Anti-slip control systems are essential for railway vehicle systems with traction. In order to propose an effective anti-slip control system, adhesion information between wheel and rail can be useful. However, direct measurement or observation of adhesion condition for a railway vehicle in operation is quite demanding. Therefore, a proportional–integral controller, which operates simultaneously with a recently proposed swarm intelligence-based adhesion estimation algorithm, is proposed in this study. This approach provides determination of the adhesion optimum on the adhesion-slip curve so that a reference slip value for the controller can be determined according to the adhesion conditions between wheel and rail. To validate the methodology, a tram wheel test stand with an independently rotating wheel, which is a model of some low floor trams produced in Czechia, is considered. Results reveal that this new approach is more effective than a conventional controller without adhesion condition estimation.

防滑控制系统对于具有牵引力的铁路车辆系统至关重要。为了提出有效的防滑控制系统，车轮和轨道之间的粘附信息可能会有用。但是，对运行中的铁路车辆的粘附状态的直接测量或观察是非常需要的。因此，本研究提出了一种比例积分控制器，该控制器与最近提出的基于群智能的粘附估计算法同时运行。该方法提供了在附着-滑动曲线上最佳附着力的确定，从而可以根据车轮和轨道之间的附着条件确定控制器的参考滑动值。为了验证该方法，电车车轮测试台带有独立旋转的车轮，考虑了在捷克生产的一些低层电车的模型。结果表明，这种新方法比没有粘附条件估计的常规控制器更有效。