A coordinated control method for wheel-rail adhesion of overloaded group trains

Abstract

The present invention belongs to the field of rail transit control, and proposes a coordinated control method for wheel-rail adhesion of heavy-haul grouped trains, including: respectively establishing a dynamic model of a heavy-haul double-unit grouped train, a rail surface recognition model, a wheel-rail adhesion control model, and a grouped train operation control model; inputting the equivalent braking force or traction force of the wheel and the wheel-rail normal force into the rail surface recognition model to calculate an estimated value of the adhesion coefficient, and inputting it into the grouped train operation control model; inputting the estimated value of the adhesion coefficient, the vehicle speed, time, wheel angular velocity of the leading train, the vehicle speed, time, and wheel angular velocity of the following train into the wheel-rail adhesion control model to calculate the motor torques of the leading train and the following train and the output logic determination value of the following train, and inputting them into the grouped train operation control model. After adjustment control, the motor torques of the adjusted leading train and following train are obtained; inputting the motor torques of the adjusted leading train and following train into the dynamic model of the heavy-haul double-unit grouped train.

Description

Technical Field

[0001] The present invention relates to the technical field of rail transit control, and particularly relates to a method for collaborative control of wheel-rail adhesion of heavy-haul group trains. Background Art

[0002] With the continuous development of heavy-haul railways in China, the problems of safe operation control, improvement of transport efficiency, and alleviation of transport capacity bottlenecks of heavy-haul trains have become increasingly prominent. The group operation control technology of heavy-haul trains breaks the traditional long formation mode, realizes the "virtual coupling" between train groups with a smaller safe tracking distance through vehicle-to-vehicle and vehicle-to-ground-to-vehicle communication, adopts moving block with the MB-V mode, increases the operation density of heavy-haul freight trains, and improves the transport capacity of the heavy-haul railway freight system. However, the traditional signal system and adhesion control strategy are difficult to support high-precision operation control under group operation conditions. Therefore, the wheel-rail adhesion control method under the group operation mode needs to be further improved. Accurate and efficient adhesion control methods are required for rapid and accurate identification of wheel spin / slide and calculation of the safe tracking distance of trains under the conditions of spin / slide and traction / braking, so as to ensure the safe operation of heavy-haul trains. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for collaborative control of wheel-rail adhesion of heavy-haul group trains, which combines group operation control with the longitudinal dynamic safety performance of trains and the wheel-rail adhesion control strategy on the basis of traditional re-adhesion control, so as to ensure the smooth running of trains under different sections and different environmental conditions. At the same time, from the perspectives of dynamics and adhesion control, a safe train tracking distance is provided for group operation trains, and the wheel-rail adhesion control effect of locomotives is improved.

[0004] The technical solution adopted by the present invention to solve its technical problems is as follows:

[0005] A method for collaborative control of wheel-rail adhesion of heavy-haul group trains includes the following steps:

[0006] Respectively establish a dynamic model of a double-formation heavy-haul group train, a rail surface recognition model, a wheel-rail adhesion control model, and a group operation control model;

[0007] The double-formation group train in the dynamic model of the double-formation heavy-haul group train includes a leading train and a following train, and a train tracking distance between the leading train and the following train is set, and the equivalent braking force or traction force of the wheel, the wheel-rail normal force, the speed of the leading train, the time of the leading train, the angular velocity of the leading train's wheel pair, the speed of the following train, the time of the following train, and the angular velocity of the following train's wheel pair are obtained;

[0008] Input the equivalent braking force or traction force of the wheel and the wheel-rail normal force into the rail surface recognition model to calculate the estimated value of the adhesion coefficient;

[0009] Input the estimated value of the adhesion coefficient, the speed of the leading train, the time of the leading train, the angular velocity of the leading train's wheel pair, the speed of the following train, the time of the following train, and the angular velocity of the following train's wheel pair into the wheel-rail adhesion control model to calculate the motor torque of the leading train, the motor torque of the following train, and the output logic determination value of the following train;

[0010] Input the speed of the leading train, the speed of the following train, the motor torque of the leading train, the motor torque of the following train, and the output logic determination value of the following train into the group operation control model. After adjustment and control, obtain the motor torque of the leading train and the motor torque of the following train after adjustment and control;

[0011] Input the motor torque of the leading train and the motor torque of the following train after adjustment and control into the heavy-haul double-unit group train dynamics model.

