基于轨面辨识的电力机车粘着控制仿真研究

Simulation Research on Locomotive Adhesion Control Based on Rail Identification

针对避免因轨面粘着条件变化而造成车轮空转,提出了基于模糊理论的轨面辨识控制方法,将实时蠕滑速度和全维状态观测器实时估计,并利用粘着系数通过模糊逻辑推理判断的当前轨面与标准轨面的相似度,快速、准确地辨识出当前轨面的粘着峰值点。最后通过对牵引电机的输出转矩动态调整,以实现充分利用当前轨面轮轨间接触力的目的。在MATLAB/Simulink中建立四轴电力机车模型进行仿真研究。仿真结果表明:基于模糊理论的轨面辨识粘着控制方法有效的防止了车轮空转,提高了列车运行的稳定性和铁路运输效率。

In order to avoid the slip of the driving wheel caused by the changes of rail adhesion conditions, a control method of rail identification based on fuzzy theory was proposed. Real-time creep speed and adhesion coefficient estimated by full-dimension state observer used fuzzy logic to determine the similarity between current rail and standard trail. Then, the adhesion peak point of current tail was quickly and accurately identified. Finally, the contact force of current track was fully utilized to dynamically adjust the output torque of traction motor. The proposed control method was simulated through four-axise electric locomotive model with MATLAB/Simulink. Simulation results show that the proposed control method effectively prevents the slip of the driving wheel, and improves the stability of train and railway transport efficiency.