Car Body Acceleration Research Articles

Comparative analysis of ride comfort evaluation indices of high-speed vehicles based on a vehicle-seat-human body coupled dynamics model

As high-speed vehicles become increasingly lightweight, the influence of passengers on the vehicle vibration system cannot be overlooked. In this paper, a 3D vehicle-seat-human body coupled dynamics model is established to comprehensively evaluate the ride comfort of high-speed vehicles. The model combines the passenger biomechanics with the carbody flexibility. This is often neglected in previous studies and only the carbody vibrations are considered. Applying the validated model, four types of ride comfort evaluation indices are calculated and compared at 250–400 km/h. Results show that the ride comfort of high-speed vehicles at different speeds is excellent when the carbody acceleration and Sperling indices are used. While the results are significantly different when the total equivalent weighted acceleration and annoyance rate indices based on human body vibrations are used. At full load and speed of 400 km/h, the passengers sitting near the windows at both ends of the carbody felt ‘slightly uncomfortable’ or ‘less comfortable’ with an annoyance rate of about 30%, which indicates that up to 30% of the passengers might find the vibrations intolerable. This study underscores the necessity of integrating human body vibrations and passenger subjective psychology into ride comfort assessments, which can provide theory references for the selection and optimization of evaluation indices for high-speed lightweight vehicles.

A robust and fail-safe semi-active vertical damper to improve ride comfort

In recent years, the technical progress in railway engineering has led to the integration of electronic elements in suspension components that once were purely mechanical. Many studies have been carried out, developing active and semi-active suspensions. Among these, semi-active suspensions are particularly attractive due to their simpler design compared to fully active ones. In this context, this paper proposes a semi-active vertical damper to be implemented on the secondary suspension stage of rail vehicles. A prototype is developed by modifying a pre-existing passive damper through the addition of an external servo-valve which manages an additional by-pass channel between the compression and rebound chambers. The prototype is characterised on a dedicated test rig. A reduced vehicle model is then developed as the starting point in developing a sliding mode controller to manage the semi-active feature of the damper. A time-varying sliding surface containing the state of the system and car body accelerations is proposed. Finally, the damper prototype is tested on a hardware-in-the-loop test rig, focusing the experimental campaign on quantifying the damper performance, the evaluation of the controller robustness and a failure analysis to study the behaviour of the proposed solution even in the case of unexpected failures.

Estimation of speed-related car body acceleration limits with quantile regression

PurposeThis study aimed to facilitate a rapid evaluation of track service status and vehicle ride comfort based on car body acceleration. Consequently, a low-cost, data-driven approach was proposed for analyzing speed-related acceleration limits in metro systems.Design/methodology/approachA portable sensing terminal was developed to realize easy and efficient detection of car body acceleration. Further, field measurements were performed on a 51.95-km metro line. Data from 272 metro sections were tested as a case study, and a quantile regression method was proposed to fit the control limits of the car body acceleration at different speeds using the measured data.FindingsFirst, the frequency statistics of the measured data in the speed-acceleration dimension indicated that the car body acceleration was primarily concentrated within the constant speed stage, particularly at speeds of 15.4, 18.3, and 20.9 m/s. Second, resampling was performed according to the probability density distribution of car body acceleration for different speed domains to achieve data balance. Finally, combined with the traditional linear relationship between speed and acceleration, the statistical relationships between the speed and car body acceleration under different quantiles were determined. We concluded the lateral/vertical quantiles of 0.8989/0.9895, 0.9942/0.997, and 0.9998/0.993 as being excellent, good, and qualified control limits, respectively, for the lateral and vertical acceleration of the car body. In addition, regression lines for the speed-related acceleration limits at other quantiles (0.5, 0.75, 2s, and 3s) were obtained.Originality/valueThe proposed method is expected to serve as a reference for further studies on speed-related acceleration limits in rail transit systems.

