Electromechanical brake (EMB) is a novel braking mode for railway trains. The reliability of the braking system is important for railway system safety. According to the RAMS (Reliability, Availability, Maintainability and Safety) requirements for railway applications, the key issues of prognostics and health management (PHM) for EMB systems are discussed at first. Consequently, the dominant tasks of the PHM system are confirmed, containing the battery State-of-Charge (SOC) and State-of-Health (SOH) estimation, electric components condition monitor, and mechanical crack prediction. Then the critical failure modes of the EMB system and their failure mechanisms are analyzed. Based on the above analysis, a PHM system developed for EMB systems and its working flow are introduced. The vehicle operation parameters, the brake control commands, and the sensor signals are inputs of the PHM system. These inputs are processed and gathered as health indicators. Then the PHM system adopts the physical model or the hybrid algorithms to track the failure mode and components. Finally, the PHM system locates the health stage of the EMB system. The primary health indicators for EMB systems are the braking distance and emergency battery capacity. And the health indicators for components are mapped with the corresponding failure modes. The estimation for the battery SOC and SOH is established based on the test results of battery properties. The model-based and data-driven hybrid method is utilized to detect the crack growth of mechanical components and the degradation in electric properties. The PHM system is useful for condition-based maintenance. And it is meaningful for the reliability and safety improvement of the EMB systems.

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Currently, the theoretical braking force control mode, characterized by actual deceleration as an unstable open-loop output, is the most widely used brake control mode in trains. To overcome the shortcomings of non-deceleration control modes, a deceleration control mode is proposed to realize the closed-loop control of train deceleration. First, a deceleration control algorithm based on parameter estimation was derived. Then, the deceleration control software logic was designed based on the existing braking system to meet the engineering requirements. Finally, the deceleration control algorithm was verified through a ground combination test bench with real brake control equipment and pneumatic brakes. The test results show that the deceleration control can make the actual braking deceleration of the train accurately track the target deceleration in the presence of disturbances, such as uncertain brake pad friction coefficients, line ramps, vehicle loads and braking force feedback errors, as well as their combined effects, and does not affect the original performance of the braking system. The average deceleration in the deceleration control mode is relatively stable, and the control error of instantaneous deceleration is smaller.

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Electropneumatic brake systems are widely used on electric multiple units (EMUs) for high-speed railway and urban rail transit. The common marshalling of the EMUs varies from four to eight cars for urban mass transit and even 16 cars for high-speed way. Traditional methods for braking calculation, which are only suitable for unit-fixed and marshalling-fixed EMUs, are not able to deal with complicated braking process and various marshalling. In this article, a general method for flexible marshalling train braking process simulation is proposed. This method deals with an EMU consisting of 1-24 cars by dividing it into one to eight units and each unit has one to three cars. During braking of EMUs, braking force is calculated according to brake level and velocity, and then managed and applied according to units' type and distributing principle. With this method, braking deceleration, speed, distance and electric braking force, pneumatic braking force and brake cylinder pressure of each car at any time during the whole braking process can be all presented. Simulation covers braking instruction transmission, braking force calculation and management at train level, electric pneumatic blending braking force distribution at unit level and braking force application at vehicle level. Simulation has been validated by field test results. Finally, an instance of simulation for a custom marshalling EMU is presented. The method can not only meet the needs of engineers and technicians to do brake calculation and braking performance validation of the existing fixed marshalling EMUs, but also provide reference for new design of novel flexible marshalling EMUs.

Aerodynamic brake is a clean and environmentally friendly braking mode, which does not use mechanical friction as a braking force. This paper describes the development of a small-distributed aerodynamic brake prototype, including its structure, working principle, ground test, and test results. A computational fluid dynamics (CFD) method is developed to obtain the aerodynamic forces of the prototype, and the simulation results are validated by performing a wind tunnel test. On the basis of the CFD simulation, the panel opening process and braking process are modelled to analyse the vertical dynamic characteristics of a high-speed electromagnetic suspension maglev with aerodynamic brakes. In addition, a vehicle, guideway, and levitation controller are modelled. Finally, a three-car system dynamic model is solved to obtain the influences of the opening time, initial braking position, and feedback gains. The aerodynamic forces of the first car show the most significant changes when the braking panels are opened. The increase in the longitudinal force is 15461.16N, and the vertical force varies from a lift force of 35342.98N to a downforce of 40721.35N. The maximum guideway deflection decreases as the opening time increases. The difference between the deflections obtained at opening times of 0.064 s and 0.6 s is 1.2 mm. Furthermore, vertical accelerations decrease as the opening time increases. The condition in which the vehicle brakes when the first car enters the object guideway has the largest influence on the deflection of the guideway. To ensure levitation stability influenced by the vertical change of the first car, a high feedback gain for the levitation clearance change is required. However, the levitation stability with aerodynamic brakes is weakly affected by the feedback gains for the observed velocity and acceleration of the system.

Pneumatic braking systems are widely used on rail vehicles. Anti-skid control systems are equipped to prevent wheels from locking and ensure braking distances in low adhesion conditions. To model and simulate an anti-skid pneumatic braking system, a concise modelling method was proposed. By dividing the pneumatic braking control unit into two parts, the complex model was simplified according to its working principle. The pneumatic model, kinematic model, adhesion force model and controller model were established and simulated with MATLAB/Simulink and AMESim. The results show that this method is suitable for anti-skid control modelling and simulation and can be used for controller development and verification.

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