Multi-fault diagnosis method of high-speed train battery packs base on DFD-DBSCAN

The battery system in high-speed trains, which serves as a backup power source, is extensively utilized in auxiliary power supply systems, with its reliability being crucial for driving safety. The complex operational environment of trains, characterized by frequent starts and stops, acceleration and deceleration, as well as vibrations, can easily cause failures in individual battery cells and connections. To ensure the safe operation of high-speed trains, the state monitoring and multi-fault diagnosis of high-speed train battery packs have garnered significant attention. Currently, there is a gap in the research on multi-fault diagnostic methods for high-speed train battery packs. This paper proposed a real-time multi-fault diagnostic method for high-speed train battery packs, based on an improved Discrete Fréchet Distance (DFD) and an adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. This method aimed to accurately identify connection and individual cell faults in the battery pack. Focusing on high-speed train batteries, this study designed a voltage cross-measurement method suitable for high-speed train battery packs, linking battery voltage and connection board voltage with different voltage sensors. The DFD algorithm was employed to extract fault characteristics of the battery pack. The voltage deviation rate and DFD were used together as input parameters for the fault diagnosis model to enhance the algorithm's robustness and reliability. Subsequently, the DBSCAN algorithm was introduced for automatic fault diagnosis and localization. To ensure the real-time nature of the algorithm, a sliding window-based forgetting mechanism was utilized for real-time diagnosis of the sampled data. Experiments conducted to validate the proposed method demonstrate its effectiveness in timely and accurately diagnosing and pinpointing individual cell and connection faults in battery packs. This approach fills the research gap in multi-fault diagnostic methods for high-speed train battery packs and holds practical engineering significance in enhancing the safety of rail transportation. © 2024, Central South University Press. All rights reserved.