Improving the energy efficiency and riding comfort of high-speed trains across slopes by the optimized suspension control

As the link between cities, the high-speed train (HST) not only effectively enhances national and regional accessibility, but also induces much energy consumption. On the other hand, passengers have a higher requirement for riding comfort of HST than before. Considering the impacts of slope gradient on energy consumption and vertical carbody acceleration, this paper optimizes the scale factor of the damper controller depending on the running condition to juggle the energy efficiency and riding comfort when HST is across slopes. Firstly, the multibody dynamics simulation model of HST is established to evaluate the energy consumed by motion resistances and carbody vibrations. Then the Skyhook control strategy is applied to the secondary vertical damper of the vehicle model. The effects of vehicle speed, slope gradient, and scale factor of the Skyhook controller on energy saving and vertical carbody acceleration of HST are investigated. Based on the simulation results, the Gaussian process regression model is established to predict the vehicle performance and describe the bi-objective optimization problem. It is demonstrated that the optimized Skyhook control system can at most save energy consumed by motion resistances by 8.52 % or reduce vertical carbody acceleration by 37.14 % without sacrificing the other target. Finally, a comprehensive feasibility and economic analysis of the proposed control system is carried out to promote its practical implementation.

Research on the traction characteristic evaluation of urban rail vehicles based on entropy weight TOPSIS

This paper aims to investigate the influence of different speed at the end of the constant power section of the traction characteristic curve (TCC) on the vehicle dynamic performance and evaluate the TCC. A dynamics co-simulation model is developed in SIMPACK and MATLAB for dynamic analysis of the urban rail vehicle (URV) under different traction characteristics. Then it is used to investigate how acceleration distance and vehicle dynamic performance varies with the speed at the end of the constant power section of the TCC under different starting torques. Moreover, the entropy weight TOPSIS method which is widely used to solve the multi-objective decision-making problem is chosen to evaluate the traction characteristics based on various dynamic performance indexes over 25 test sections and acceleration distance. The results show that under traction conditions, the starting torque has effects on the lateral and vertical accelerations of car body, lateral and vertical wheel-rail contact forces, derailment coefficient and wheel unloading factor. The higher the torque, the greater the value of each index, that means the poorer the vehicle ride characteristics and running safety. For a given starting torque, the dynamic performance indexes increase with the increase of the speed at the end of the constant power section from 50 km/h to 80 km/h during the vehicle speed-up process. The maximum growth rate of the lateral and vertical accelerations of car body, lateral and vertical wheel-rail contact forces are 17%, 8%, 8% and 2%, respectively, when the speed at the end of the constant power section increases from 50 km/h to 80 km/h. Last, the comprehensive evaluation of traction characteristics using entropy-weight TOPSIS method reveals when the starting torque is 800 [Formula: see text], 1000 [Formula: see text], 1200 [Formula: see text] and 1400 [Formula: see text], the corresponding optimal speed at the end of the constant power section is 80 km/h, 80 km/h, 70 km/h and 50 km/h, respectively. The result of the study can provide theoretical support for traction characteristic design and traction control for URVs.

Assessment of random dynamic behavior for EMUs high-speed train based on Monte Carlo simulation

A novel statistical method was developed to obtain a dynamic response with irregular line excitations and independent uncertain parameters. The proposed approach combines a three-dimensional vehicle-track coupling dynamics model and uncertainty parameters. Moreover, a new method is used to treat the dynamic indices: derailment coefficient, vertical/lateral wheel/rail force, vertical/lateral car body acceleration, and wheel reduction ratio. The model is validated by comparing simulations (deterministic) results with field measurements, which provide excellent agreement with limited data. According to the findings, the results reveal that the high vibration effect arises when the uncertainty parameter in the dynamic system exists. The total fit effects, the consistency of the vehicle safety, and the tail fit effects are determined for selecting the best method. Therefore, regarding the approach, the lognormal and extreme maximum distribution values may be the appropriate assumed distribution for dynamic safety under limited data.