[0012] As a further optimization, establish a heavy-haul double-unit group train dynamics model based on the SIMPACK platform.

[0013] As a further optimization, the establishment of the heavy-haul double-unit group train dynamics model based on the SIMPACK platform includes:

[0014] Establish a leading train dynamics model;

[0015] Establish a following train dynamics model with the same formation as the leading train;

[0016] Set the train tracking distance, the initial train speed, and the rail surface conditions.

[0017] As a further optimization, the rail surface identification model is a rail surface adhesion coefficient identification model based on a disturbance observer established in MATLAB;

[0018] In the rail surface adhesion coefficient identification model based on a disturbance observer, use the disturbance observer to estimate the wheel-rail adhesion force F adh in real time, that is, calculate the estimated value of the adhesion coefficient.

[0019] As a further optimization, the calculation of the estimated value of the adhesion coefficient includes:

[0020] Calculate the wheel-rail normal force according to the axle load of the locomotive N ;

[0021] Establish a locomotive wheel pair dynamics equation, perform Laplace transform, then use first-order low-pass filtering for processing, and then perform inverse Laplace transform to obtain the estimated value of the adhesion coefficient μ as:

[0022] ,

[0023] Wherein, ω is the rotational angular velocity of the wheel set, J w is the moment of inertia of the wheel set, R w is the rolling circle radius of the wheel, F B / T is the equivalent braking force / tractive force at the rolling circle radius of the wheel, p is the Laplace operator, λ is the cut-off frequency.

[0024] As a further optimization, in the wheel-rail adhesion control model, the adhesion control model of the leading train uses the longitudinal creep ratio of the wheel set as the anti-skid criterion, and the torque is controlled by PID; the adhesion control model of the following train uses the longitudinal creep ratio of the wheel set, the wheel-rail adhesion coefficient, the train tracking distance and the relative speed difference of the train as the combined criterion, and the torque is controlled and adjusted by the re-adhesion control strategy.

[0025] As a further optimization, in the adhesion control process of the leading train, the longitudinal creep ratio of the wheel set is used as the anti-skid criterion for determination;

[0026] When the difference between the longitudinal creep ratio c of the wheel set and the given first threshold e Lc1 < 0, it is determined as the skidding out-of-control state, and enters the torque reduction stage. Record the initial torque T 0 of the motor, and use PID control to reduce the torque. Calculate the torque change Δ T L1 , and output the motor torque T Lt = T L0 - Δ T L1 , then enter the torque holding stage, keep the torque unchanged for a period of time, and then enter the torque recovery stage. Use PID control to reduce the torque, calculate the torque change Δ T L2 , and output the motor torque T Lt = T 0 + Δ T L2 . Finally, use the second threshold for determination. When the difference e Lc2 > 0, the torque recovers to the initial state, and the adhesion control is completed;

[0027] The expression of the PID torque control for reducing the torque by using PID control is:

[0028] ,

[0029] The difference between the longitudinal creep ratio of the wheel set and the given threshold value e Lci The expression is as follows:

[0030] ,

[0031] In the formula, P, I, D are the proportional coefficient, integral coefficient, and differential coefficient of the controller respectively, t is the torque adjustment time, c Lref is the longitudinal creep ratio threshold of the wheel set, t 1 is the trigger time, t 2 is the end time.

[0032] As a further optimization, in the adhesion control process of the following train, the wheel-rail adhesion coefficient and the longitudinal creep ratio of the wheel set are used as a combined anti-skid criterion. At the same time, the train tracking distance and the relative speed difference of the train are input as boundary conditions. Within the allowable range of error, the train tracking distance is ensured to be constant, and the relative speed difference of the train is made close to zero;

[0033] The change amount of the torque is controlled by an adjustment method with a fixed slope, and the adhesion control output logic determination value Log of the following train is obtained.

