Heavy-load group train wheel-rail adhesion cooperative control method

Abstract

The invention belongs to the field of rail traffic control, and provides a heavy-load group train wheel-rail adhesion cooperative control method which comprises the following steps: respectively establishing a heavy-load double-compiled group train dynamic model, a rail surface recognition model, a wheel-rail adhesion control model and a group operation control model; inputting the equivalent braking force or traction force of the wheel and the normal force of the wheel rail into the rail surface recognition model, calculating an estimated value of an adhesion coefficient, and inputting the estimated value into the group operation control model; and inputting the estimated value of the adhesion coefficient, the speed, time and wheel pair angular velocity of the pilot train and the speed, time and wheel pair angular velocity of the following train into a wheel-rail adhesion control model, calculating motor torque of the pilot train and the following train and an output logic decision value of the following train, inputting the motor torque and the output logic decision value into a group operation control model, and performing adjustment control to obtain the wheel-rail adhesion coefficient. The motor torques of the pilot train and the following train after adjustment and control are obtained; and inputting the adjusted and controlled motor torques of the pilot train and the following train into the heavy-load double-compiled group train dynamical model.

Description

Technical Field

[0001] The present invention relates to the field of rail transit control technology, and in particular to a method for coordinated control of wheel-rail adhesion of heavy-load group trains. Background Art

[0002] With the continuous development of my country's heavy-haul railways, the problems of safe operation control, transportation efficiency improvement, and transportation capacity bottleneck relief of heavy-haul trains have become increasingly prominent. The heavy-haul train group operation control technology breaks the traditional long and large marshaling mode. Through car-to-car and car-ground-to-car communication, the "virtual coupling" between each train group is realized with a smaller safe tracking distance. The MB-V mode of mobile blocking is adopted to increase the operation density of heavy-haul freight trains and improve the transportation capacity of heavy-haul railway freight systems. However, traditional signal systems and adhesion control strategies are difficult to support high-precision operation and control under group operation conditions. Therefore, the locomotive wheel-rail adhesion control method under the group operation mode needs to be further improved. Fast and accurate idling / slipping identification and calculation of train safety tracking distance under slipping idling / traction braking conditions require accurate and efficient adhesion control methods to ensure the safe operation of heavy-haul trains. Summary of the invention

[0003] The purpose of the present invention is to provide a heavy-load group train wheel-rail adhesion coordinated control method. On the basis of traditional re-adhesion control, the group operation control is combined with the train longitudinal dynamics safety performance and wheel-rail adhesion control strategy to ensure that the train runs smoothly in different sections and under different environmental conditions. At the same time, from the perspective of dynamics and adhesion control, a safe train tracking distance is provided for the group operation train, and the locomotive wheel-rail adhesion control effect is improved.

[0004] The present invention solves the technical problem and adopts the following technical solution: A method for coordinated control of wheel-rail adhesion of a heavy-load group train comprises the following steps: 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.

[0005] As a further optimization, a dynamic model of heavy-load double-unit group train is established based on the SIMPACK platform.

[0006] As a further optimization, the heavy-load double-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.

[0007] As a further optimization, 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.

[0008] As a further optimization, the estimated value of the adhesion coefficient is calculated, including: 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 B / Tis 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.

[0009] As a further optimization, 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.

[0010] As a further optimization, 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, 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: ,

[0011] 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.

[0012] As a further optimization, the adhesion control process of the following train adopts the wheel-rail adhesion coefficient and the longitudinal creep rate of the wheelset as the 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 error range, the train tracking distance is guaranteed to be constant and the relative speed difference of the train is 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.

[0013] As a further optimization, 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.

[0014] As a further optimization, 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 =TF / L , the torque size is only determined by adhesion control.

[0015] The beneficial effects of the present invention are as follows: through the above-mentioned heavy-load group train wheel-rail adhesion coordinated control method, the heavy-load double-train group train dynamics model, the track surface recognition model, the wheel-rail adhesion control model and the group operation control model can be coupled with each other and jointly simulated, and the group operation control is combined with the train longitudinal dynamics safety performance and the wheel-rail adhesion control strategy. On the one hand, a safe train tracking distance is provided for the group operation train, and on the other hand, the locomotive wheel-rail adhesion control effect can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of data processing trends of various models of a method for coordinated control of wheel-rail adhesion of a heavy-load group train in the first embodiment of the present invention; Figure 2 This is a simulation diagram of wheel-rail optimized adhesion control under the operation of a heavy-load train group in the first embodiment of the present invention; Figure 3 This is a diagram of the dynamics model of a group train system in Embodiment 1 of the present invention; Figure 4 The wheel-rail adhesion control diagram of the lead train and the following train in the first embodiment of the present invention; Figure 5 This is a group operation control model diagram in the first embodiment of the present invention; Figure 6 The longitudinal creep rate and angular acceleration of the wheelset of the lead train and the following train in the second embodiment of the present invention; Figure 7 is the adhesion coefficient and motor torque of the lead train and the following train in the second embodiment of the present invention; Figure 8 is the speed and relative speed difference between the pilot train and the following train in the second embodiment of the present invention; Fig. 9 It is the running distance and tracking interval of the lead train and the following train in the second embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, 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 in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations. Embodiment 1

