摘要
电机优化设计的传统方法通常采用场路数值分析和有限元方法,设计周期长、效率低、运算量大。为解决这一问题,提出将遗传智能算法同有限元法相结合,能够有效缩短设计周期,显著提高优化效率;并首次提出将MATLAB与COMSOL联合仿真进行永磁同步发电机的优化。首先分析永磁同步发电机的结构和电磁特性,建立电机数学模型,然后研究遗传算法的原理和实现步骤,最后实现MATLAB与COMSOL联合仿真,实现两者之间数据的双向传递。通过在MATLAB中直接提取永磁同步发电机COMSOL计算模型结果,再传递给遗传算法寻找适应度函数最优解,最终完成电机优化。实验结果验证了MATLAB与COMSOL联合仿真优化电机的可行性,为电机优化设计提供了1种新的设计思路。
The traditional method of optimal design of electric machine usually uses the numerical analysis and finite element method,which has long design period,low efficiency and sophisticated computation.In order to solve this problem,this paper presented the combination of genetic algorithm and the finite element method,which can shorten the design cycle,improve the efficiency and reduce the computational complexity.And the co-simulation of MATLAB and COMSOL is put forward in the first time to optimize permanent magnet synchronous generator（PMSG）.Firstly,the structure and electromagnetic properties of PMSG is analyzed,and mathematical model is established.Then,the principle and implementation steps of genetic algorithm are discussed.Finally,the joint simulation of MATLAB and COMSOL and the bi-directional data flows is realized.The COMSOL model computational results of PMSG is extracted by MATLAB in directly,then it is transferred to genetic algorithm to find the optimum solution of the fitness function,and the motor optimization is finally completed.The feasibility of MATLAB and COMSOL co-simulation to optimize motor is verified,providing a new design idea for optimization design of motor.
出处
《中国科技论文》
北大核心
2017年第17期2012-2017,共6页
China Sciencepaper
基金
国家自然科学基金资助项目(51207105
51577132)
