Research Article | Open Access
Numerical Investigation into the Critical Speed and Frequency of the Hunting Motion in Railway Vehicle System
The critical speed and hunting frequency are two basic research objects of vehicle system dynamics and have a significant influence on the dynamic performance. A lateral dynamic model with 17 degrees of freedom was established in this study to investigate the critical speed and hunting frequency of a high-speed railway vehicle. The nonlinearities of wheel/rail contact geometry, creep forces, and yaw damper were all considered. A heuristic nonlinear creep model was employed to estimate the contact force between the wheel and the rail. The Maxwell model, which covers the influence of the stiffness characteristic, is used to simulate the yaw damper. To reflect the blow-off of the yaw damper, the damping coefficient is described by stages. Based on the mathematical model, the combined effects of vehicle parameters on the critical speed in the straight line and hunting frequency of the wheelset were investigated innovatively. The novel phenomenon that the hunting frequency exhibits a sudden increase from a smaller value to a larger value when the blow-off of the yaw damper occurs was discovered during the calculations. The extents to which various parameters affect the critical speed and hunting frequency are clear on the basis of the numerical results. Moreover, all of the parameter values were divided into three sections to determine the sensitive range for the critical speed and hunting frequency. The results show that the first section of values plays the decisive role on both the critical speed and the hunting frequency for all parameters analyzed. The investigation in this paper enriches the study of hunting stability and gives some ideas to probably solve the abnormal vibrations during the actual operation.
Stability analysis, referred to as one of the classical research areas in vehicle system dynamics, is studied throughout the development of railway vehicles and plays an important role in the development of high-speed trains in China . The primary subject of a stability analysis is hunting motion, which is characterized by self-excited lateral-yaw oscillations . The creep forces and wheel conicity are regarded as the main causes of hunting instability . The hunting motion occurs at a certain speed called the critical speed, which determines the actual operating speed of the railway vehicle. Once the vehicle speed exceeds the critical speed, the vibration amplitude increases with increasing speed and eventually causes a violent lateral swing of the wheelset, which deteriorates the ride comfort, makes the vehicle prone to derailment, damages the track, and induces fatigue failure in the vehicle structure. The hunting motion is therefore the foundation of vehicle system dynamics and has attracted increasing attention from researchers and engineers.
Since Stephenson found the hunting motion phenomenon, researchers have conducted extensive studies on this subject from different aspects . The objects of the study expanded gradually from a single wheelset or bogie to a vehicle and even to an entire train. With the increase in the degrees of freedom, the model became more complex and the factors considered were more comprehensive. Early works generally used linear models which correspond to systems of linear differential equations [5–7]. The critical speed is defined as the lowest speed at which the system characteristic equation has an unstable root, and the influences of different parameters on the hunting stability thus can be analyzed using roots of the characteristic equation. However, with the development of nonlinear dynamics, it was recognized that linear models offer a limited view of vehicle dynamics and cannot describe the entire characteristics of hunting motion. Therefore, the subsequent studies by Law and Brand , Hedrick and Arslan , and many other researchers extended the linear models to include the nonlinear factors of the vehicle systems, such as the wheel/rail contact geometry, creep forces, and suspension elements. The bifurcation theory provides the dynamic behavior of nonlinear systems when the system parameters change and plays an important role in the analysis of nonlinear system. Going beyond the classical linear stability theory, True [10–14] calculated the unknown solution after the bifurcation point and plotted the diagram of subcritical Hopf bifurcation. Subsequently, a group of scientists [15–19] further studied bifurcation by using numerical and analytical methods. They considered nonlinear creep-creep forces as well as nonlinear contact geometry at the wheel/rail interface. Several nonlinear dynamic phenomena, including chaotic motion, were observed in their models and the results demonstrated that the nonlinear elements in railway vehicles significantly affected bifurcation features. However, these studies assumed that suspension elements never left their linear range, and their nonlinearities were not involved in their studies. The yaw damper, which is a hydraulic system connecting the bogie frame with the car body longitudinally, is the most important component to prevent unstable oscillations of high-speed vehicles. Considering the nonlinearity of yaw dampers at the primary suspension, Ahmadian and Yang [20, 21] analyzed Hopf bifurcation in a wheelset and a locomotive bogie. Applying the center manifold theorem and the method of normal form, Yan  presented the influence of the nonlinear yaw damper on the bifurcation type of the bogie. Polach  compared the blow-off forces of a vehicle with yaw dampers and that without a yaw damper and discussed bifurcation characteristics using two bifurcation analysis methods. Uyulan  analyzed and compared the Hopf bifurcation behavior of a two-axle railway bogie and a dual wheelset by considering the nonlinearities of creep forces and yaw damper forces. However, their studies ignored or did not analyze the oil stiffness of the yaw damper, and the stiffness behavior of the yaw damper actually had a considerable influence on the dynamic characteristics of the yaw damper [25–27].
