In particular locations of the railway track, the excessively polished rail in the inner corner and the large rail cant will lead to an extremely low wheel–rail contact conicity. Consequently, the carbody hunting instability arises and deteriorates the ride comfort of passengers. In this paper, the carbody hunting instability of an electric locomotive is observed and tested. Combined with the analysis of wheel–rail contact and track condition, the ride comfort and running stability indices are evaluated. The dynamic model for the locomotive is established. The measured wheel and rail profiles as well as the curve radius and superelevation are integrated into the simulation model to reproduce the phenomenon that the carbody hunting displayed violent in the straight line while the abnormal vibration disappeared in the curve segment. The linearised and non-linear study on the optimisation of suspension parameters are carried out to solve the carbody hunting instability. Finally, the optimised measures that decreasing the series stiffness and damping of the yaw damper as well as the primary longitudinal stiffness are put forward, and verified by the on-track test. The investigation enriches the study of carbody hunting instability and gives some ideas to probably solve the abnormal vibration.

A long-term tracking test was performed on a newly designed high-speed train with the nominal speed of 250 km/h. The wheel roughness and structural vibration were both recorded during two re-profiling cycles. The 3rd order polygonal wear was observed in the early stage. The vibration of the axlebox can be aggravated even at lower speed when the passing frequency of polygonal wear approaches the P2 resonance frequency. Subsequently, the 22nd–25th and 14th–15th order developed. The trend analysis suggests that the development of high-order polygonal wear is exponential-like. Moreover, a localised decline is explored during the development progress due to the change of route, which indicates the polygonal wear can be suppressed by reducing the proportion of constant-speed operation. It is also found that the acceleration amplitude of 550–650 Hz shows the most remarkable rise with the mileage, following the 300–400 Hz. However, there is a slight difference of characteristic frequency between the initially dominant peak and the finally developed order. The high-frequency vibration induced by high-order polygonal wear can be noticed on the entire vehicle, and it transmits between the adjacent wheels through the rail.

Hunting stability is a long-standing research topic and has been deeply investigated due to its great influence on railway vehicle dynamic performances. Most of the existing hunting monitoring methods detect only the large amplitude hunting instability (LAHI). However, the small amplitude hunting instability (SAHI) is still hard to be detected accurately and efficiently. To face this challenging problem, this paper describes a signal analysis based hunting instability detection methodology. The proposed method is based on cross-correlation techniques and is able to detect both SAHI and LAHI in a simple, efficient and effective way. Eight cross-correlation indicators (CCIs) are exploited to detect anomalous SAHI and LAHI conditions. A fully detailed dynamic model of one typical high-speed railway vehicle is developed to test the methodology and to compare the CCIs under different vehicle operating conditions. The most effective CCI and its critical values are determined on the basis of the statistics and comparisons of the simulation results. Furthermore, the robustness of the proposed method to distinguish hunting instability and periodic excitations coming from track irregularities has been verified. Finally, the proposed instability detection methodology has been validated by detecting the SAHI successfully on field test data coming from specific experimental campaigns.

Carbody hunting stability has attracted more and more attention due to its great influence on the dynamic performance of a railway vehicle. To fully understand the correlation between the wheel–rail contact relationship and the carbody hunting stability of an electric locomotive, the wheel–rail contact geometry analysis and the multi-body dynamics simulation are carried out in this work. The focus is on the influences of track parameters (including rail profile, rail cant and track gauge) on wheel–rail contact relationships and carbody hunting stability. A group of rail profiles are obtained by interpolating between the standard CHN60 profile and the worn rail profiles. The nominal equivalent conicity, the effective equivalent conicity and the wheel–rail contact bandwidth for a wheelset lateral displacement of ±6 mm are used to evaluate the wheel–rail contact relationship, while the lateral continuous comfort index is used to evaluate the carbody hunting stability. The simulation results show that keeping the rail cant at about 1/40 and reducing the track gauge and the wear depth at the gauge corner of rail can improve the carbody hunting stability of the electric locomotive. Furthermore, the effective equivalent conicity is a good choice to establish the relationship between the wheel–rail contact geometry and the carbody hunting stability.

This paper describes a measuring system for hunting monitoring which considers the real-time wheel/rail contact relationships of high-speed railway vehicles during violent hunting motions. The proposed monitoring system relies on signal-based techniques and is able to predict the wheelset lateral displacement and yaw angle as well as the wheel/rail contact relationships in an efficient, effective and low-cost way. The Hankel matrix-based singular value decomposition (SVD) method is applied for the prediction by using the sensor-collected bogie lateral accelerations as inputs. To achieve real-time performances, the look-up table (LUT) method is used to carry out the wheel/rail contact analysis. The accuracy and efficiency of the proposed method have been validated by comparisons of the predicted results with simulated and experimental results. Finally, the critical values are corrected based on the comparison results.