Real-time detection of vehicle hunting performance using a newly proposed evaluation indicator: Methodology and experimental validation

Abstract

During long-term service, railway vehicles are subjected to significant challenges in maintaining stable hunting performance. Developing a reliable diagnostic tool for detecting hunting instability in real-time and establishing a practical method for early warning are crucial to ensuring vehicle safety and operational comfort. In this study, a novel diagnostic approach is introduced, utilizing a newly proposed evaluation indicator, Hunting Coefficient (H_C), to assess wheelset lateral motion. The indicator is derived from the conventional frame lateral vibration acceleration and reformulated to enable evaluation based on wheelset lateral displacement. A high-speed railway vehicle dynamics model is established to reproduce typical hunting phenomena occurring during line operations, identifying key influencing factors and providing preliminary threshold values for H_C calculation. To validate the method, rig tests are conducted on various types of vehicles, including high-speed trains, subways, and express freight wagons. The results show that the H_C-based diagnostic method enables accurate real-time identification of vehicle hunting states, provides early warnings of instability, and serves as a valuable tool for effective vehicle condition monitoring and predictive maintenance.