Intelligent identification of differential subgrade settlement of ballastless track system based on vehicle dynamic responses and 1D-CNN approach

The millimeter-scale deformation control standards of high-speed railways make the monitoring and identification of subgrade settlement a key technology, especially for ballastless track systems. Addressing the uncoordinated deformation between track and subgrade caused by high track stiffness, this paper proposes an intelligent identification method for subgrade settlement based on vehicle vibration signals and deep-learning technology. Firstly, a high-speed vehicle-ballastless track-subgrade coupled dynamics model considering the track-subgrade nonlinear contact state is utilized, to obtain various vibration responses of the vehicle subsystem due to differential subgrade settlement. After data preprocessing, a multi-channel one-dimensional convolutional neural network (1D-CNN) is established to extract features from the vehicle vertical acceleration dataset and output subgrade settlement status automatically. Finally, the robustness of the model is verified using Gaussian white noise. The research indicates that the vertical accelerations of the car body and bogie frame contain dynamic characteristics caused by medium-long wavelength settlements, while the vertical acceleration of the wheelset is more sensitive to short-wavelength settlements. It is feasible to identify the degree of subgrade settlement using car body, bogie frame and wheelset vertical accelerations as parameterized multi-source input of the 1D-CNN network. The three-channel input model significantly improves the identification accuracy and demonstrates the robustness against noise interference compared to the single-input and dual-input models. This method can effectively enhance the identification capability of ‘concealed’ subgrade settlements in high-speed railways, offering a scientific methodology for status maintenance of ballastless track lines.

Track Irregularity Identification Method of High-Speed Railway Based on CNN-Bi-LSTM.

Track smoothness has become an important factor in the safe operation of high-speed trains. In order to ensure the safety of high-speed operations, studies on track smoothness detection methods are constantly improving. This paper presents a track irregularity identification method based on CNN-Bi-LSTM and predicts track irregularity through car body acceleration detection, which is easy to collect and can be obtained by passenger trains, so the model proposed in this paper provides an idea for the development of track irregularity identification method based on conventional vehicles. The first step is construction of the data set required for model training. The model input is the car body acceleration detection sequence, and the output is the irregularity sequence of the same length. The fluctuation trend of the irregularity data is extracted by the HP filtering (Hodrick Prescott Filter) algorithm as the prediction target. The second is a prediction model based on the CNN-Bi-LSTM network, extracting features from the car body acceleration data and realizing the point-by-point prediction of irregularities. Meanwhile, this paper proposes an exponential weighted mean square error with priority inner fitting (EIF-MSE) as the loss function, improving the accuracy of big value data prediction, and reducing the risk of false alarms. In conclusion, the model is verified based on the simulation data and the real data measured by the high-speed railway comprehensive inspection train.

Dynamic analysis of ultra-low frequency carbody swaying for a high-speed rail vehicle: Causes and measures

This paper investigated on the ultra-low frequency carbody swaying (ULFCS) of a high-speed railway vehicle through field tests and numerical simulations. In the field tests, the vibration characteristics, the dynamics performance, the wheel-rail contact condition, and the track condition were analyzed to realize the manifestation as well as the possible cause of this abnormal vibration. The excessive low equivalent conicity caused by the abnormal wheel tread wear arouse suspicion for this issue. To find out the mechanism and propose the solving measures, the multi-body dynamic (MBD) model of the high-speed vehicle was developed and verified by applying the measured wheel/rail profiles and carbody acceleration. Based on the developed model, the linearized and nonlinear researches were performed. The results indicate that the carbody hunting, caused by the frequency coupling between the hunting mode and the carbody lower sway mode, is the deep reason of the ULFCS, and this issue can be solved by increasing the equivalent conicity and decreasing the roll stiffness of the anti-roll torsion bar. Furthermore, the ULFCS can pose a potential threat to running safety once the violent carbody swaying gives rise to the wheel-rail contact point entering the wheel flange area. Finally, the optimized measures that reducing the hardness of the abrasive block, changing the working mode of the tread cleaning device, and decreasing the anti-roll stiffness were proposed and verified by the on-track test.

