRM using Genetic Algorithm and Simulated Annealing
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DOI：
10.1109/indcon.2005.1590241
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发表时间：
2005-12
期刊：
影响因子：
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通讯作者：
R. T. Naayagi;V. Kamaraj
中科院分区：
文献类型：
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作者：
R. T. Naayagi;V. Kamaraj
利用遗传算法和模拟退火技术对开关磁阻电机进行了形状优化。为了在指定的空间包络内实现所需的性能，利用遗传算法对开关磁阻电机的物理尺寸（定子极弧、转子极弧、转子直径和堆长）进行了优化。采用遗传算法后，SRM的功率密度提高了11.7%。同样使用SA，机器的功率密度提高了26.94%。与标准设计程序相比，拟议的设计突出了性能的改进，尺寸大大减小。GA和SA方法都能最大限度地提高SRM的磁链和单位转子体积的转矩。即使在非常高的功率应用中，如航空航天应用，也可以使用所提出的策略实现类似的优化。对4相、8/6极、lkW、100V、25A、1500rpm的SRM进行了仿真，结果表明了该策略的实用性和有效性。
This paper describes the Shape Optimization of Switched Reluctance Machine (SRM) using Genetic Algorithm (GA) and Simulated Annealing (SA). To achieve the required performance within a specified space envelope, the physical dimensions of the Switched Reluctance Machine like Stator pole arc, Rotor pole arc, Rotor diameter and Stack length were optimized using GA. The proposed strategy improves the Power Density of the SRM by 11.7% using GA. Similarly using SA, the power density of the machine is increased by 26.94%. The proposed design, in comparison with standard design procedures, highlights improvement in performance with considerable reduction in size. Both the methods GA and SA maximize Flux linkage and Torque per unit rotor volume of the SRM. Even in very high power applications such as Aerospace applications, it is possible to achieve similar optimization using the proposed strategy. The simulation results obtained for a 4 phase, 8/6 pole, lkW, 100V, 25A, 1500 rpm SRM signify the usefulness and effectiveness of the proposed strategy.