A virtual train tracking control method and system

Abstract

The present invention discloses a virtual marshaling train tracking control method and system, the method comprising the following steps: based on the actual state of each train unit in the current cycle and the target state sequence of a first preset number of cycles before the current moment, determining whether to execute a backup control strategy to obtain a first judgment result; if the first judgment result is yes, executing the backup control strategy to control each train unit; if the first judgment result is no, calculating the target state sequence of each train unit in the current cycle according to position or calculating the target state sequence of each train unit in the current cycle using a synchronization relationship; and controlling each train unit according to the target state sequence of each train unit in the current cycle. The present invention achieves the goal of ensuring that all trains can maintain a synchronous operation relationship with each other while tracking their respective recommended driving curves.

Description

Technical Field

[0001] The present invention relates to the technical field of rail transit signal control, and in particular to a virtual marshaling train tracking control method and system. Background Art

[0002] Urban rail transit (URRT) construction has achieved remarkable success in recent years. With the rapid expansion of URRT networks, the uneven temporal and spatial distribution of passenger flow and its erratic dynamic changes have become increasingly prominent. Virtual train coupling (VC) technology is a widely recognized solution to the operational challenges this presents.

[0003] Virtual marshaling technology can significantly shorten the running distance between train units that are not physically coupled, allowing them to provide transport services similar to physically coupled trains. Virtual marshaling technology enables online, dynamic, and flexible adjustment of train unit numbers, thereby improving the effective utilization of vehicle and line resources. This can both meet the high capacity demands during peak passenger flow periods and reduce the idle vehicle rate during off-peak periods. Therefore, the development of virtual marshaling technology can reduce train operating energy consumption and transportation costs without compromising service quality, which is of great significance to the green and sustainable development of urban rail transit.

[0004] In most existing studies, the control method for virtual train operation is to achieve this by having the lead train follow a recommended driving curve, while the following train adjusts based on the real-time status of the preceding train to maintain a desired tracking distance with the preceding train. To ensure train operation safety, the tracking distance should be greater than the safety protection distance. However, the actual safety protection distance is high-order and nonlinear, and the following train in real-time control cannot directly handle complex distances. Therefore, a more conservative, simplified tracking distance is often used. This approach increases the tracking distance between adjacent train units and can also lead to problems such as asynchronous train entry and large differences in platform stop times.

[0005] To address this issue, research has proposed that all train units in a virtual formation follow their own recommended driving curves to maintain a desired tracking distance. Each train unit's recommended driving curve consists of a time-discrete sequence of position, velocity, and acceleration. When all train units in the virtual formation follow the recommended curves on time, they arrive at their target platforms relatively synchronously, minimizing the time difference in arrival at the station.

[0006] However, due to inevitable departure delays, accumulated control errors and other problems, existing methods cannot guarantee that all trains can maintain a synchronous operation relationship with each other while tracking their respective recommended driving curves, which will seriously affect the operating performance of virtual marshaling trains, resulting in large differences in the time for virtual marshaling trains to enter the station or unexpected situations such as emergency braking triggered by overspeeding during operation. Summary of the Invention

[0007] The purpose of the present invention is to provide a virtual train tracking control method and system to ensure that all trains can maintain a synchronous operation relationship with each other while tracking their respective recommended driving curves.

[0008] To achieve the above object, the present invention provides the following solutions:

[0009] The present invention provides a virtual marshaling train tracking control method, the method comprising the following steps:

[0010] Get the actual status of the current cycle of each train unit in the virtual formation;

[0011] Based on the actual state of each train unit in the current cycle and the target state sequence of a first preset number of cycles before the current moment, determining whether to execute a backup control strategy to obtain a first determination result; the backup control strategy includes a control strategy for tracking the driving curve of the first train unit and a control strategy for tracking the i-th train unit of the i+1-th train unit, where the value of i is greater than or equal to 1;

[0012] If the first judgment result is yes, then executing the backup control strategy to control each train unit;

[0013] If the first judgment result is no, perform the following operations:

[0014] Determining whether the synchronization of each train unit in the virtual marshaling satisfies a preset condition, and obtaining a second determination result;

[0015] If the second judgment result indicates yes, then calculating the target state sequence of each train unit in the current cycle according to the actual state of each train unit in the current cycle according to the position;

[0016] If the second judgment result indicates no, then calculating the target state sequence of each train unit in the current cycle using the synchronization relationship according to the actual state of each train unit in the current cycle;

[0017] Each train unit is controlled according to the target state sequence of the current cycle of each train unit.

