减小小功率开关磁阻电机转矩脉动的迭代学习控制

优化开关磁阻电机的相电流波形来减小开关磁阻电机的转矩脉动是国内外学者争相研究的热点问题.本文基于开关磁阻电机的线性和非线性电感模型,在转矩反馈的基础上,提出了转矩补偿的迭代学习控制方法,通过迭代学习,调整各相绕组不同位置的电流给定值,优化开关磁阻电机的相电流波形.仿真研究证实了本文所提出的转矩补偿迭代学习控制方法具有精度高、收敛速度快的优点,从而有效减小了开关磁阻电机的转矩脉动.

Torque Ripple Reduction of a Small Power Switched Reluctance Motor Based on Iterative Learining Control

Optimizing phase current waveforms of switch reluctance motors (SRM) to reduce torque ripple becomes a hotspot question for foreign and domestic researchers to deduce torque ripples of SRM. Based on linear and nonlinear models of SRM, a novel iterative learning control strategy with torque feedback was presented in this paper. Through iterative learning, the given current value is adjusted by different rotor positions to optimize phase current waveform. The simulation results validate that the presented iterative learning control strategy with torque feedback not only has the merit of high precision and fast convergent speed, but also reduces the torque ripples of SRM.