[0034] As a further optimization, the group operation control model includes a train time-speed-position model and a train cooperative control model;

[0035] The train time-speed-position model is provided by the heavy-haul train ATP system. The corresponding track model and train running speed are directly set in the heavy-haul double-unit group train dynamics model, and the train running time, distance, and speed are output in real time. The train cooperative control model is established by using the PID speed coordination algorithm and the constant time interval control strategy, and the vehicle speed difference and the train tracking distance are controlled by PID.

[0036] As a further optimization, the group operation control model takes the real-time speeds of the leading train and the following train v 1 , v 2 as inputs, and through PID adjustment, the output torque Δ T PID ;

[0037] Under the skidding condition, considering the mutual coupling influence of the group operation control and the adhesion control, the group operation control model and the wheel-rail adhesion control model are adjusted and controlled, and the conversion is carried out through the "0" and "1" switches. The output logic determination value is defined as "Log =e c >0&& x > x max ||Δ v > v 0 ”, that is, when Log = 1, it indicates no adhesion control. At this time, the train tracking distance exceeds the maximum limit or the relative speed difference between trains exceeds the maximum limit, and the group operation control model is turned on. The final output torque is T FS / LS =T F / L +Δ T PID When Log = 0, wheel slip occurs at this time. The group operation control model is turned off, and the wheel-rail adhesion control model is turned on for torque adjustment. The output torque is T FS / LS =T F / L The torque magnitude is only determined by the adhesion control.

[0038] The beneficial effects of the present invention are as follows: Through the above-mentioned wheel-rail adhesion collaborative control method for heavy-haul group trains, the dynamic model, rail surface recognition model, wheel-rail adhesion control model, and group operation control model of heavy-haul double-unit group trains can be coupled with each other for joint simulation, combining group operation control with the longitudinal dynamic safety performance of trains and wheel-rail adhesion control strategies. On the one hand, it provides a safe train tracking distance for group operation trains, and on the other hand, it can also improve the wheel-rail adhesion control effect of locomotive wheels. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the data processing flow of each model of a wheel-rail adhesion collaborative control method for a heavy-haul group train in Embodiment 1 of the present invention;

[0040] Figure 2 It is a simulation diagram of optimized wheel-rail adhesion control under the group operation of a heavy-haul train in Embodiment 1 of the present invention;

[0041] Figure 3 It is a system dynamic model diagram of a group train in Embodiment 1 of the present invention;

[0042] Figure 4 It is a wheel-rail adhesion control diagram of a leading train and a following train in Embodiment 1 of the present invention;

[0043] Figure 5 It is a group operation control model diagram in Embodiment 1 of the present invention;

[0044] Figure 6 It is the longitudinal creep rate and angular acceleration of the wheelset of a leading train and a following train in Embodiment 2 of the present invention;

[0045] Figure 7Adhesion coefficients and motor torques of the leading train and the following train in Embodiment 2 of the present invention

[0046] Figure 8 Vehicle speeds and relative speed differences of the leading train and the following train in Embodiment 2 of the present invention

[0047] Figure 9 Running distances and tracking intervals of the leading train and the following train in Embodiment 2 of the present invention Detailed implementation manners

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations. Embodiment 1

[0049] Refer to Figure 1 and Figure 2 This embodiment provides a wheel-rail adhesion collaborative control method for a heavy-haul group train, including the following steps:

[0050] S1. Respectively establish a heavy-haul double-unit group train dynamics model, a rail surface recognition model, a wheel-rail adhesion control model, and a group operation control model;

[0051] S2. The double-unit group train in the heavy-haul double-unit group train dynamics model includes a leading train and a following train, and a train tracking distance between the leading train and the following train is set, and the equivalent braking force or traction force of the wheels, the wheel-rail normal force, the speed of the leading train, the time of the leading train, the angular velocity of the leading train's wheel pair, the speed of the following train, the time of the following train, and the angular velocity of the following train's wheel pair are obtained;

[0052] S3. Input the equivalent braking force or traction force of the wheels and the wheel-rail normal force into the rail surface recognition model to calculate an estimated value of the adhesion coefficient;

[0053] S4. Input the estimated value of the adhesion coefficient, the speed of the leading train, the time of the leading train, the angular velocity of the leading train's wheel pair, the speed of the following train, the time of the following train, and the angular velocity of the following train's wheel pair into the wheel-rail adhesion control model to calculate the motor torque of the leading train, the motor torque of the following train, and the output logic determination value of the following train;

[0054] S5. Input the speed of the leading train, the speed of the following train, the motor torque of the leading train, the motor torque of the following train, and the output logic determination value of the following train into the group operation control model. After adjustment and control, obtain the motor torque of the adjusted leading train and the motor torque of the following train.