[0018] Optionally, the determining whether to execute the backup control strategy based on the actual state of each train unit in the current cycle and the target state sequence of a first preset number of cycles before the current moment to obtain the first determination result specifically includes:

[0019] Determine whether the flag bit of the first cycle before the current moment is displayed normally, and obtain a third determination result;

[0020] If the third judgment result indicates yes, then determine whether the difference between the actual speed of the current cycle of each train unit and the first target speed in the target state sequence within n cycles before the current moment is less than the speed difference threshold; if the difference between the speed of the current cycle of each train unit and the first target speed in the target state sequence within n cycles before the current moment is less than the speed difference threshold, then determine that the first judgment result is yes, and set the flag bit of the current cycle to normal; otherwise, determine that the first judgment result is no, and set the flag bit of the current cycle to abnormal;

[0021] If the third judgment result indicates no, then determine whether the difference between the actual speed of the current cycle of each train unit and the first target speed in the target state sequence within m cycles before the current moment is less than the speed difference threshold. If the difference between the speed of the current cycle of each train unit and the first target speed in the target state sequence within m cycles before the current moment is less than the speed difference threshold, then determine that the first judgment result is yes, and set the flag bit of the current cycle to normal; otherwise, determine that the first judgment result is no, and set the flag bit of the current cycle to abnormal, n and m are the values ​​of the first preset number in different situations, m≥n.

[0022] Optionally, the determining whether the synchronization of each train unit in the virtual formation satisfies a preset condition to obtain a second determination result specifically includes:

[0023] When the time index deviations between any two adjacent train units in the virtual marshaling are less than the time index deviation threshold, determining that the second judgment result is yes;

[0024] When the time index deviations between any two adjacent train units in the virtual formation are not all less than the time index deviation threshold, the second judgment result is determined to be no.

[0025] Optionally, the step of calculating the target state sequence of each train unit in the current cycle according to the actual state of each train unit in the current cycle by position specifically includes:

[0026] According to the actual position and actual speed of each train unit in the current cycle, the initial target state is determined as:

[0027] in, is the initial target position in the target state sequence of the current cycle of the i-th train unit, is the initial target speed in the target state sequence of the current cycle of the i-th train unit, s i,k and v i,k are the actual position and actual speed of the current cycle of the i-th train unit, V() is the calculation function of the target speed, and represent the qth and q+1th recommended position values ​​on the driving curve of the i-th train unit, respectively. and represents the qth and q+1th recommended speed values ​​on the driving curve of the i-th train unit, where I is the number of train units in the virtual formation;

[0028] Based on the initial target position and the initial target speed, the target position and target speed in the target state sequence of the current cycle of each train unit are calculated based on the following formula;

[0029]

[0030]

[0031] in, and are the j+1th target position and j+1th target speed in the target state sequence of the current cycle of the i-th train unit, and are the jth target position and jth target speed in the target state sequence of the current cycle of the i-th train unit, N is the number of target states in the target state sequence, τ is the sampling interval, is the calculation function of the target speed, and represent the pth and p+1th recommended position values ​​on the driving curve of the i-th train unit, respectively. and represents the pth and p+1th recommended speed values ​​on the driving curve of the i-th train unit;

[0032] A differential calculation is performed on the target speed in the target state sequence of the current cycle of each train unit to obtain the target acceleration in the target state sequence of the current cycle of each train unit.

