摘要
电励磁双凸极发电机是一种新型的交流无刷电机,结构简单,可靠性高,在汽车和飞机发电领域有着广阔应用前景。但其磁链和电感均为激磁电流、相电流、转子位置的非线性函数无法采用常规的方法建立精确的数学模型。该文采用二维电磁场有限元法对一台12/8极电励磁双凸极发电机进行了精确分析计算,得到了电机的静态特性;利用模糊神经网络的非线性逼近能力,尝试建立了双凸极电励磁发电机的模糊神经网络非线性模型,获得了很高的模型精度,并将仿真分析结果与实验结果进行了对比,验证了所建模型的精确性、有效性及方法的可行性,为飞机直流发电系统的设计、分析建立了基础。
Fielding-winding doubly salient generator is anew type of brushless electrical machine, which offers anexcellent balance between cost, reliability, power density ,andhigh speed capability. So there is an excellent potential inaircraft and automobile. But it always operates within thesaturation region. The phase flux linkage and induction are anonlinear variation of the rotor position and current. So it isdifficult to derive a comprehensive mathematics model toexactly describe the behavior of the generator. In this paper, a12/8 pole prototype field-winding doubly salient brushless DCgenerator is designed and calculated using 2-D FEM, the staticcharacteristic is obtained. Based on the Sugeno fuzzy-neuralnetwork(FNN), a nonlinear model of fielding-winding doublysalient generator is firstly presented in this paper. Simulationresults show that this model is highly precise and less timeconsuming for convergence. It is compared with experimentalresults. The validity and accuracy of the approach is alsoverified with experiment results, It establishes the base ofanalyzing direct current aircraft electrical power generatingsystem.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2005年第10期137-143,共7页
Proceedings of the CSEE
关键词
电励磁双凸极发电机
非线性模型
静态特性
数学模型
模糊神经网络
Electric machinery
Field-winding doublysalient generator
FEM
Static characteristic
Nonlinearmodeling
Fuzzy-neural network
