基于开启角度优化的改进型 DITC 控制方法

Chaozhi Huang;Wensheng Cao;Zhou Chen;Yuliang Wu;Yongmin Geng
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摘要

开关磁阻电机(SRM)通常采用直接瞬时转矩控制(DITC)来抑制转矩纹波。然而,由于固定的接通角和两相交换区的控制模式,传统的 DITC 控制方法在不同工况下的适应性较差,会产生较大的转矩纹波。针对这一问题,本文提出了一种基于开启角优化的改进型 DITC 控制方法。首先,利用改进的 BP 神经网络构建非线性转矩模型,从而可以实时准确地反馈转矩。其次,建立基于改进型 GRNN 神经网络的接通角优化算法,实现接通角的在线自适应调节。然后,根据电感变化率的大小,将两相交换区域划分为两个区域,选择电感变化率和电流较大的相,在分区域内提供转矩。最后,以三相 6/20 SRM 为例,通过仿真和实验验证了该方法的有效性。
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An Improved DITC Control Method Based on Turn-On Angle Optimization
Switched reluctance motor (SRM) usually adopts Direct Instantaneous Torque Control (DITC) to suppress torque ripple. However, due to the fixed turn-on angle and the control mode of the two-phase exchange region, the conventional DITC control method has low adaptability in different working conditions, which will lead to large torque ripple. For this problem, an improved DITC control method based on turn-on angle optimization is proposed in this paper. Firstly, the improved BP neural network is used to construct a nonlinear torque model, so that the torque can be accurately fed back in real time. Secondly, the turn-on angle optimization algorithm based on improved GRNN neural network is established, so that the turn-on angle can be adjusted adaptively online. Then, according to the magnitude of inductance change rate, the two-phase exchange region is divided into two regions, and the phase with larger inductance change rate and current is selected to provide torque in the sub- regions. Finally, taking a 3-phase 6/20 SRM as example, simulation and experimental verification are carried out to verify the effectiveness of this method.
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