[0033] Optionally, the step of calculating the target state sequence of each train unit in the current cycle by using the synchronization relationship according to the actual state of each train unit in the current cycle specifically includes:

[0034] According to the actual position and actual speed of each train unit in the current cycle, the initial target state of each train unit is determined as:

[0035] in, is the initial target position in the target state sequence of the current cycle of the i-th train unit, is the actual position of the current cycle of the i-th train unit, and are the initial target speeds in the target state sequences of the 1st train unit and the i'th train unit in the current cycle, v a (0) is the adjustment amount of the initial target speed in the target state sequence of the current cycle of the i-th train unit, is the calculation function of the target speed, and represent the qth and q+1th recommended position values ​​on the driving curve of the i-th train unit, respectively. and represents the qth and q+1th recommended speed values ​​on the driving curve of the i-th train unit; I is the number of train units;

[0036] Based on the initial target state, the target position and target speed in the target state sequence of the current cycle of each train unit are calculated based on the following formula;

[0037]

[0038]

[0039] in, and are the j+1th target position and j+1th target speed in the target state sequence of the current cycle of the i-th train unit, and are the jth target position and jth target speed in the target state sequence of the current cycle of the i-th train unit, τ is the sampling interval, is the calculation function of the target speed, and represent the pth and p+1th recommended position values ​​on the driving curve of the i-th train unit, respectively. and represents the pth and p+1th recommended speed values ​​on the driving curve of the i-th train unit, v a (j) is the adjustment amount of the jth target speed in the target state sequence;

[0040] A differential calculation is performed on the target speed in the target state sequence of the current cycle of each train unit to obtain the target acceleration in the target state sequence of the current cycle of each train unit.

[0041] Optionally, the calculation formula for the adjustment amount of the j-th target speed in the target state sequence is:

[0042]

[0043] Among them, c a The number of cycles between the current cycle and the cycle where the distance is first adjusted by the adjustment amount, a a is the preset adjustment acceleration, τ is the sampling interval, Δv a is the maximum adjustment speed, T a Adjust the time for the preset.

[0044] Optionally, the controlling each train unit according to the target state sequence of the current cycle of each train unit further includes:

[0045] When the difference between the actual speed of each train unit and the EBI speed at a second preset number of moments between the previous moment and the current moment does not meet the preset condition, the following operations are performed:

[0046] Adjust the target speed and target position in the target state sequence of the current cycle of each train unit based on the following formula;

[0047]

[0048]

[0049]

[0050] in, is the jth adjusted target speed in the target state sequence of the current cycle of the i-th train unit, and are the jth and j+1th adjusted target positions in the target state sequence of the current cycle of the i-th train unit, respectively. is the jth target speed in the target state sequence of the current cycle of the i-th train unit, k e is the compensation ratio coefficient, τ is the sampling interval, Δv e is the speed compensation, v i,lis the actual speed at the lth moment before the current moment, l-1 is the second preset number, is the EBI speed of the i-th train unit, v e is the EBI speed margin value;

[0051] A differential calculation is performed on the adjusted target speed in the target state sequence of the current cycle of each train unit to obtain the adjusted target acceleration in the target state sequence of the current cycle of each train unit.

[0052] A virtual marshaling train tracking control system, the system being applied to the above method, the system comprising:

[0053] A status acquisition module is used to obtain the actual status of each train unit in the virtual marshaling in the current cycle;

[0054] a first judgment module, configured to determine whether to execute a backup control strategy based on the actual state of each train unit in the current cycle and a target state sequence of a first preset number of cycles before the current moment, and obtain a first judgment result; the backup control strategy includes a control strategy for tracking the driving curve of the first train unit and a control strategy for tracking the i-th train unit of the i+1-th train unit, where the value of i is greater than or equal to 1;

[0055] a first control module, configured to execute a backup control strategy to control each train unit if the first judgment result is yes;

[0056] A second judgment module is configured to, if the first judgment result is negative, judge whether the synchronization of each train unit in the virtual marshaling satisfies a preset condition to obtain a second judgment result;

[0057] a first target state sequence calculation module, configured to calculate the target state sequence of each train unit in the current cycle according to the actual state of each train unit in the current cycle according to the position, if the second judgment result indicates yes;

[0058] a second state sequence calculation module, configured to calculate a target state sequence of each train unit in the current cycle using a synchronization relationship based on the actual state of each train unit in the current cycle if the second judgment result indicates no;

[0059] The second control module is used to control each train unit according to the target state sequence of the current cycle of each train unit.

[0060] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0061] A computer-readable storage medium stores a computer program, which implements the above method when executed.

