The geometric filtering phenomenon is first analyzed with a simplified vertical vehicle model. Analytical solutions obtained with this model show that geometric filtering phenomenon consists of ‘wheelbase filtering’ and ‘bogie spacing filtering’ effects. The wheelbase filtering effect occurs when there is neither car body bounce nor pitch response at certain track wavelengths, whereas the bogie spacing filtering effect occurs when there is a null in either the car body bounce or pitch response at particular track wavelengths. Then, the correlated frequency response function for railway vehicles is defined to assess the effect of geometric filtering upon the resonant frequencies of a flexible car body. It is found that if the car body’s first bending frequency coincides with the peak values of bounce acceleration transmissibility, that is, it is near the null pitch response frequencies, resonant vibration of the flexible car body will happen. Finally, to suppress the resonant vibration of the flexible car body, it is proposed to use a dynamic vibration absorber (DVA) suspended under the car body underframe. The DVA parameters are optimized according to car body bending frequency and the null pitch frequency. The optimal DVAs show very good performance and robustness in suppression of the car body resonant vibration.

High structural modal frequencies of car body are beneficial as they ensure better vibration control and enhance ride quality of railway vehicles. Modal sensitivity optimization and elastic suspension parameters used in the design of equipment beneath the chassis of the car body are proposed in order to improve the modal frequencies of car bodies under service conditions. Modal sensitivity optimization is based on sensitivity analysis theory which considers the thickness of the body frame at various positions as variables in order to achieve optimization. Equipment suspension design analyzes the influence of suspension parameters on the modal frequencies of the car body through the use of an equipment-car body coupled model. Results indicate that both methods can effectively improve the modal parameters of the car body. Modal sensitivity optimization increases vertical bending frequency from 9.70 to 10.60 Hz, while optimization of elastic suspension parameters increases the vertical bending frequency to 10.51 Hz. The suspension design can be used without alteration to the structure of the car body while ensuring better ride quality.

Low-frequency swaying is an abnormal vibration of railway vehicles. It is manifested by a low-frequency and high-amplitude swaying of the car body, which continues for a period of time, posing a significant threat to the passengers’ ride comfort and even the vehicle operation safety. However, the complexity of swaying makes the alleviation of this hazard by the conventional suspension parameters and available wheel-rail profile optimisation schemes quite problematic. This study analyses the specifics of vibration signal detection and active low-frequency vibration absorption, based on which a comprehensive set of implementable and universal process approaches to detect and control the low-frequency swaying is proposed. First, the intrinsic parameters of various stages of the swaying signal were obtained via the wavelet packet transform. Based on this, two online detection methods based on a single intrinsic parameter and a combination of intrinsic parameters were proposed. Subsequently, an active low-frequency inerter-spring-damper (ISD) type dynamic vibration absorber (DVA) control strategy was adopted to suppress low-frequency swaying. Finally, full-vehicle models with passive suspension and active low-frequency ISD-DVA were established to investigate the effect of online detection and control of low-frequency swaying. The results obtained proved that the proposed method could promptly detect and accurately identify different swaying stages of the railway vehicle, and the active ISD-DVA is instrumental in the low-frequency swaying elimination and overall improvement of the vibration performance of railway vehicle systems.

Ride comfort indices are used to evaluate the vibration of rail vehicles and to measure the discomfort of passengers. Among the various ride comfort indices, the Sperling index is widely used in China and other countries. However, there are several different methods for determining the Sperling index from dynamic simulations and performance measurements of rail vehicles, and the results obtained by different algorithms are inconsistent. It is therefore difficult to make an accurate evaluation with the different calculation results. In this paper, a comparison is made between algorithms based on time domain and frequency domain analysis and using the second and third powers of the acceleration. The different algorithms are then summarised into a unified equation, and the consistency of the results is analysed by this equation. It is found that only the r.m.s-based algorithm in the time or frequency domain is stable when analysis is carried out over different sample times. The time-frequency consistency of the r.m.s-based algorithms is verified by Parseval’s theorem and using calculation results from time domain simulations.