Feature analysis of precipitation-induced subgrade defects on a high-speed rail ballasted track using multiple track inspection data: A case study

Heavy rainfall has posed a great challenge to the service performance of high-speed rail (HSR) substructure, resulting in a reduction in the ride quality and safety of high-speed trains. To carry out proper repair work for the substructure, it is imperative to realize efficient identification of precipitation-induced subgrade defects. To this end, this paper aims to extract the features of typical precipitation-induced subgrade defects from the multiple track inspection data to provide a basis for defect identification. Firstly, the geotechnical site investigation including Ground Penetrating Radar (GPR) detection, moisture content test, and dynamic cone penetration (DCP) test of a typical defective spot is performed to determine the condition of the subgrade after heavy rainfall; then, the analysis methods of track inspection data are introduced; finally, the track geometry data and carbody acceleration data of four typical defective sections are analyzed, and the time-domain, frequency-domain and discrete wavelet transform (DWT)-based features which are highly correlated with the precipitation-induced subgrade defects are extracted. The results show that the feature indexes extracted from track surface irregularity and carbody vertical acceleration increase significantly after heavy rainfall; the long wavelength components (8 m and above) of both track irregularity and carbody vibration are more sensitive to the subgrade defects, which is reflected by the sharp increase of the DWT-based features at some levels corresponding to long wavelength ranges. The results of defect feature extraction based on the track inspection data agree well with the geotechnical site investigation results, which demonstrate the feasibility of utilizing multiple track inspection data to identify the typical precipitation-induced subgrade defects.

Disturbance observer-based sliding mode control of active vertical suspension for high-speed rail vehicles

Disturbance observer-based sliding mode control (SMC) on the active vertical suspension (AVS) is developed to suppress the car body’s rigid and flexible vibration to improve ride comfort for a high-speed rail vehicle. A vertical-dynamics-intended vehicle model is foremost built with the bounce, pitch, and bending mode of the car body involved. Two sliding surfaces and disturbance observers are then designed for SMC, which only require the car body states, obviating the bogies’ states. The observer is successful in estimating the effect of unknown track irregularities perturbation as well as externally straightforwardly excitations on the car body with good accuracy. Control efficacy is verified through comparison with passive cases and sky-hook controls. With modal damping below 2% in passive cases, the mode shape function, especially with large displacement at the suspension support, would enlarge the car body acceleration. Moreover, the longitudinal traction rod can significantly multiply the flexible vibration at certain speeds. Comparative studies indicate that SMC provides satisfactory outcomes in the rigid and bending vibration suppression when all the car body’s three modes are considered in the sliding surface. However, it requires a high-frequency response actuator and allows a tighter tolerance of the control time delay than the sky-hook control.

Study on the structural stability of the rail pad and its influence on the dynamic response of the vehicle-track coupled system

This paper investigates the structural stability difference between Grooved Rail Pads (GRP) and Mesh-Type Rail Pad with Damping Blocks (MTRPDB), along with their impact on vehicle-track coupled systems. Firstly, the different loading tests reveal that both Rail Pad (RP) types exhibit increased static/dynamic stiffness when with higher loading. The MTRPDB maintains superior structural stability and vibration absorption under large loading, and the fatigue tests confirm its better fatigue resistance. Then, finite element analysis demonstrates that MTRPDB outperforms GRP with a higher bearing capacity and lower stress level under large loading. Moreover, MTRPDB can better maintain a linear stiffness under identical working conditions. Finally, the dynamic analysis reveals that an increasing number of RP failures negatively impact train safety, and the car body acceleration significantly rises with more RP failures. Furthermore, the MTRPDB exhibits lower dynamic responses compared to GRP across different speed conditions, indicating its superior vibration absorption capacity.