[0062] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0063] An embodiment of the present invention provides a virtual marshaling train tracking control method and system, the method comprising the following steps: obtaining the actual state of the current cycle of each train unit in the virtual marshaling; judging whether to execute a backup control strategy based on the actual state of the current cycle of each train unit and the target state sequence of a first preset number of cycles before the current moment, and obtaining a first judgment result; if the first judgment result is yes, executing the backup control strategy to control each train unit; if the first judgment result is no, judging whether the synchronization of each train unit in the virtual marshaling meets the preset conditions, and obtaining a second judgment result; if the second judgment result indicates yes, calculating the target state sequence of the current cycle of each train unit according to the position based on the actual state of the current cycle of each train unit; if the second judgment result indicates no, calculating the target state sequence of the current cycle of each train unit according to the synchronization relationship based on the actual state of the current cycle of each train unit; and controlling each train unit according to the target state sequence of the current cycle of each train unit. The present invention uses the control strategy of tracking driving curves as the main solution and the tracking of target state sequences based on position calculation or synchronization relationship calculation as the auxiliary solution, thereby ensuring that all trains can maintain a synchronous operation relationship with each other while tracking their respective recommended driving curves. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0065] Figure 1 A flowchart of a virtual marshaling train tracking control method provided by an embodiment of the present invention;

[0066] Figure 2 Generate a logic flow chart for the target state sequence provided by the embodiment of the present invention;

[0067] Figure 3 The speed and distance-time diagrams of the front and rear train units under the ideal control effect provided by the embodiment of the present invention;

[0068] Figure 4Each train unit provided in the embodiment of the present invention still operates according to its own recommended speed curve, and the speed and distance-time diagrams of the front and rear train units under the condition of delayed departure of the rear train;

[0069] Figure 5 The embodiment of the present invention provides a speed and distance-time diagram of a train unit under the condition of a delayed departure of the following train using the present invention to control a virtual marshaling train;

[0070] Figure 6 The speed and distance-time diagrams of the front and rear train units are provided for the case where each train unit still operates according to its own recommended speed curve and the cumulative control error of the rear train leads to asynchrony (the rear train is slower than the front train);

[0071] Figure 7 A speed and distance-time diagram of a train unit provided by an embodiment of the present invention when a virtual marshaling train is controlled by the present invention and the cumulative control error of the rear train leads to asynchrony (the rear train is slower than the front train);

[0072] Figure 8 The speed and distance-time diagrams of the front and rear train units are provided for the case where each train unit still operates according to its own recommended speed curve and the cumulative control error of the rear train leads to asynchrony (the rear train is faster than the front train);

[0073] Figure 9 The embodiment of the present invention provides a speed, distance-time diagram of a train unit when a virtual marshaled train is controlled by the present invention and the cumulative control error of the rear train leads to asynchrony (the rear train is faster than the front train). DETAILED DESCRIPTION

[0074] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0075] The purpose of the present invention is to provide a virtual train tracking control method and system to ensure that all trains can maintain a synchronous operation relationship with each other while tracking their respective recommended driving curves.

[0076] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0077] Example 1

[0078] Embodiment 1 of the present invention provides a virtual train tracking control method. Figure 1 As shown, the method includes the following steps:

[0079] Get the actual status of each train unit in the virtual formation in the current cycle.

[0080] Based on the actual state of the current cycle of each train unit and the target state sequence of the first preset number of cycles before the current moment, it is determined whether to execute the backup control strategy to obtain a first judgment result; the backup control strategy includes the control strategy of tracking the driving curve of the first train unit and the control strategy of tracking the i-th train unit of the i+1-th train unit, where the value of i is greater than or equal to 1.

[0081] If the first judgment result is yes, the backup control strategy is executed to control each train unit.

[0082] If the first judgment result is no, perform the following operations:

[0083] It is determined whether the synchronization of each train unit in the virtual marshaling satisfies a preset condition to obtain a second determination result.

[0084] If the second judgment result indicates yes, then according to the actual state of each train unit in the current cycle, the target state sequence of each train unit in the current cycle is calculated according to the position.

[0085] If the second judgment result indicates no, then according to the actual state of each train unit in the current cycle, the target state sequence of each train unit in the current cycle is calculated using the synchronization relationship.

