基于小波神经网络的开关磁阻发电机仿真建模

Simulation modeling of switched reluctance generator based on wavelet neural network

开关磁阻发电机由于其双凸极结构,具有严重的非线性,普通方法难以获得较为准确的仿真模型.采用小波神经网络对开关磁阻发电机进行磁链特性的数据拟合,建立了开关磁阻发电机非线性仿真模型,并通过仿真实验验证了该模型的正确性.该模型为实际开关磁阻发电机研究提供了一种较好的仿真建模方法.

Switched reluctance generator （SRG） has serious nonlinearity due to the doubly salient structure. It is dif ficult to obtain the accurate simulation model of SRG by the general method. In this paper, flux linkage characteris- tic of SRG is fitted by using wavelet neural network. Then the nonlinear simulation model of SRG is established, and the model is tested and verified. It provides a better simulation modeling method for actual SRG research.