基于最优蠕滑率的列车防滑控制研究

Research on Train Anti-skid Control Based on Optimal Creep Rate

由于轨面环境的时变,传统列车防滑算法不能使列车很好地利用轮轨间的黏着力,导致制动距离过大。针对这种现象,提出基于最优蠕滑率的自适应滑模控制算法。该算法首先利用一阶低通滤波器得到轮轨间的黏着力;接着设计一种动态遗忘因子递归最小二乘算法,来对轨面环境的最优蠕滑率进行实时估计;最后在传统滑模算法基础上引入自适应算法,在解决外部干扰的同时,抑制了滑模控制抖动。实验结果表明,该算法可以使蠕滑率快速收敛于参考值,使列车能更好地适应轨面变化,减少了制动距离,保证了良好的防滑效果。

Due to the time-varying environment of the rail surface, the traditional train anti-skid algorithm can not make the train make good use of the adhesion between the wheel and rail, resulting in excessive braking distance. For this phenomenon, an adaptive sliding mode control algorithm based on optimal creep rate is proposed. Firstly, the first-order low-pass filter is used to obtain the adhesion between the wheel and rail. Then,a dynamic forgetting factor recursive least squares algorithm is designed to estimate the optimal creep rate of the rail surface environment in real time. Finally, the adaptive algorithm is introduced based on the traditional sliding mode algorithm, which suppresses the jitter of sliding mode control while solving external interference.The experimental results show that the proposed algorithm can make the creep rate quickly converge to the reference value, make the train better adapt to the rail surface change, reduce the braking distance, and ensure a good anti-slip effect.