Robust Multiobjective and Multidisciplinary Design Optimization of Electrical Drive Systems

作     者：Gang Lei Tianshi Wang Jianguo Zhu Youguang Guo 

作者机构：School of Electrical and Data EngineeringUniversity of Technology SydneySydney2007Australia School of Electrical and Information EngineeringThe University of SydneyAustralia 

出 版 物：《CES Transactions on Electrical Machines and Systems》 (中国电工技术学会电机与系统学报（英文）)

年 卷 期：2018年第2卷第4期

页      面：409-416页

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

主　　题：Electrical drive systems electrical machines multidisciplinary design optimization multiobjective optimization robust design optimization 

摘      要：Design and optimization of electrical drive systems often involve simultaneous consideration of multiple objectives that usually contradict to each other and multiple disciplines that normally coupled to each *** paper aims to present efficient system-level multiobjective optimization methods for the multidisciplinary design optimization of electrical drive *** the perspective of quality control,deterministic and robust approaches will be investigated for the development of the optimization models for the proposed ***,two approximation methods,Kriging model and Taylor expansion are employed to decrease the computation/simulation *** illustrate the advantages of the proposed methods,a drive system with a permanent magnet synchronous motor driven by a field oriented control system is *** and robust Pareto optimal solutions are presented and compared in terms of several steady-state and dynamic performances(like average torque and speed overshoot)of the drive *** robust multiobjective optimization method can produce optimal Pareto solutions with high manufacturing quality for the drive system.