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This paper is an attempt to collate and critically appraise the recent advances in control strategies used to solve challenges related to railway vehicles which present nonlinearities and uncertainties. These strategies concentrate on stability of solid axle-wheelsets, guidance for wheelsets to provide the function of track following and curving to reduce all unnecessary creep forces and associated wear/noise. The focus is on active primary and secondary suspensions, braking and traction subsystems. This paper examines potential new and efficient applications of modern predictive control methods, analysis tools and techniques which could be used in effective and reliable condition monitoring systems allowing informed decision making on maintenance and renewals activities.

The interaction between the wheel and rail greatly influences the dynamic response of railway vehicles on the track. A roller rig facility can be used to study and monitor real time parameters that influence wheel-rail interaction such as wear, adhesion, friction and corrugation without actual field tests being carried out. This paper presents the development of the mathematical models for full scale roller rig and 1/5 scale roller rig and the wear prediction model based on KTH wear function. The simulated critical speed for the 1/5 scale roller rig is about one-fifth of the critical speed for the full scale model so the simulated results compare well with the theory related to wheel-rail contact and dynamics. Also the differences between the simulated rolling radii for the full scale model with and without wear function are analysed. This paper presents the initial stage of a large scale research project where the influence of wear on the wheel-rail performance will be studied in more depth.

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Exposure to particulate material (PM) is a major health concern in megacities across the world which use trains as a primary public transport. PM emissions caused by railway traffic have hardly been investigated in the past, due to their obviously minor influence on the atmospheric air quality compared to automotive transport. However, the electrical train releases particles mainly originate from wear of rails track, brakes, wheels and carbon contact stripe which are the main causes of cardio-pulmonary and lung cancer. In previous reports most of the researchers have focused on case studies based PM emission investigation. However, the PM emission measured in this way doesn't show separately the metal PM emission to the environment. In this study a generic PM emission model is developed using rail wheel-track wear model to quantify and characterise the metal emissions. The modelling has based on Archard's wear model. The prediction models estimated the passenger train of one set emits 6.6mg/km-train at 60m/s speed. The effects of train speed on the PM emission has been also investigated and resulted in when the train speed increase the metal PM emission decrease. Using the model the metal PM emission has been studied for the train line between Leeds and Manchester to show potential emissions produced each day. This PM emission characteristics can be used to monitor the brakes, the wheels and the rail tracks conditions in future.