The bogie hunting motion, regarded as a special model in the vehicle system, has a significant influence on the vehicle stability. The damping ratio of this model largely determines whether the hunting motion converges to the equilibrium or diverges to a stable limit cycle. In addition to the damping ratio, the frequency of the hunting motion should also be given enough attention, as it could affect the abnormal vibration of the vehicle on many situations. Both car body hunting  and car body shaking , observed in daily operation in China, are relevant to the hunting frequency. Furthermore, the traditional formula of the hunting wavelength derived by Klingle  is no longer suitable for the analysis of high-speed vehicles. Apart from the equivalent conicity, many other parameters in the vehicle also have large influence on the hunting frequency. The nonlinearities of the wheel/rail contact geometry, creep forces, and suspension elements are also needed to be taken into consideration during the calculation of hunting frequency. However, the corresponding study on the hunting frequency is rare at present.
In this paper, a lateral dynamic model of the high-speed vehicle was established, and the nonlinearities of wheel/rail contact geometry, creep forces, and yaw damper forces were taken into consideration. The parameters involved in the nonlinear wheel/rail contact relationship were attained using polynomial interpolation. The nonlinear relationship between creepage and creep force based on a heuristic nonlinear creep model was employed for estimating the contact forces between the wheel and the rail. To integrate the stiffness behavior, the yaw damper was modeled as a Maxwell element, whose damping coefficient is described by stages. The influences of the vehicle parameters on the critical speed and hunting frequency were studied together. The ranges of the parameters studied were divided into three sections and the influence proportion of each section was subsequently compared.
2. Mathematical Model of a High-Speed Railway Vehicle
2.1. Description of the System
Figure 1 shows a typical high-speed vehicle schematic: (a) denotes the top view and (b) denotes the front view. The vehicle is modeled as a four-axle mass-spring-damping multi-rigid-body system including a car body, two bogie frames, four wheelsets, and two-stage suspensions. The wheelsets have 2 DOFs, including motions of traverse y and yaw φ. The bogie frames and the car body both have 3 DOFs, including motions of traverse y, yaw φ, and roll Φ, with respect to their mass centroids. Therefore, the vehicle system has 17 DOFs. The vehicle proceeds at a constant speed v on a straight track.
The subscripts c, t, and w represent the car body, bogie frame, and wheelset, respectively, and the subscripts p and s denote the primary and secondary suspensions, respectively. It should be noted that physical quantities, such as , , , , etc., are defined in the nomenclature displayed in the Appendix.
This study used the common way of representing a yaw damper: a linear spring in series with a viscous damper. Cd denotes the damping generated as a result of the resistance of the fluid passing through the various damping valves, and Kd denotes the series stiffness representing an elastic characteristic which includes the flexibility related to the connection joints of the damper and oil compressibility.
It is convenient to derive the equations of motion for the lateral dynamic vehicle system by applying the d’ Alembert-Lagrange principle.
2.2. Governing Equations of Motion
The governing equations of motion for the lateral displacement yc, yaw angle φc, and roll angle Φc of the car body are given, respectively, by the following:Note that subscripts 1 and 2 in Equations (1)–(3) indicate that the corresponding physical properties relate to the front and rear bogie frames, respectively. Furthermore, the double dots above the quantities on the left-hand side of Equations (1)–(3) denote differentiation with respect to the time variable t.
