摘要：基于星三角原理设计转子绕组的绕线式无刷双馈电机是在风力发电等领域具有良好应用前景的新型无刷双馈电机。合理地在定子功率绕组和控制绕组之间分配磁负荷和电负荷可以获得最大的输出转矩，降低损耗，提高其性能指标。本文根据电机的等效电路，在优化电机参数时，采用了一种改进的粒子群优化算法，粒子通过同时追随自己找到的最优解、随机的其它粒子同维度的最优解和整个群的最优解来完成速度更新，通过判别区域边界来完成位置优化更新。并把这种改进的算法与模拟退火机制相结合，既实现了进化算法全局优化的特性，又保持了优化算法的快速收敛速度。样机实验结果表明，基于星－三角原理的绕线式无刷电机具有优良的稳态特性，经过优化处理后其性能得到进一步改善。

关键词：星三角；无刷双馈电机；设计优化

Abstract: The woundrotor Brushless Doublyfed Machine(BDFM) with a structure in the form of stardelta(YΔ) is a new type of BDFM. The machine is intended for use as a variable speed generator. Maximum torque output may be obtained by optimally dividing the overall magnetic loadings and electric loadings between the stator windings attending by reasonable rotor winding. This paper proposed an improved particle swarm optimization algorithm (IPSO) for solving the parameter design optimization of the brushless doublyfed generator based on the equivalent circuit. The algorithm completed the optimization through following the personal best solution of each particle, the best solution of same dimensions of other stochastic particle and the global best value of the whole swarm on speed update, through judging by area boundary on position update. It achieved global searching and solved easy trapping into local optimum value problem of late IPSO by inducting mechanism of Simulated Annealing(SA). Finally, the correctness of results was verified through the experiment of laboratory BDFM.

Key words: stardelta; brushless doublyfed machine; design optimization.