Reliability, safety and efficiency have always been the top concerns of the railway sector. Indeed it is important to increase performance and to develop sustainable solutions to win new challenges on the playing field with road and plane transport and to be as close as possible to the customer needs. To this end, it is important to have strong levers to optimize performance. The braking system is particularly important since it determines the safety of the system, influences ergonomics of driving and also contributes mostly to the global performance of railway operation in terms of capacity and line speed.
Braking curves, which are computed in real time, represent the core of modern speed control systems. They can be implemented in different ways depending on the underlying technology (beacon transmission, radio transmission, moving block…) but in each case they rely on the Emergency Braking curve (EB). This curve is particularly important since all the other curves are derived from it. The development of ETCS, the European Train Control System has created a unified framework for braking curves, in order to facilitate cross border operation and promote interoperability. ETCS allows a physical and more accurate description of the Emergency Braking curve, with resulting parameters that reflect the characteristics of the emergency braking architecture.
The proposed method shows a system approach to determine the emergency braking performance. All the influent parameters (friction coefficient, cylinder pressure, calliper efficiency…) are taken into account and their characteristics are incorporated in the model. The Monte Carlo statistical method is then used to evaluate iteratively the model of the braking architecture and to determine the requested parameters. The presented tool is also very useful during the design step, for the accurate quantification of the contribution of specific braking systems (brake types or friction materials for instance) to the overall performance of the line.
Pierre Meyer - SNCF - CIM/ESF