As shown in Figure 1, the suspension forces acting on the car body in the lateral direction, Fsy1 and Fsy2, the suspension moments acting on the car body in the vertical direction, Msz1 and Msz2, and the suspension moments acting on the car body in the longitudinal direction, Msx1, Msx2, Msy1, Msy2, and Mgc, are given bywhere Fd1 and Fd2 are the damping forces produced by the yaw dampers of the front and rear bogie frames, and they will be listed in the next section. Consider
The governing equations of motion for the lateral displacement yti, yaw angle φti, and roll angle Φti of the bogie frames are given, respectively, byNote that subscripts in Equations (13)–(15) indicate the corresponding physical properties related to the front and rear bogie frame, and the subscripts 1 and 2 denote the corresponding properties related to the front and rear wheelset in a bogie.
Meanwhile, with respect to the bogie frames, the suspension forces acting in the lateral direction, Fpy1 and Fpy2, the suspension moments acting in the vertical direction, Mpz1 and Mpz2, the suspension moments acting in the longitudinal direction, Mpxi, Msi, and Mgti, are given by
The governing equations of motion for the lateral displacement and yaw angle of the wheelsets are given, respectively, bywhere subscripts in Equations (23) and (24) are defined as above, and subscripts j=1, 2 denote the corresponding physical properties related to the front and rear wheelset. The nonlinear terms, the lateral creep force Fryij, the gravity restoring force Fgij, the moment in the vertical direction produced by the longitudinal creep force and spin moment Mrzij, and the moment in the vertical direction produced by the gravity restoring force Mgijare listed below.
2.3. Nonlinear Terms
2.3.1. Nonlinearity of Creep Force
A single wheelset model consisting of 2 DOFs is established, and the front view of the wheelset is depicted in Figure 2. In the figure, a denotes half of the rolling cycle gauge; v is the forward speed of the wheelset; and rL and rR denote the radius of the left and right wheels at the contact points on the rail, respectively. The creepages of the left and right wheels in the longitudinal, lateral, and spin directions of the contact plane can be derived as follows:where Ω is the rolling angular velocity of the wheelset relative to its own axle; the subscripts L and R represent the left and right wheels, respectively, while the subscripts t, a, and s represent the longitudinal and lateral directions, respectively.
By using Kalker’s linear creep theory , the longitudinal creep force, lateral creep force, and spin creep moment can be written in the following forms:where , and are the creep coefficients and can be calculated referring to Shabana et al.  Note that subscripts , R in Equation (26) indicate the corresponding physical properties related to the left and right wheels. A heuristic nonlinear creep model  that combines Kalker’s linear creep theory with a creep force saturation representation is used for computing creep force. The creep forces at each wheel are given bywhere the saturation constant α is given bywhere , μ is the wheel/rail friction coefficient, and N is the normal force to the contact plane. The contact plane creep forces and moment are then transformed to the wheelset coordinates by
The forces and moments acting on the track coordinates can be obtained as follows:corresponding to each wheelset as
2.3.2. Nonlinearity of Wheel/Rail Contact
With respect to the rolling radii rL and rR and the contact angles δL and δR, they can be taken from tables as functions of excursion y . However, the cost of computation is high when using this method. Function fitting is a good alternative and has been adopted by some authors [18, 22]. The relationship between the equivalent radius of the wheel and the lateral displacement is given bywhere r0 is the distance between the contact point and the center of the wheel without displacement, λ1 is the linear gradient on the conical tread, and is the nonlinear correction factors of the geometry relationship between the wheel and the rail.
The relationship between the contact angles and the lateral displacement is given by
One more prerequisite mentioned in  has also been applied in this study as
The sine and cosine functions are expanded in the Taylor series, and only the first two terms are considered and all higher order derivatives are ignored. Similarly, the tangent function in the Taylor series is expanded to the first two terms in the calculation of Mg.
The wheel profile type of S1002CN and rail profile type of UIC60 are selected in this study, and the parameters of and are selected from the results in Yan and Zeng . Based on the relationship between the lateral displacement y and the contact angles δL or δR, the values of d0=0.0544, d1=-9.45, d4=3.8e7, and d5=-3.58e9 can be obtained using fifth-order polynomial interpolation. A comparison between the real data and the result of polynomial interpolation is given in Figure 3.
