矿用电机车直接转矩智能控制策略

A direct torque intelligent control strategy for mine-used electric locomotive

介绍了矿用电机车直接转矩控制的基本原理,针对传统直接转矩控制低速时电流和转矩波动较大的缺点,提出了基于模糊神经网络的预期电压矢量控制方法,通过模糊神经网络智能控制器产生预期电压矢量,并采用空间矢量脉宽调制法产生开关电压。仿真结果表明,该方法明显优于传统的直接转矩控制,减少了电流和转矩脉动,提高了系统的控制性能。

The basic theory of DTC （direct torque control） for mine-used electric locomotive was introduced, and in view of huge fluctuation of current and torque at low speed in traditional DTC, prospective voltage vector control method based on fuzzy neural network was put forward. Prospective voltage vector produced through fuzzy neural network intelligent controller, while switching voltage produced by applying space vector pulse width modulation. Simulation results showed that the method was superior to traditional DTC, and reduced the fluctuation of current and torque, thus the control performance of the system improved.