[0055] S6. Input the motor torque of the adjusted leading train and the motor torque of the following train into the heavy-haul double-unit group train dynamics model. When wheel slippage occurs, after multiple adjustments by multiple systems, finally, the motor torque is output in real time and fed back to the heavy-haul double-unit group train dynamics model.

[0056] In this embodiment, a heavy-haul double-unit group train dynamics model can be established based on the SIMPACK platform. The establishment of the heavy-haul double-unit group train dynamics model based on the SIMPACK platform includes:

[0057] Establish a leading train dynamics model;

[0058] Establish a following train dynamics model with the same formation as the leading train;

[0059] Set the train tracking distance, the initial train speed, and the track surface conditions.

[0060] Here, when establishing the leading train dynamics model, use SIMPACK to establish a train dynamics model of an HXN3 diesel locomotive coupled with 50 C80 freight cars. The diesel locomotive adopts a multi-rigid body spatial dynamics model, and details such as the car body, bogie, wheelset, axle box suspension device, and drive system device are considered. The locomotive drive system model details the gear transmission device and the motor mechanical system. Among them, the gear transmission model uses the moving Marker point technology, the calculation of the wheel-rail normal force in the locomotive wheel-rail contact adopts the Hertz contact algorithm, the calculation of the wheel-rail tangential force adopts the Polach creep theory, the freight car adopts a single-mass point model, and the vehicles are connected by a complete coupler buffer model.

[0061] See Figure 3 , after establishing the leading train dynamics model, on this basis, establish a following train dynamics model with the same formation, and then set parameters such as the train tracking distance, the initial train speed, and the track surface conditions.

[0062] Among them, it is necessary to consider in detail the vehicle-track interaction, locomotive wheel-rail relationship, traction drive control, braking device, etc. In the existing research on the operation control of heavy-haul train groups, single-particle or multi-particle models are generally adopted for trains. Although such simplified processing can improve the calculation efficiency and can be combined with the communication field at the same time, there are significant differences from the actual situation and it is impossible to accurately simulate the train dynamics performance under actual conditions. Therefore, when establishing a heavy-haul double-formation train group dynamics model based on the SIMPACK platform in this embodiment, the dynamics operation state of the double-formation heavy-haul train group can be accurately simulated, and this model has also been verified through actual test experiments.

[0063] It should be noted that the rail surface identification model can be a rail surface adhesion coefficient identification model based on a disturbance observer established in MATLAB; in the rail surface adhesion coefficient identification model based on a disturbance observer, a disturbance observer is used to F adh estimate the wheel-rail adhesion force in real time, that is, calculate the estimated value of the adhesion coefficient. Since the wheel-rail adhesion force cannot be directly measured and the wheel-rail adhesion state affects the safe operation of the train. Therefore, the adhesion force can be estimated by calculating the motor traction force or braking force, so as to obtain the wheel-rail longitudinal creep force and the wheel-rail adhesion coefficient, which are input into the adhesion control model as important anti-skid criteria.

[0064] Therefore, a rail surface adhesion coefficient identification model based on a disturbance observer is established in MATLAB, and the adhesion state of the rail surface is output in real time in SIMULINK, including wheel-rail traction force / braking force, wheel-rail longitudinal creep force, wheel-rail normal force, wheel-rail adhesion coefficient, etc. Since the wheel-rail adhesion force F adh cannot be directly measured, a disturbance observer is used to estimate it in real time, that is, the adhesion force is estimated by calculating the motor traction force or braking force. According to the locomotive axle load, the wheel-rail normal force N is calculated. At the same time, considering the influence brought by axle load transfer, it can also be directly output by the dynamics model. First, a locomotive wheel pair dynamics equation is established, then Laplace transform is performed, first-order low-pass filtering is carried out, and finally inverse Laplace transform is performed. Finally, the estimated value of the adhesion coefficient μ is:

[0065] ,

[0066] In the formula, ω is the rotational angular velocity of the wheel pair, J w is the moment of inertia of the wheel pair, R w is the radius of the wheel rolling circle, F B / Tis the equivalent braking force / tractive force at the rolling circle radius of the wheel, p is the Laplace operator, λ is the cut-off frequency.