2.3.3. Nonlinearity of Damping Force
The yaw damper considered here is modeled as a Maxwell element, which is used as a part model introduced in Pracny et al.  and can describe the effects of hysteresis in a given frequency range. As mentioned previously, it is based on a linear spring and a viscous damper connected in series, as shown in Figure 4(a), where Fd denotes the damping force, x denotes the total displacement, and xd denotes the displacement of the damper. To consider the curve negotiating property of the vehicle and protect the damper, a yaw damper possessing the blow-off characteristic is applied, and the damping can be described by stages, as shown in Figure 4(b), where is the first stage damping before blow-off, is the second stage damping after blow-off, vu is the blow-off velocity, and Fu is the blow-off force.
The relationship for the spring force can be written as follows:As the damper is assumed to be nonlinear, the rate of this displacement is given byDifferentiating Equation (35) with respect to time and replacing the damper velocity with Equation (36), we obtain the following differential equation:which can be integrated in closed form. The analytical solution corresponding to the for is given by Equation (38) shows that the current force is a function of the entire time history of the excitation between and the actual time . Thus, replacing the integral with the sum and discretization of the time and , we obtain
3. Numerical Analysis of the Critical Speed and Hunting Frequency of the Vehicle System
3.1. Hopf Bifurcation Characteristics
A bifurcation diagram is a powerful tool for analyzing railway nonlinear dynamics. The railway system expresses the typical Hopf bifurcation, whose diagram is illustrated in Figure 5 . In Figure 5, the abscissa represents the vehicle speed while the ordinate represents the amplitude of the limit cycle. The solid and dashed lines denote the stable and unstable limit cycles, respectively. Point A is the Hopf bifurcation point, and the corresponding speed Vlin at point A is defined as the linear critical speed of railway vehicles. Point B is the turning point from a stable equilibrium point to a periodic solution, and the corresponding speed at point is defined as the nonlinear critical speed of railway vehicles.
For the subcritical Hopf bifurcation, system vibration will result in a stable equilibrium position for any external excitations when the vehicle speed V is less than Vnl. When V is larger than Vlin, the system will exhibit a stable periodic motion with a large amplitude regardless of the amplitude of the disturbance. In the interval Vnl < V < Vlin, however, the vibration of the system depends on the amplitude of the external excitation, and the interval is an uncertain region. For the supercritical Hopf bifurcation (b), the system always exhibits a stable periodic motion when V achieves the linear critical speed Vlin. With the increase in V, the amplitude of the hunting motion increases gradually. The supercritical Hopf bifurcation (a) has both subcritical Hopf bifurcation and the supercritical Hopf bifurcation characteristics. The uncertain region of V extends to Vnl ~ Vc, in which the solution will converge to equilibrium or a limit cycle with a small amplitude at a small track excitation and diverge to a limit cycle with a large amplitude at a large track excitation. The bifurcation diagram can be calculated using a path following method or a set of numerical simulations [36–38]. The path following method is used in this paper.
3.2. Critical Hunting Speed
To investigate the stability of a railway vehicle system in practical engineering, the nonlinear critical hunting speed Vnl is generally considered. From a mechanical viewpoint, a system can be regarded as stable if the oscillation of the system decays after a discontinuation excitation. Increasing the vehicle speed slowly, when the system displays a periodic motion at a constant amplitude, the corresponding speed can be regarded as the critical speed Vcr, namely, Vnl. The lateral displacement of the front wheelset is used as the output value to judge the critical speed in this study. With respect to excitations, three types of excitations are applied widely to railway vehicle system , and type (b) is chosen to calculate the critical speed here:(a)No excitation, running on an ideal track, starting from the limit cycle, and reducing the speed until a stable wheelset motion is achieved(b)Excitation by a singular irregularity, followed by an ideal track (or with a short irregularity sequence followed by an ideal track), with or without variation in the excitation amplitude(c)Excitation by a stochastic (measured) track irregularity, and applying the criteria used during the vehicle acceptance test.
