大型磁悬浮CMG转子的组合优化策略

为提高空间站用大型磁悬浮CMG(Control Moment Gyroscope)系统的设计效率,并获得最优设计参数,针对高转速(12000r/min)大角动量(1000N.m.s)磁悬浮转子进行优化设计与分析。提出了一种基于遗传算法(Genetic Algorithm,GA)和序列二次规划算法(Sequential Quadratic Programming,NLPQL)的组合优化策略来优化转子组件。采用ANSYS进行参数化建模,通过ISIGHT软件集成ANSYS实现优化过程。取转子质量和最大等效应力分别最小为优化目标,选择转子轮盘结构尺寸为设计变量,并根据转子运行工况对转子提出包括尺寸、强度、效能等方面约束限制。与GA、NLPQL算法相比组合优化策略的优化结果要优于单纯使用一种全局优化算法或局部优化算法。组合优化策略结果表明转子质量减少了3.92%;安全系数提高了2.69%。实验结果证明了组合优化策略的设计结果。

The Combinatorial Optimization Strategy for Large-Sized Magnetic Suspension Rotor in CMG System

To improve the efficiency and to get the best design parameters of the large-sized magnetic suspension CMG(Control Moment Gyroscope) system being used in space station,a optimization design and analysis method about the rotor with high speed(1200r/min) and big angular momentum(1000 N·m·s) has been proceeded.A combinatorial optimization strategy based on Genetic Algorithm(GA) and Sequential Quadratic Programming(NLPQL) is proposed to optimize the rotor system.ANSYS is used to build a parameterization model,INIGHT and ANSYS are integrated to finish the optimization motor mass and maximal equivalent stress taken to be minimum respectively are chose as the design objects.The wheel disk dimensions are taken as design variables.Size,strength and effectiveness are taken as constraints according to the rotor working condition.Compared with GA and NLPQL in operating efficiency and optimization result,it is found that the combinatorial optimization strategy is better than a global or a local optimization algorithm to be used only.The combinatorial optimization strategy’s result indicates that the mass decreases 3.92 percent,the safety factor improves 2.69 percent.The experimental result demonstrates the combinatorial optimization strategy’s design result.