[0067] Among them, in the wheel-rail adhesion control model, the adhesion control model of the leading train uses the longitudinal creep rate of the wheel set as the anti-skid criterion, and the torque is controlled by PID; the adhesion control model of the following train uses the longitudinal creep rate of the wheel set, the wheel-rail adhesion coefficient, the train tracking distance and the relative speed difference of the train as the combined criterion, and the torque is controlled and adjusted by the re-adhesion control strategy. The main control logic is as Figure 4 shown.

[0068] See Figure 4 -I's adhesion control process of the leading train, which uses the longitudinal creep rate of the wheel set as the anti-skid criterion for judgment; when the longitudinal creep rate of the wheel set c the difference from the given first threshold e Lc1 <0, it is determined as the skidding out-of-control state, enters the torque reduction stage, records the initial torque of the motor T 0 , uses PID control to reduce the torque, calculates the torque change amount Δ T L1 , and outputs the motor torque T Lt = T L0 - Δ T L1 , then enters the torque holding stage, the torque remains unchanged for a period of time, then enters the torque recovery stage, uses PID control to reduce the torque, calculates the torque change amount Δ T L2 , and outputs the motor torque T Lt = T 0 + Δ T L2 , finally, uses the second threshold for judgment. When the difference e Lc2 >0, the torque recovers to the initial state, and the adhesion control is completed;

[0069] The PID control is used to reduce the torque, and its PID torque control expression is:

[0070] ,

[0071] The difference between the longitudinal creep rate of the wheel set and the given threshold e Lci The expression is:

[0072] ,

[0073] In the formula, P, I, D are respectively the proportional coefficient, integral coefficient, and differential coefficient of the controller, t is the torque adjustment time, c Lref is the threshold value of the longitudinal creep rate of the wheel set, t 1 is the trigger time, t 2 is the end time.

[0074] See Figure 4-II For the adhesion control process of the following train, the wheel-rail adhesion coefficient and the longitudinal creep rate of the wheel set are used as a combined anti-skid criterion. At the same time, the train tracking distance and the relative speed difference of the train are input as boundary conditions. Within the allowable range of error, the train tracking distance is ensured to be constant, and the relative speed difference of the train is made close to zero. Its main adhesion control logic is basically the same as that of the leading train, but PID torque control is not adopted. The change amount of the torque is mainly controlled by an adjustment method with a fixed slope. In addition, to prevent conflicts between adhesion control and group operation control, the adhesion control of the following train will output a logical judgment value Log to solve this problem.

[0075] Therefore, in this embodiment, an adhesion control with a more comprehensive anti-skid criterion and a more stable PID torque adjustment strategy are adopted to achieve safer operation. The main purpose is to be able to adapt to the train operation control strategies under different group modes, improve the adhesion control effect under more complex conditions, and thus obtain information such as logical judgment values, motor torque, and speed, which are input into the group operation control model.

[0076] In this embodiment, only the group operation control mode is studied from the perspective of dynamics, and the communication system within the train group and the simulation modeling of train control system equipment are not considered. Therefore, in this embodiment, the group operation control model includes a train time-speed-position model and a train cooperative control model, as Figure 5 shown; the train time-speed-position model is provided by the heavy-haul train ATP system. In the heavy-haul double-unit train dynamics model, the corresponding track model and train running speed are directly set, and the train running time, distance, and speed are output in real time. The train cooperative control model is established by using the PID speed coordination algorithm and the constant time interval control strategy, and the vehicle speed difference and the train tracking distance are controlled through PID.