3.3. Hunting Frequency
The hunting frequency of the wheelset is an important factor in a vehicle dynamic system, whose value can significantly affect the occurrences of car body hunting and car body shaking phenomena. According to the Klingel theory , there is a direct relationship between the hunting frequency of the wheelset and the forward speed, as well as with the equivalent conicity of the wheel tread for a simple wheelset with coned wheels. The author’s model is completely different and complex, and the influences of other components and nonlinearities on the hunting frequency of the wheelset are worth investigating.
In this study, the calculation of hunting frequency is divided into two parts. When the vehicle speed is less than Vcr, the system vibration will result in a stable equilibrium position and the nonlinearities will have no influences on hunting frequency. For a linear system, the hunting frequency can be determined using the roots of the characteristic equation, whose imaginary part is the angular frequency of the wheelset hunting motion. When the vehicle speed exceeds Vcr, the system vibration will diverge to a limit cycle with a large amplitude and the nonlinearities of the system should be taken into consideration. In this way, a numerical method based on the characteristics of time histories of vehicle components is proposed to calculate the hunting frequency of the wheelset.
The nonlinear governing equations of motion of the vehicle can be solved using the fourth-order Runge–Kutta method. The linear interpolation is subsequently used to change the variable step time series into a fixed step. The wheelset motion signals are collected over a finite time Tc and consist of a discrete number of points obtained at a selected sampling frequency. The data can then be modeled as a sum of the sine and cosine functions of time t with the period being an integer submultiple of Tc. The fast Fourier transform (FFT) is then used to calculate the frequency spectrum, and the hunting frequency can thus be obtained by selecting the main frequency in the spectrum. During the calculation of hunting frequency, the track irregularity is removed and the wheelset is set to an initial displacement.
4. Results and Discussion
Simulation studies of self-excitation vibrations and stability of the nonlinear vehicle model were carried out based on the fourth-order Runge–Kutta method . The results for the lateral displacement of the wheelset in this study are based on the first bogie leading wheelset.
To determine the critical speed, the Dichotomy method was applied to the simulation. The simulation was started with a speed of 300 km/h, and the speed was increased or decreased in intervals of 10 km/h to determine another boundary of the interval. The calculation precision was 1 km/h, and the time series of the lateral displacement and the state-space plot of the wheelset lateral shift velocity versus displacement were determined. In the state-space plot, the data of the initial 3 s are removed. The results obtained for the last two speeds are shown in Figure 6. It can be seen that once the vehicle speed is less than 322 km/h, for instance, 321 km/h, the lateral displacements of the vehicle components tend toward the equilibrium point after the track irregularities disappear. When the vehicle speed reaches 322 km/h, the lateral displacements of the vehicle components diverge to a stable limit cycle and a sustained lateral hunting motion occurs. Therefore, it can be concluded that the critical hunting speed of this vehicle is 321 km/h.
The bifurcation diagram of this vehicle is shown in Figure 7(a). It is a typical supercritical Hopf bifurcation of type (a), and the linear critical speed is 440 km/h while the nonlinear critical speed is 321 km/h. Point P is on the unstable limit cycle with an amplitude of 3 mm, and the corresponding speed is 375 km/h. It means that, under the initial excitation of 3 mm, when the vehicle speed is less than 375 km/h the solution will converge to equilibrium, and when the vehicle speed is greater than 375 km/h the solution will diverge to a limit cycle.
Figure 7(b) presents the variation in the hunting frequency of the wheelset with increasing vehicle speed. The initial wheelset amplitude is 3 mm. It is understandable that the hunting frequency increases with the increase in speed. However, there is a jump from point Q1 to point Q2 at 375 km/h which just corresponds to point P in Figure 7(a). That is to say, the hunting frequency exhibits a sudden change when the solution of the movement changes from equilibrium to the limit cycle. It is partly caused by the discontinuity of the damping coefficient of the yaw damper, and the evidence can be seen in Figure 8, which shows the time histories of the wheelset displacement and yaw damper velocity vd. The red line represents the blow-off velocity of the yaw damper. It can be seen that, when vd is lower than the blow-off velocity, the cycle of the wheelset displacement is 0.25 s, namely, a frequency of 4 Hz. When vd is greater than the blow-off velocity, the cycle of the wheelset displacement is 0.19 s, namely, a frequency of 5.3 Hz. The influence of the damping coefficient on the hunting frequency needs to be explained, and it is described below. Thus, it can be concluded that the hunting frequency exhibits a sudden increase once the blow-off of the yaw damper occurs, and the hunting frequency can be divided into two parts: before blow-off and after blow-off.
