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A novel anti-slip control approach for railway vehicles with traction based on adhesion estimation with swarm intelligence

机译:基于骨折估计的铁路车辆铁路车辆的一种新型防滑控制方法

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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.
机译:防滑控制系统对于具有牵引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以是有用的。然而,在操作中直接测量或观察铁路车辆的粘附条件是非常苛刻的。因此,在本研究中提出了一种与最近提出的基于群体基于智能的粘合估计算法同时操作的比例积分控制器。该方法提供了在粘合滑移曲线上最佳的粘合力的确定,使得控制器的参考滑动值可以根据车轮和轨道之间的粘附条件来确定。为了验证方法,可以考虑具有独立旋转轮的电车轮测试支架,这是捷克地区生产的一些低层电车的模型。结果表明,这种新方法比传统控制器更有效而没有粘附条件估计。

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