[0077] Here, the group operation control model takes the real-time speeds v 1 , v 2 of the leading train and the following train as inputs, and through PID adjustment, outputs the torque Δ T PID ;

[0078] However, under the skidding condition, the mutual coupling effect between the group operation control and the adhesion control also needs to be considered. Therefore, the group operation control model and the wheel-rail adhesion control model are adjusted and controlled, and the conversion is carried out through the "0" and "1" switches. The output logic decision value is defined as "Log = e c >0 && x > x max || Δ v > v 0 ". That is, when Log = 1, it means there is no adhesion control. At this time, the train tracking distance exceeds the maximum limit or the relative speed difference of the train exceeds the maximum limit. The group operation control model is turned on, and the final output torque is T FS / LS = T F / L + Δ T PID . When Log = 0, at this time, the wheelslip occurs on the wheel pair. The group operation control model is turned off, and the wheel-rail adhesion control model is turned on for torque adjustment. The output torque is T FS / LS = T F / L . The magnitude of the torque is only determined by the adhesion control.

[0079] During the entire adjustment and control process, data is transmitted in real time among the dynamic model of the heavy-haul double-unit group train, the wheel-rail adhesion control model, and the group operation control model. The decision control is carried out every 0.002 s. Within the allowable error range, the distance and speed between the front and rear vehicles are ensured to be constant, and the safe operation of the group train is realized.

[0080] It should be noted that in this embodiment, the proposed coordinated control of wheel-rail adhesion for heavy-haul group trains takes the train tracking distance and the relative speed difference between trains as boundary conditions to realize the mutual coupling relationship between group operation control and adhesion control. Since the dynamic model in this embodiment is a three-dimensional space model, which is complete in model, complex in structure and has many non-linearities, its state space equation / transfer function cannot be output, and the vehicle-vehicle communication / vehicle-ground-vehicle communication cannot be accurately simulated. However, this does not affect the core research content of this embodiment. Therefore, this embodiment can establish sensors as the transmission medium to transmit signals such as the time, speed, and position of the train in real time. Although the communication system within the train group is not detailedly established in this embodiment, the real-time transmission of data is still maintained to simulate the virtual interaction relationship based on communication between trains. Moreover, the focus of this embodiment is not on the impact of communication delay on heavy-haul group trains, but on integrating wheel-rail adhesion control into group operation control to cope with safe traction / braking under complex working conditions such as slipping / idling. Therefore, this embodiment simplifies the communication system within the group and carefully considers the wheel-rail adhesion control strategy to achieve real-time control among the dynamic system, adhesion control system, and group operation control system of the group trains. Embodiment 2

[0081] Based on Embodiment 1, the main parameters related to the dynamics of group trains and the coordinated control of wheel-rail adhesion in this embodiment are shown in Tables 1 - 2.

[0082] Table 1 Main parameters for the dynamic modeling of group trains

[0083] ,

[0084] Table 2 Main parameters for group operation and wheel-rail adhesion control

[0085] ,

[0086] According to the above modeling process of Embodiment 1 and referring to the main parameters of the above dynamics, adhesion control, and group operation control modeling, a coupled large model of the heavy-haul train group operation control system is established. The following line conditions and simulation results are used to illustrate the detailed application effect of this method.

[0087] In this co-simulation model, the group trains travel on a track surface that changes from dry to wet through the locomotive traction characteristic curve. The initial track surface is dry, then it changes from dry to wet and then returns to the dry state, and the changing track length is 140 m. When the group trains accelerate under traction and reach the wet track surface position, the leading locomotive's guiding wheelslip occurs, triggering the adhesion control system and the group operation control system.

[0088] Figure 6are the results of the angular acceleration and longitudinal creep ratio of the wheelsets of the leading train and the following train. As can be seen from Figure 6 that in the time period of t = 9.65 - 17.75 s, when the formation train travels on the track of 520 - 670 m, the leading train's locomotive guiding wheelset slips. The maximum amplitude of the angular acceleration of the following train in the control stage is 8.7 rad / s 2 , the maximum amplitude of the angular acceleration of the leading train in the control stage is 21.0 rad / s 2 , the maximum amplitude of the creep ratio of the following train in the control stage is 0.012, the maximum amplitude of the creep ratio of the leading train in the control stage is 0.033, the first threshold of the longitudinal creep ratio of the wheelset is 0.025, and the wheelsets are effectively controlled with good control effect.