To illustrate the consequences of this phenomenon, the time-frequency analysis for a section of the measured accelerations on the car body floor is given in Figure 9(a). It can be seen that the car body acceleration around 10 Hz exists for almost the whole-time history, which corresponds to the elastic mode of the car body, while the acceleration around 1 Hz is caused by the rigid mode of the car body. The car body acceleration during the period of 39220–39240 s, whose frequency is around 10Hz, is significantly larger than other sections. It is a typical phenomenon of car body shaking , and the local enlargement of the acceleration in the resonance section is shown in Figure 9(b). It can be seen that there exists a harmonic vibration in the resonance section, and the acceleration amplitude increases dramatically. In general, the hunting frequency of the bogie can hardly reach 10 Hz, only if the yaw damper blows off and a large jump occurs in the hunting frequency. The situation outlined above exists in daily operation when the equivalent conicity reaches a high level and the vehicle loses stability.
Predictably, the choice of key parameters largely determines the critical speed of the vehicle. Furthermore, the resonance problem such as those pertaining to the hunting and shaking of the car body, which are closely related to the hunting frequency, should be focused on during the design of the vehicle. For this reason, the combined effects of key parameters in the vehicle system on critical speed and hunting frequency are analyzed immediately. These parameters include the first stage damping , the second stage damping , the series stiffness of the yaw damper Kd, the coefficient of friction u, longitudinal stiffness of primary suspension Kpx, creep force coefficients f11 and f22, and the lateral damping of secondary suspension Csy.
Figure 10 shows the influences of yaw damper parameters on the critical speed and hunting frequency. During the calculation of hunting frequency, the vehicle speed is taken as 300 km/h. In the figures, the black solid line represents the critical speed Vcr, the blue solid line represents the hunting frequency f, and the blue dash line represents the jump of the hunting frequency. Figure 10(a) depicts the results of . It can be seen that Vcr increases logarithmically with the increase in and finally stabilizes at 330 km/h. The f exhibits a sudden change at the value of 140 kN·s/m where Vcr reaches 300 km/h. Before that, f maintains a constant value, and once exceeds 140 kN·s/m, f decreases with the increase in . We can thus draw the conclusion that only affects the hunting frequency before blow-off of the yaw damper. Figure 10(b) illustrates the results of . It can be seen that Vcr virtually increases linearly in two parts with the increase in . The dividing point of these two parts is located at the value of 15 kN·s/m. Similar to , f also exhibits a sudden change at the value of 15 kN·s/m where Vcr reaches 300 km/h. The difference is that f decreases with the increase in before the sudden change, and, once exceeds 15 kN·s/m, f maintains a constant value. It indicates that only affects the hunting frequency after blow-off of the yaw damper. Furthermore, it can be seen from Figure 10(c) that Vcr firstly increases with increasing Kdand then decreases and finally tends to a stable value. The f decreases with the increase in Kd overall, and the jump of f also exists at the critical speed of 300 km/h.
Figure 11 shows the change of Vcr and f with the increase of u, f11, Kpx, and Csy. During the calculation of f, the vehicle speed is taken as 350 km/h. The lateral creep force coefficient f22 is set equal to f11. They both affect Vcr and f by changing the creep forces. The Vcr decreases with the increase in u, as shown in Figure 11(a). In addition, f increases with the increase in u when Vcr is less than 350 km/h, and f maintains a constant value when Vcr is larger than 350 km/h. It indicates that u affects the hunting frequency only if the vehicle loses stability. Figure 11(b) shows the results of f11 (f22), and it can be seen that, with the increasing of f11 (f22), Vcr decreases gradually, f increases overall, and the jump of f exists at the critical speed of 350 km/h. Apart from the yaw damper parameters, Kpx and Csy are another two important parameters in the vehicle suspension system.
