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A novel anti-slip control approach for railway vehicles with traction based on adhesion estimation with swarm intelligence
Railway Engineering Science ( IF 4.4 ) Pub Date : 2020-11-24 , DOI: 10.1007/s40534-020-00223-w
Abdulkadir Zirek , Altan Onat

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.



中文翻译:

基于群智能的附着力估计的铁路牵引车辆防滑控制新方法

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。

更新日期:2020-11-25
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