[0089] Figure 7 It shows that under the combined action of formation operation control and adhesion control, the motor torque of the leading train is adjusted 8 times in total. The motor torque of the following train decreases steadily. When the rail surface returns to the dry state again, the motor torque of the leading train gradually decreases, and the motor torque of the following train gradually increases. Finally, at t = 32 s, the motor torques return to the same magnitude, and the formation train returns to the normal state and continues to run smoothly. In addition, the adhesion coefficient threshold in the present invention is 0.15, while the adhesion coefficient in the control stage is always stable at around 0.2. When the rail surface returns to the dry state, the maximum amplitude of the adhesion coefficient of the leading train reaches 0.38, and the adhesion utilization rate increases, indicating that this control method not only does not affect the adhesion characteristics of the locomotive, but may instead improve its adhesion utilization rate.

[0090] As can be seen from Figures 8 - 9 that during the entire control process, the tracking distance of the train always remains within the range of 1005 - 1005.8 m. After the slip control, the tracking distance only increases by 0.8 m. At the same time, the maximum value of the speed difference is only 0.11 m / s, which is much smaller than the relative speed difference threshold of the train. At t = 32 s, the two trains return to the same vehicle speed and maintain a constant train tracking distance, indicating that the control method of the present invention is effectively utilized and the control effect also meets the requirements of safe operation.

[0091] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for coordinated control of wheel-rail adhesion of a heavy-load group train, characterized in that: The steps include: The dynamic model of heavy-load double-unit train group, track surface recognition model, wheel-rail adhesion control model and group operation control model are established respectively; The double-marshaling group train in the heavy-load double-marshaling group train dynamic model includes a lead train and a following train, and a train tracking distance between the lead train and the following train is set, and the equivalent braking force or traction force of the wheels, the wheel-rail normal force, the lead train speed, the lead train time, the lead train wheel angular velocity, the following train speed, the following train time and the following train wheel angular velocity are obtained; The equivalent braking force or traction force of the wheel and the wheel-rail normal force are input into the rail surface identification model to calculate the estimated value of the adhesion coefficient; Inputting the estimated value of the adhesion coefficient, the speed of the lead train, the time of the lead train, the wheel-to-wheel angular velocity of the lead train, the speed of the following train, the time of the following train, and the wheel-to-wheel angular velocity of the following train into the wheel-rail adhesion control model, and calculating the motor torque of the lead train, the motor torque of the following train, and the output logic judgment value of the following train; The speed of the pilot train, the speed of the following train, the motor torque of the pilot train, the motor torque of the following train, and the output logic judgment value of the following train are input into the group operation control model, and after adjustment and control, the motor torque of the pilot train and the motor torque of the following train after adjustment and control are obtained; The motor torque of the lead train and the motor torque of the following train after adjustment and control are input into the dynamic model of the heavy-load double-unit group train.

2. A method for coordinated control of wheel-rail adhesion of heavy-load train groups according to claim 1, characterized in that: A dynamic model of heavy-load double-unit train group is established based on the SIMPACK platform.

3. The method for controlling wheel-rail adhesion of a heavy-load group train according to claim 2, characterized in that: The heavy-load double-train group train dynamics model is established based on the SIMPACK platform, including: Establish a pilot train dynamics model; Establish a dynamic model of the following train with the same formation as the lead train; Set the train tracking distance, initial train speed and track surface conditions.

4. The method for controlling wheel-rail adhesion of a heavy-load group train according to claim 1, characterized in that: The rail surface identification model is a rail surface adhesion coefficient identification model based on disturbance observer established in MATLAB; In the track adhesion coefficient identification model based on disturbance observer, the disturbance observer is used to identify the wheel-rail adhesion coefficient. F adh A real-time estimation is performed, i.e. an estimated value of the adhesion coefficient is calculated.

5. A method for coordinated control of wheel-rail adhesion of heavy-load train groups according to claim 4, characterized in that: The calculation of the estimated value of the adhesion coefficient includes: According to the locomotive axle weight, the wheel-rail normal force is calculated N ; Establish a locomotive wheel dynamics equation, perform Laplace transform, then use first-order low-pass filtering for processing, and then perform inverse Laplace transform to obtain the adhesion coefficient μ The estimated value of is: ， In the formula, ω is the wheelset rotation angular velocity, J w is the wheelset moment of inertia, R w is the radius of the wheel rolling circle, F T / B is the equivalent braking force / traction force at the radius of the wheel rolling circle, p is the Laplace operator, λ is the cut-off frequency.