[0086] Each train unit is controlled according to the target state sequence of the current cycle of each train unit.

[0087] like Figure 2 As shown, the above method specifically includes:

[0088] The position, velocity and acceleration of the receiving train unit i at time k are expressed as s i,k , v i,k , a i,k , where i = 1 and 2 represent the front and rear trains, respectively. First, determine the running phase of the virtual train. When all the following conditions are true, it is considered to be in the platform parking phase; otherwise, it is considered to be in the inter-station operation phase: (1) The positions of all train units are within the platform parking area; (2) The speed of all train units is zero; (3) The stop countdown is not zero; (4) No platform departure signal is received.

[0089] If it is in the platform parking stage, other modules will be responsible for handling the platform operation functions (this module can use the design in existing research and invention, and the present invention does not involve the module design to realize this part of the function).

[0090] If it is in the interval operation stage, the control target sequence of each train unit will be calculated.

[0091] Use the target sequence in the future Indicates, where j = 1, 2, ..., N, N represents the maximum time domain length, and the recommended speed curve calculated offline is used Indicates that the sampling interval is τ.

[0092] Function 1 determines whether the control errors of all train units are within the acceptable range. If the control errors of all train units meet the requirements, meaning they can keep up with the recommended driving curve, adjusting the target sequence can effectively alleviate problems such as asynchronous operation caused by accumulated control errors. However, if the control of train units is poor, causing them to fall behind the target sequence, the difference between the actual train state and the target sequence is large, and the impact of adjusting the target sequence on the actual state is difficult to determine, making it difficult to achieve synchronized train operation by adjusting the target sequence. Therefore, first determine whether the train can keep up with the target (speed) to determine the adjustment method.

[0093] The execution steps of function 1 are as follows:

[0094] (1) Calculate the difference between actual speed and target speed

[0095] (2) If the previous cycle flag shows that the control effect is normal, determine whether the difference within n cycles meets the threshold Requirements:

[0096] (3) If the previous cycle flag indicates that the control effect is abnormal, determine whether the difference within m cycles meets the threshold Requirements:

[0097] (4) If the difference meets the requirements, the control effect is normal and the main scheme is switched to.

[0098] (5) If the difference does not meet the requirements, the output control effect abnormal flag will be turned on and the backup plan will be used.

[0099] The design scheme of the numerical threshold is as follows. Representing a collection

[0100]

[0101] Among them, v r Can be a velocity-related value v r =f(v 1,k ,v 2,k ), or it can be a constant value, determined according to the variation law of the difference between the actual speed and the target speed in the experimental results. However, it should be noted that And m ≥ n. This is to avoid frequent switching between normal and abnormal judgment results, which may cause algorithm instability.

[0102] Next, enter function 2 to check the synchronization relationship of all train units. The synchronization of train units is determined by the time index of the current state of all train units on their respective recommended driving curves.

[0103] The execution steps of function 2 are as follows:

[0104] (1) Calculate the time index of the two vehicles: t i,k =T(s i,k ), T(s i,k ) represents a function that converts train positions into corresponding time indexes. A preferred calculation method is

[0105]

[0106] (2) Calculate the time index difference Δt between the two vehicles k =t 1,k -t 2,k ;

[0107] (3) If the previous cycle flag shows that the time index difference between the two vehicles is normal, then determine the time index difference Δt between the two vehicles within n cycles. k =t 1,k -t 2,k Whether the requirements are met

[0108] (4) If the previous cycle flag shows that the time index difference between the two vehicles is abnormal, then determine the time index difference Δt between the two vehicles within m cycles. k =t 1,k -t 2,k Whether the requirement Δt is met k ∈T t ;

[0109] (5) If the difference meets the requirements, go to function 3;

[0110] (6) If the difference does not meet the requirements and the speed of all train units is greater than Then go to function 4.

[0111] Threshold value T t A preferred design scheme is as follows

[0112] T t :={Δt:Δt≤t}

[0113] Where t can be a value related to speed t=f(v 1,k ,v 2,k ), or it can be a constant value, determined according to the variation law of the difference between the actual speed and the target speed in the experimental results. However, it should be noted that And m ≥ n. This is to avoid frequent switching between normal and abnormal judgment results, which may cause algorithm instability.