Monitoring and Evaluation of High-Speed Railway Turnout Grinding Effect Based on Field Test and Simulation

Turnouts are the weak spot in high-speed rail systems, and it is simple for the phenomenon of the wheel–rail force and the carbody lateral acceleration over-limit to arise when the train passes through, which affects the service life of the rail and the running stability of the train. In this paper, the turnout with wheel–rail force over-limit and carbody lateral acceleration over-limit is selected for analysis, and the profiles of the wheel and rail are monitored. Then, the vehicle–turnout coupled multi-body dynamics model is simulated. Additionally, the portable vibration analyzer, the comprehensive inspection train, and the wheel–rail contact dynamic stress tester monitors the data and evaluates the impact of rail grinding on high-speed railway. The results of this study demonstrated that the turnout profiles are in good agreement with the standard wheel profiles following grinding, and the wheel–rail contact point and equivalent conicity both improved. When the train passes the ground turnout at high speed with and without the wheel polygonal wear, the wheel–rail force and the carbody acceleration were clearly improved. Using the wheel–rail contact dynamic stress tester, the comprehensive inspection train, and the portable vibration analyzer monitoring the changes in the carbody acceleration, the wheel–rail force and the carbody acceleration are definitely better after grinding. Similar to the pattern in the simulation, the train’s running steadiness increased by grinding.

Rail-structure interaction and vehicle-track-structure interaction level 1 and 2 analyses

Rail-structure interaction (RSI) analysis and vehicle-track-structure-interaction (VTSI) analysis are often required during bridge design. For example, the California High-Speed Train Project requires RSI analysis for final design of all structures, as well as VTSI analysis, with the level of interaction to be modeled determined by the complexity of a structure. The goal of RSI analysis is to ensure that superstructure deformations and rail stresses are within acceptable limits. VTSI analysis is a dynamic analysis that takes into account influence of actual trainsets. VTSI Level 1 analysis includes train loads as a series of moving loads. This analysis allows evaluation of dynamic impact effects from trainsets and vertical accelerations of the deck. For complex high-speed railway bridges, VTSI Level 2 might be required, accounting for full dynamic interaction between the trainset and the bridge. To represent this interaction, the trainset is modeled as a multibody system consisting of rigid bodies, springs, and dashpots. The interaction between wheels and rails is accounted for through kinematic constraints and Lagrange multipliers. This paper presents modeling, RSI, and VTSI analyses of a railway bridge in the LARSA 4D software package. The track and superstructure are modeled in an expedited way using a macro that generates the track, approach, and bridge geometries. Fasteners are modeled as hysteretic springs and automatically positioned along the curved geometry of the track using a LARSA 4D’s bridge path coordinate system definition. RSI analysis is performed accounting for temperature differentials between rails and the deck, vertical train loads, acceleration and braking forces. Break in the rail is introduced using stage construction analysis, followed by progressive collapse analysis (with adapting increments and arc-length control) or nonlinear dynamic analysis. Finally, VTSI Level 1 and 2 analyses are performed and the results are compared. Car body accelerations are compared to limit values to ensure passenger comfort.

Influence of shortwave irregularity on increasing the vehicle running speed on bi-block ballastless track lines

