Intelligent Memetic Algorithm Using GA and Guided MADS for the Optimal Design of Interior PM Synchronous Machine

被引：30
|
作者：
Lee, Dongsu [1 ]
Lee, Seungho [1 ]
Kim, Jong-Wook [1 ]
Lee, Cheol-Gyun [2 ]
Jung, Sang-Yong [1 ]
机构：
[1] Dong A Univ, Dept Elect Engn, Pusan 604714, South Korea
[2] Dong Eui Univ, Dept Elect Engn, Pusan 614714, South Korea
来源：
IEEE TRANSACTIONS ON MAGNETICS | 2011年 / 47卷 / 05期
关键词：
Constant power speed ratio (CPSR); genetic algorithm (GA); guided mesh adaptive direct search (guided MADS); intelligent memetic algorithm; interior permanent magnet synchronous machine (IPMSM); SEARCH ALGORITHMS; OPTIMIZATION;
D O I：
10.1109/TMAG.2010.2072913
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Optimal design of an electric machine based on finite element analysis (FEA) calls for much longer computation time for maintaining high accuracy. In order to compensate for the excessive computation time and guarantee the reliable convergence to a global optimum, an intelligent memetic algorithm is newly implemented by combining a genetic algorithm (GA) and the guided mesh adaptive direct search (MADS) that employs an extension search step after the poll step. The effectiveness of guided MADS (GMADS) alone has been verified through the function optimization, and the proposed memetic algorithm is applied to an optimal design of an interior permanent magnet synchronous machine (IPMSM), of which the cost function has many local minima. Optimization results confirm that the proposed method locates an acceptable solution more effectively maintaining the reliable accuracy.
引用
收藏
页码：1230 / 1233
页数：4
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