[0018] See also Figure 1 and Figure 2This embodiment provides a method for coordinated control of wheel-rail adhesion of a heavy-load group train, comprising the following steps: S1. Establish the heavy-load double-train group train dynamics model, track surface recognition model, wheel-rail adhesion control model and group operation control model respectively; S2. 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; S3, inputting the equivalent braking force or traction force of the wheel and the wheel-rail normal force into the rail surface identification model to calculate an estimated value of the adhesion coefficient; S4, 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; S5, inputting the pilot train speed, the following train speed, the pilot train motor torque, the following train motor torque and the following train output logic determination value into the group operation control model, and after adjusting and controlling, obtaining the pilot train motor torque and the following train motor torque after adjusting and controlling; S6. Input the motor torque of the pilot train and the motor torque of the following train after adjustment and control into the dynamic model of the heavy-load double-train group train. When the wheelset slips, after multiple adjustments by multiple systems, the motor torque is finally fed back to the dynamic model of the heavy-load double-train group train in real time.

[0019] In this embodiment, a heavy-load double-group train dynamics model may be established based on the SIMPACK platform. The heavy-load double-group train dynamics model established based on the SIMPACK platform includes: 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.

[0020] Here, when establishing the dynamic model of the pilot train, SIMPACK is used to establish the train dynamic model of a HXN3 diesel locomotive coupled to 50 C80 freight cars. The diesel locomotive adopts a multi-rigid body space dynamic model, and considers the car body, frame, wheelset, axle box suspension device, drive system device, etc. in detail. The locomotive drive system model considers the gear transmission device and motor mechanical system in detail. Among them, the gear transmission model adopts the moving marker point technology, the wheel-rail normal force calculation in the locomotive wheel-rail contact adopts the Hertz contact algorithm, and the wheel-rail tangential force calculation adopts the Polach creep theory. The freight car adopts a single particle model, and the vehicles are connected by a complete coupler buffer model.

[0021] See also Figure 3 After establishing the dynamic model of the lead train, a dynamic model of the following train with the same formation is established on this basis, and then the parameters such as train tracking distance, train initial speed, and track surface conditions are set.

[0022] Among them, it is necessary to consider the vehicle-track relationship, locomotive wheel-track relationship, traction drive control, vehicle deceleration device, etc. in detail. In the existing heavy-load train group operation control research, the train generally adopts a single-particle or multi-particle model. Although such simplified processing can improve the calculation efficiency and can be combined with the communication field, it is quite different from the actual situation and cannot accurately simulate the train dynamics performance under actual conditions. Therefore, when this embodiment establishes a heavy-load double-group train dynamics model based on the SIMPACK platform, it can accurately simulate the dynamic operation state of the double-group heavy-load group train, and the model has also been verified through actual test experiments.

[0023] It should be pointed out that the track surface identification model can be a track surface adhesion coefficient identification model based on disturbance observer established in MATLAB; in the track surface adhesion coefficient identification model based on disturbance observer, the disturbance observer is used to calculate the wheel-rail adhesion. F adh Real-time estimation is performed, that is, the estimated value of the adhesion coefficient is calculated. Since the adhesion between the wheel and the rail cannot be measured directly, and the wheel-rail adhesion state affects the safe operation of the train. Therefore, the adhesion can be estimated by calculating the motor traction or braking force, thereby obtaining 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.

[0024] Therefore, a disturbance observer-based track adhesion coefficient identification model is established in MATLAB, and the track adhesion state is output in real time in SIMULINK, including wheel-rail traction / braking force, wheel-rail longitudinal creep force, wheel-rail normal force, wheel-rail adhesion coefficient, etc. F adhIt cannot be measured directly, so a disturbance observer is used to estimate it in real time, that is, the adhesion is estimated by using the motor traction or braking force. According to the locomotive axle weight, the wheel-rail normal force is calculated. N , while considering the impact of axle load transfer, it can also be directly output by the dynamic model. First, establish a locomotive wheel set dynamic equation, then perform Laplace transform, use first-order low-pass filtering for processing, and finally perform Laplace inverse transform. Finally, the adhesion coefficient is obtained. 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 B / T 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.

[0025] Among them, in the wheel-rail adhesion control model, the adhesion control model of the leading train uses 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 uses 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. The main control logic is as follows Figure 4 shown.

[0026] See also Figure 4 -I's lead train adhesion control process uses the longitudinal creep rate of the wheelset as the anti-skid criterion for judgment; 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, 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 TLt = 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.

[0027] See also Figure 4-Ⅱ The adhesion control process of the following train uses the wheel-rail adhesion coefficient and the longitudinal creep rate of the wheelset as the 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 error range, the train tracking distance is guaranteed to be constant and the relative speed difference of the train is close to zero. Its main adhesion control logic is basically the same as that of the pilot train, but PID torque control is not used. The torque change is mainly controlled by adjusting the fixed slope. In addition, in order to prevent the adhesion control from conflicting with the group operation control, the adhesion control of the following train will output the logic judgment value Log to solve this problem.

