智能型电子防滑器控制系统的研究

Research on the Electronically Controlled Intelligent Antiskid System

近几年来 ,我国列车运营速度大幅度提高 ,对制动距离的要求更加严格 ,要求防滑器在制动过程中充分利用轮轨间的粘着以尽量缩短制动距离 ,保证行车安全。因此 ,理想的防滑器必须能够实时跟随轮轨间的最佳粘着。防滑器的控制一般以经验判剧来判断各轴运行状况 ,并进行制动缸压力的调节。由于控制对象的复杂 ,尤其是影响轮轨间粘着系数的随机因素太多 ,难以用传统的控制理论建立控制模型 ,文中利用模糊神经网络控制理论进行了防滑器智能控制模型的研究 ,并开发了相应的仿真软件。根据仿真表明 ,文中建立的控制模型的确能够随着轮轨间粘着的变化而自动调整制动力。

Over the years, the operating speed of train has been raised in a great rate in Chinese railways. To guarantee safety of train operation, it requires more strict braking distance of the train and thus asks the electronic antiskid system to make full use of the adhesion force of wheel-rail effectively for minimizing braking distance. The ideal antiskid system must follow with the optimal adhesion during brake application in real time. The state of wheel is judged by experiential criterion so as to modulate the air pressure of brake cylinder. Because of the complication of wheel-rail, especially the random factors, it is difficult to build up the control model by means of traditional control theory. This paper uses the fuzzy neural network theory to study the control model of antiskid system and has developed the simulation software. The simulation shows that the model introduced in this paper can modulate the braking force with the change of wheel-rail adhesion.