No abstract

No abstract

Abstract. The cross wind risk analysis is today, within the European railway operators, one of the most important items related to the safety problem. In order to define the risk associated to the cross wind along a railway line, the effects of the infrastructure scenarios on the aerodynamic loads acting on a vehicle have to be investigated. A typical railway line is

This paper presents a review of recent research that has been carried out on the cross-wind effects on road and rail vehicles. After a brief introduction to the issues involved, the risk analysis framework is set out. All risk analysis methods require some knowledge of cross-wind aerodynamic force and moment coefficients, and methods of obtaining these through full scale and wind tunnel testing and through Computational Fluid Dynamics methods are then described. The picture of the flow fields around vehicles that is suggested by these measurements and calculations is then presented, and the steady and the unsteady aerodynamic force characteristics described. The detailed methodology for using this information to predict accident risk is then set out, including details of the vehicle dynamics system models that can be used. Finally potential alleviation methods are described and suggestions made for further works.

Huge improvements and advances in sensor technology, together with the increasing demand for safety and handling performances, pull research towards new control strategies. Robustness and promptness of sensors used for active control are key requisites. The main idea behind the research presented in this paper is to instrument the tire with appropriate sensors in order to estimate several contact parameters ranging from the kinematic conditions of the tire (the longitudinal slippage and the side slip angle [Fukada, Y., 1999, Slip-angle estimation for vehicle stability control. Vehicle System Dynamics, 32(4–5), 375–388.]) to its dynamic properties (the contact area shape and dimensions as well as the longitudinal, lateral and vertical loads [Cole, D.J. and Cebon, D., 1989, A capacitative strip sensor for measuring dynamic type forces. Proc. of the Second International Conference on Road Traffic Monitoring, London, 38–42; Cole, D.J. and Cebon, D., 1992, Performance and application of a capacitative strip tyre force sensor. Proc of IEE Conference on Road Traffic Monitoring, London, 123–132.]) and to the adhesion characteristics of the road (the surface roughness [Pasterkamp, W.R. and Pacejka, H.B., 1997, The tire as a sensor to estimate friction. Vehicle System Dynamics, 27, 409–422; Pohl, A., Steindl, R. and Reindl, L., 1999, The ‘intelligent tire’ utilizing passive SAW sensorsmeasurement of tire friction. IEEE Transactions on Instrumentation and Measurement, 48(6), 1041–1046; Ray, L.R., 1997, Nonlinear tire force estimation and road friction identification: Simulation and experiments. Automatics, 33(10), 1819–1833.]). Thus, the tire becomes a sensor of tire–road interaction. Clearly, no other measuring device may ever be more robust nor prompt, and anyway closer to the contact area. After a preliminary research in which the pros and cons of the various sensor technologies were taken into account, it was decided to put accelerometers inside the tire. These accelerometers were fixed to the liner and on-board analysis of the acquired data was performed to reduce the amount of data then sent via radio control to a central data processing unit. This unit, through post-elaboration and recombination of the reduced signals coming from the various accelerometers in the tire, estimates some of the above-described contact parameters. In the near future, these contact parameters coming from all four tires and eventually other signals from sensors placed on the vehicle may be used to develop innovative control strategies in order to increase vehicle performances as well as running safety