Compared with slab ballastless track, bi-block ballastless track has the advantages of simpler constructed components and better economy, and has been used in high-speed railways for nearly 20,000 km in China. During the construction, the position deviation between sleepers and the disturbance of sleeper position caused by track bed concrete pouring can easily lead to shortwave irregularity with wavelength of 1 ∼ 2 m of bi-block ballastless track. Massive detection data on several high-speed railway lines showed that the standard deviation of vertical wheel-rail contact forces on bi-block ballastless track was about 58% higher than that on slab ballastless track. In this paper, a vehicle-track coupled dynamic analysis model was established, which can consider 1 ∼ 2 m shortwave irregularities of the track. Under the current construction and operation control standards, the dynamic responses of vehicles and tracks under different running speeds were studied. The results showed that vertical shortwave irregularity mainly affected the dynamic response of the wheel and rail, and rarely affected the dynamic response in other components. Compared with no shortwave irregularity, when the track had shortwave irregularity with σv = 0.8 mm, the peak value of the vertical acceleration of wheelset increased by 4.1 times, the standard deviation of wheel-rail contact force increased by 3.9 times, the vertical acceleration of frame increased by 1.7 times, and the vertical acceleration of track bed increased by 1.8 times, while the vibration acceleration of car body had almost no effect. When the track had shortwave irregularity with σh = 0.8 mm, the lateral acceleration of wheelset increased by 2.3 times. When the track had shortwave irregularity with σv = 0.8 mm and the vehicle speed increased to 450 km·h−1, the wheel load reduction rate reached 0.85, which exceeded the safety limit. Consider the results of this study, following suggestions can be obtained:(1) the shortwave irregularity with wavelength of 1 ∼ 2 m can be measured indirectly by the standard deviation of wheel-rail vertical contact force or wheelset vibration acceleration. (2) To control the wheel load reduction rate within 0.6, the standard deviation of random vertical irregularity should be controlled within 0.6 mm when running speed is 350 km/h, and within 0.4 mm when running speed is 400 km/h or above.

Analysis of driving stability and smoothness based on magnetic negative stiffness suspension for cars

Existing economy vehicles mostly use inexpensive passive suspensions, which struggle to fulfil the driving performance needs of people because of their fixed damping stiffness. This paper proposes to build magnetic suspensions by integrating inexpensive negative stiffness magnetic springs and passive suspensions to improve the suspension performance of such cars. Based on the constructed magnetic suspension model, simulations were conducted to investigate and analyse its stability and smoothness in various aspects. Finally, the performance was verified using experiments. The results demonstrate that adding magnetic springs in passive suspensions enables the total stiffness of the suspension to vary adaptively, enhancing the car’s driving stability. Furthermore, it also reduces the car body acceleration, the resonance interval of the suspension system and its displacement transmissibility, further improving the car’s ride smoothness. These performance benefits increase with increasing road excitation, and their role is more pronounced in off-road vehicles. This magnetic suspension system provides novel ideas for the further design of passive suspensions and lays the foundation for the future development of variable stiffness suspensions.

Aerodynamic Interference and Dynamic Influence of Wind Barrier on Train-bridge Coupling Vibration System

Wind barrier is an important wind-resistant measure for the running performance of trains on long-span bridges. This study aims to clarify how the aerodynamic interference of wind barrier to the train-bridge system affects the dynamic response of the system. The aerodynamic interference and dynamic influence of wind barriers on the train-bridge system are studied by wind tunnel test and coupling vibration analysis. Wind barriers with different ventilation rates are selected to study their wind-resistant performance on trains travelling in four lanes on the bridge. The results show that installing wind barriers can increase the side and lift coefficients of bridge and decrease the side and lift coefficients of train. The maximum difference is that installing a wind barrier with ventilation of 0 can increase the side coefficient of the bridge by 0.6, while reducing the side coefficient of train in Lane 1 from 1.25 to −0.25. Although the wind barrier has changed the aerodynamic coefficient of the bridge, the maximum dynamic response of train-bridge system depends more on its influence on the aerodynamic coefficient of train. Installing a wind barrier with 0% ventilation rate can reduce the maximum lateral displacement at mid span of bridge by 10 mm, the maximum reduction rate of the wheel from 0.38 to 0.1, and the lateral car body acceleration from 1.1 m/s2 to 0.45 m/s2. The vertical dynamic response of train-bridge system is insensitive to wind barrier. The key effect of optimizing train side coefficient on wind-resistant performance of wind barrier is pointed out.