[0028] Therefore, in this embodiment, a more comprehensive anti-slip criterion adhesion control 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 strategy under different group modes and improve the adhesion control effect under more complex conditions, so as to obtain logic judgment values, motor torque, speed and other information, and input them into the group operation control model.

[0029] In this embodiment, the group operation control mode is only studied from the perspective of dynamics, without considering the simulation modeling of the communication system in the train group and the train control system equipment. Therefore, in this embodiment, the group operation control model includes the train time-speed-position model and the train cooperative control model, such as Figure 5As shown in the figure, 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 cooperative control model is established using the PID speed coordination algorithm and constant time distance control strategy, and the speed difference and train tracking distance are controlled by PID.

[0030] Here, 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 ; However, under the slip condition, the mutual coupling effect between the group operation control and the adhesion control must also be considered. Therefore, the group operation control model and the wheel-rail adhesion control model are adjusted and controlled, 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.

[0031] During the entire adjustment and control process, data is transmitted in real time between the heavy-load double-train group train dynamics model, the wheel-rail adhesion control model and the group operation control model. Decision control is performed every 0.002 seconds to ensure that the distance and speed between the front and rear vehicles are constant within the allowable error range, thereby achieving safe operation of the group train.

[0032] It should be noted that, in this embodiment, the proposed heavy-load group train wheel-rail adhesion coordinated control takes the train tracking distance and the relative speed difference of the train 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, the model is complete, the structure is complex, and there are many nonlinearities, it is impossible to output its state space equation / transfer function, and it is impossible to accurately simulate the vehicle-to-vehicle communication / vehicle-ground-vehicle communication, but this does not affect the core research content of this embodiment. Therefore, this embodiment can establish sensors as transmission media to transmit the time, speed, position and other signals of the train in real time. Although this embodiment does not establish a detailed communication system within the train group, it still maintains real-time data transmission, thereby simulating the virtual interaction relationship between trains based on communication. Moreover, the focus of this embodiment is not on the impact of communication delay on heavy-load 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 considers the wheel-rail adhesion control strategy in detail, thereby realizing real-time control between the group train dynamic system, adhesion control system and group operation control system. Embodiment 2

[0033] Based on the first embodiment, the main parameters of the group train dynamics and wheel-rail adhesion coordinated control involved in this embodiment are shown in Tables 1-2.

[0034] Table 1 Main parameters of group train dynamics modeling , Table 2 Main parameters of group operation and wheel-rail adhesion control , According to the above modeling process of implementation one, and with reference to the main parameters of the above dynamics, adhesion control, and group operation control modeling, a large coupled model of the heavy-load train group operation control system was established. The following line conditions and simulation results are used to illustrate the detailed application effect of this method.

[0035] In this joint simulation model, the group train passes through the locomotive traction characteristic curve and travels on a track where the track surface changes from dry to wet. The initial track surface is dry, then the track surface changes from dry to wet, and then returns to dry. The length of the changed line is 140m. When the group train accelerates to the wet track surface, the locomotive guide wheels of the lead train slip, triggering the adhesion control system and the group operation control system.

[0036] Figure 6 is the result of the wheel pair angular acceleration and the wheel pair longitudinal creep rate of the lead train and the following train. Figure 6It can be seen that in the time period of t=9.65~17.75s, when the group train was traveling on the track at 520~670m, the locomotive guide wheel pair of the leading train slipped. The maximum angular acceleration of the following train in the control stage is 8.7 rad / s 2 The maximum angular acceleration of the pilot train during the control phase is 21.0 rad / s 2 The maximum creep rate of the following train in the control stage is 0.012, the maximum creep rate of the leading train in the control stage is 0.033, and the first threshold of the longitudinal creep rate of the wheelset is 0.025. The wheelset is effectively controlled and the control effect is good.

[0037] Figure 7 It shows that under the joint action of group operation control and adhesion control, the motor torque of the pilot train was adjusted 8 times in total, and the motor torque of the following train decreased steadily. When the rail surface returned to a dry state, the motor torque of the pilot train gradually decreased, and the motor torque of the following train gradually increased. Finally, at t=32s, the motor torque returned to the same size, and the group train returned to a normal state and continued 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. As the rail surface returns to a dry state, the maximum value of the adhesion coefficient of the pilot train reaches 0.38, and the adhesion utilization rate increases. This shows that the control method not only does not affect the adhesion characteristics of the locomotive, but may improve its adhesion utilization rate.

[0038] Depend on Figures 8 and 9 It can be seen that during the entire control process, the tracking distance of the train is always maintained in the range of 1005~1005.8m. After slip control, the tracking distance only increases by 0.8m. At the same time, the maximum speed difference is only 0.11m / s, which is far less than the relative speed difference threshold of the train. When t=32s, the two cars return to the same speed and maintain a constant train tracking distance, which shows that the control method of the present invention is effectively utilized and the control effect also meets the requirements of safe operation.

[0039] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in 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 B / T 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.

Images