Figure 11(c) illustrates the influence of Kpx on Vcr and f. The results show that Vcr increases logarithmically with the increase in Kpx and finally stabilizes at 322 km/h. The f decreases gradually with the increase in Kpx and finally stabilizes at 4.9 Hz. As for Csy, the influences on both Vcr and f are coincident with the results of Kpx in the trend, as shown in Figure 11(d).
To further compare the influence of the same parameter whose value is taken in different sections on the critical speed and hunting frequency, the parameters analyzed above were divided into three sections, as shown in Table 1. Within the range of parameters, the change of critical speed is defined as , while the change of hunting frequency is defined as . The comparison results of different parameters and different sections with regard to are shown in Figure 12(a). It can be seen that parameters of u, , , f11, and have a significant influence on the critical speed. Within the range of these parameters, all exceed 100 km/h. The parameters of Kpx and Csy, by contrast, have less influence on the critical speed, and are within 50 km/h. As for the proportion of each section, the first section plays a decisive role in Cd1, u, Kpx, and Csy. The first section is close to the second section in f11, and the third section accounts for a small proportion in all parameters. Figure 12(b) indicates the results of Δf, and the influence of frequency jump is removed during the calculation. It can be seen that the parameters of u and process the greatest impact on the hunting frequency, and the parameters of , Kd, and f11 come next. However, it is worth noting that the parameters of u and Cd2 only work when the vehicle loses stability, and parameters of only work when the vehicle does not lose stability. The parameters of Kpx and Csy, by contrast, have less influence on the hunting frequency, and Δf are within 0.8 Hz. As for the proportion of each section, all of the parameters show the same regularity; that is, the first section comes first, the second section comes next, and the third section is the least.
The parameters analyzed in the previous section significantly influence Vcr without changing the bifurcation type. However, the blow-off force Fu affects not only Vcr but also the bifurcation type, as shown in Figure 13. With the increase in Fu, the type of Hopf bifurcation transforms from subcritical to supercritical Hopf bifurcation of type (a), and, when Fu tends to infinity, namely, with a linear damping coefficient, the bifurcation type transforms to supercritical Hopf bifurcation of type (b). Furthermore, Fu does not affect the linear critical speed, which is decided by , and increasing Fu can increase Vcr until the system reaches the linear critical speed.
In this study, the lateral dynamic model of a vehicle with 17 degrees of freedom was established, and the nonlinearities of wheel/rail contact geometry, creep forces, and yaw damper were considered. The wheel profile type of S1002CN and the rail profile type of UIC 60 were selected, and the bifurcation type was supercritical Hopf bifurcation of type (a). In addition to the critical speed, the hunting frequency of the wheelset was considered together during the calculation. The following conclusions can be drawn:(1)Owing to the discontinuity of the damping coefficient of the yaw damper, the hunting frequency of the wheelset increases suddenly when blow-off of the yaw damper occurs.(2)Parameters u, , and Kd have the greatest influence on the critical speed, followed by parameters and f11, and parameters Kpx and Csy have the least influence. Parameters u and have a significant influence on the hunting frequency; however, they only work when the vehicle loses stability. Conversely, only affects the hunting frequency when the vehicle does not lose stability.(3)As for the influence proportion of each section on the critical speed and hunting frequency, all of the parameters analyzed show the same regularity that the first section comes first, the second section comes next, and the third section is the least.(4) Fu affects not only the critical speed but also the bifurcation type. With the increase in the blow-off force, the Hopf bifurcation transforms from subcritical to supercritical of type (a), and then to supercritical of type (b).
It is noted that the results presented herein are based on calculation performed considering the straight line, and further research regarding the influence of vehicle parameters on the stability when a vehicle traverses a curve is needed. This will be a topic in our future work.
See Table 2.
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
This research has been supported by the National Science Foundation for Young Scholars (Grant no. 51805450), by the Joint Key Fund Projects (Grant no. U1734201), and by the Independent Subject of State Key Laboratory of Traction Power (Grant no. 2018TPL_T04). The authors wish to express their many thanks to the reviewers and editors of the present paper, whose help was invaluable in revising and improving the English language in this paper.
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