6. The method for controlling wheel-rail adhesion of a heavy-load group train according to claim 1, characterized in that: In the wheel-rail adhesion control model, the adhesion control model of the leading train adopts the longitudinal creep rate of the wheelset as the anti-skid criterion, and the torque is controlled by PID; the adhesion control model of the following train adopts the longitudinal creep rate of the wheelset, the wheel-rail adhesion coefficient, the train tracking distance and the relative speed difference of the train as the combined criterion, and the torque is controlled and adjusted by the re-adhesion control strategy.

7. A method for coordinated control of wheel-rail adhesion of heavy-load train groups according to claim 6, characterized in that: The adhesion control process of the pilot train adopts the longitudinal creep rate of the wheelset as the anti-skid criterion for determination; When the longitudinal creep rate of the wheelset c The difference from the given first threshold e Lc1 When <0, it is judged as slipping out of control state, enters the torque reduction stage, and records the initial torque of the motor T 0, use PID control to reduce the torque, and calculate the torque change Δ T L1 , output motor torque T Lt = T L0 - Δ T L1 Then it enters the torque holding stage, the torque remains unchanged for a period of time, and then enters the torque recovery stage, using PID control to reduce the torque, and the torque change Δ is calculated T L2 , output motor torque T Lt = T 0+ Δ T L2 Finally, the second threshold is used for judgment. e Lc2 When >0, the torque returns to the initial state and adhesion control is completed; The PID control is used to reduce the torque, and the PID torque control expression is: ， The difference between the longitudinal creep rate of the wheelset and the given threshold e Lci The expression is: ， In the formula, P, I, D are the proportional coefficient, integral coefficient and differential coefficient of the controller respectively. t is the torque adjustment time, c Lref is the wheelset longitudinal creep rate threshold, t 1 is the trigger time, t 2 is the end time.

8. The method for controlling wheel-rail adhesion of a heavy-load group train according to claim 6, characterized in that: The adhesion control process of following the train adopts the wheel-rail adhesion coefficient and the longitudinal creep rate of the wheelset as the combined anti-skid criterion, and at the same time, inputs the train tracking distance and the relative speed difference of the train as boundary conditions, and ensures that the train tracking distance is constant within the allowable error range, and makes the relative speed difference of the train close to zero; The torque change is controlled by a fixed slope adjustment method, and the adhesion control output logic judgment value Log of the following train is output.

9. The method for controlling wheel-rail adhesion of a heavy-load group train according to claim 1, characterized in that: The group operation control model includes a train time-speed-position model and a train cooperative control model; The train time-speed-position model is provided by the heavy-load train ATP system. The corresponding track model and train running speed are directly set in the heavy-load double-group train dynamics model, and the train running time, distance and speed are output in real time. The train collaborative control model is established using the PID speed coordination algorithm and constant time distance control strategy, and the PID is used to control the vehicle speed difference and train tracking distance.

10. The method for controlling wheel-rail adhesion of a heavy-load group train according to claim 1, characterized in that: The group operation control model uses the real-time speed of the lead train and the following train v 1. v 2 as input, through PID regulation, output torque Δ T PID ; Under the slip condition, the mutual coupling effect between group operation control and adhesion control is considered, and the group operation control model and wheel-rail adhesion control model are adjusted and controlled. The "0" and "1" switches are used for conversion, and the output logic judgment value is defined as "Log = e c >0 && x > x max || Δ v > v 0”, that is, when Log=1, it means there is no adhesion control. At this time, the train tracking distance exceeds the maximum limit or the relative speed difference of the train exceeds the maximum limit. The group operation control model is turned on, and the final output torque is T FS / LS =T F / L +Δ T PID When Log=0, the wheelset slips, the group operation control model is turned off, the wheel-rail adhesion control model is turned on, and torque adjustment is performed. The output torque is T FS / LS =T F / L , the torque size is only determined by adhesion control.

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