Time consideration in machine learning models for train comfort prediction using LSTM networks

Safety and passengers’ comfort affect directly the reliability and availability of trains. Therefore, appropriate monitoring of the variables influencing those two concepts is mandatory for good operation and maintenance costs reduction. Moreover, operators and rail manufacturers are evolving to a condition-based maintenance strategy (CBM). For this purpose, machine learning is being used to predict early main component’s failures, avoiding a loss of reliability or availability during commercial operation. From the passengers’ point of view, punctuality and comfortability are two of the most relevant factors when evaluating a railway transport service. Comfort is mainly based on the availability of all services in the train, but it is also related to the accelerations received through the car body to the passengers. More precisely, the lateral car body acceleration (Ayc variable in this paper) is a key variable related to comfort perception and it is therefore important to be monitored and controlled. Rolling, suspension, and damping elements must be kept in perfect conditions during operation to achieve a smooth train movement. In this paper, an optimized model based on Long Short Term Memory networks (LSTM) is designed and trained to predict lateral car body accelerations using only the train accelerometers and with no additional sensoring for this specific experiment. This model will be compared with artificial neural networks (ANN) models to evaluate the relevance of time dependency for this purpose. The optimal time frame to group data is a key characteristic of the neural network training process and is also determined in this paper. The model is trained with data corresponding to the correct dynamic behavior of the train. To test the reliability of this method, a real case of excessive train movement is tested. In these situations, an alert could be sent to the operator or the maintainer for a not-programmed maintenance inspection at the depot (predictive maintenance), avoiding future passenger complaints for the loss of comfort or, in extreme cases, speed limitations due to safety reasons for excessive accelerations. The main contributions of this work are the following:- A LSTM-based neural network, predicting lateral car body accelerations achieving better results than a plain ANN for this dataset: 0.0335 m/s2 MAE and a 12% gain on extreme axles.- An optimization of the time frame to group the measurements in this algorithm that is considering as an input the time variable: 5 s.- A real use case of the model in which monitoring the deviation would have helped to take an early maintenance adjustment on the suspension or damping elements to prevent the loss of comfort.- The p-value used to reduce the uncertainty of the results obtained in the real use case is reaching over 0.95 in the coaches with good dynamic behavior and less than 0.15 in the coaches where a dynamic problem related to comfort loss is detected.

Influence of suspension schemes on medium-low speed maglev vehicle-guideway dynamic interaction

A comparative study was conducted on Levitation Frame with Mid-set Air Spring (LFMAS) and Levitation Frame with End-set Air Spring (LFEAS). First of all, the work done by air spring force and by track excitation on two levitation frames were analysed, respectively, and the mechanism of the low dynamic interaction of LFMAS with guideway was explained theoretically; then, dynamics simulation and coupled vibration test on LFEAS and LFMAS were carried out using coupled vibration test bench of single levitation frame. Theoretical equations show that both the work done by the air spring forces and by track excitation on LFMAS are less than those on LFEAS under the same vibration condition, demonstrating that LFMAS has better levitation stability than LFEAS. Simulation and test results show that the fluctuation of levitation gap as well as the vibration acceleration of track beam platform, levitation frame and car-body of LFMAS are all smaller than those of LFEAS; with the increase of sine excitation frequency or vehicle speed, the superiority of LFMAS in dynamics performance is more obvious.

Ride analysis of railway vehicle considering rigidity and flexibility of the carbody

ABSTRACT In this paper, a twenty-one degrees of freedom mathematical model of a railway vehicle is formulated, considering its main components (i.e. carbody, bolster, bogie frame, and wheel axle) as rigid for the rigid body analysis of ride behavior of the vehicle. The ride comfort of the vehicle is analyzed and optimized using ISO 2631 criteria. Further, vertical flexibility of the carbody is accounted for with few modifications in the model, and the effect of vertical stiffness on ride behavior is analyzed and compared with a rigid carbody analysis using the Spering ride index. The carbody bending frequencies are investigated using the covariance method, and it is found that the reduction in stiffness of carbody beyond a specific frequency introduces significant carbody acceleration and declines the vehicle ride. The increased carbody bending frequencies can achieve higher vehicle speed and adequate isolation from track excitations.