Abstract
Abstract 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.
Published Version
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