[0114] Function 3 is used to calculate the control target sequence for the future period based on the output of Function 2. Entering Function 3 means that all train units have good tracking control and are currently operating synchronously. Therefore, all train units calculate the target sequence according to their respective recommended driving curves, which can still ensure the synchronous operation of the virtual marshaling with close spacing.

[0115] The execution steps of function 3 are as follows:

[0116] (1) Calculate the target speed of the train at its current location:

[0117] (2) Based on the position and speed at time j, calculate the target position and speed at the next time j+1

[0118] (3) Calculate the target acceleration by taking the difference based on the target velocity

[0119] Among them, the calculation function V of the target speed r (s i ) is defined as

[0120] The output of Function 2 is transferred to Function 4 to calculate the control target sequence for the future period. If Function 4 is entered, it indicates that the virtual train formation is not synchronized properly and requires adjustment based on the real-time status. The fundamental idea behind Function 4 is to use the time index of the leading train to find the relative displacement that needs to be adjusted for the trailing train, that is, to convert the time asynchrony into position asynchrony. Then, within a specified period of time, the trailing train must adjust back to this displacement.

[0121] The execution steps of function 4 are as follows:

[0122] (1) When entering function 4 for the first time, initialize the adjustment flag F a =1 and counter c a =1; calculate the distance difference between the corresponding positions of the two vehicles' time nodes on the recommended speed curve of the following vehicle And calculate the maximum adjustment speed Among them, T a with a a They represent the adjustment time designed in advance and the acceleration during the adjustment process respectively;

[0123] (2) Calculate the target speed of the following vehicle at its current position on the recommended speed curve of the following vehicle: where v a (j) represents the adjustment amount related to the synchronization of the train units and is expressed by the following formula

[0124]

[0125] Among them, c a The number of cycles between the current cycle and the cycle when the distance is first adjusted by the adjustment amount is used to represent how many cycles have passed since the distance was first adjusted by this equation. For example, when k = 10 and the distance is first adjusted by this method, then when k = 11, c a =2, when k=12, c a =3, and so on.

[0126] (3) Based on the position and speed at time j, calculate the target position and speed at the next time j+1 and

[0127] (4) Calculate the target acceleration by taking the difference based on the target velocity

[0128] This design can be used in a limited time domain T a The difference between the time nodes of the two vehicles is eliminated, and the speed adjustment value first gradually increases and then gradually decreases to 0. The changing trend of the target speed sequence is reflected in the subsequent experimental result graph.

[0129] According to the output values ​​of function 1 and function 2, the function 5 is transferred to the function 5. The implementation of function 5 can follow the existing virtual marshaling train tracking operation control method, which will not be described in detail in the embodiment of the present invention.

[0130] Finally, function 6 is used to prevent the train's target speed from being too high, which could lead to emergency braking during tracking. The core of this function is to determine the relationship between the train's current speed and the EBI speed.

[0131] The execution steps of function 6 are as follows:

[0132] (1) Calculate the difference between actual speed and EBI speed

[0133] (2) Determine whether the difference within n cycles meets the threshold Vebi Requirements: Among them, V ebi :={Δv:Δv≤v e}, v e It is the EBI speed margin value designed in advance.

[0134] (4) If the difference meets the requirements, the calculated target position, velocity, and acceleration sequence are output normally;

[0135] (5) If the difference does not meet the requirements, the calculated target position, velocity, and acceleration sequence will be adjusted as follows: For all target speeds Among them, k e is the compensation proportional coefficient; and

[0136] (6) Calculate the target acceleration by taking the difference based on the target velocity

[0137] Afterwards, based on the calculated target sequence, the control command generation module calculates control commands and applies them to the train. Since the generated target is a sequence of target states for a period of time in the future, the model predictive control method can be used to calculate the control commands.

[0138] exist Figure 3 The figure shows the speed-time and distance-time diagrams for the leading and trailing train units under ideal control (following a recommended driving curve). The difference in stopping time between the two trains at the target platform is 1.6 seconds. Furthermore, experiments were conducted in the following three scenarios to demonstrate some of the benefits of the present invention.

[0139] The first scenario is that the following train is delayed for 5 seconds. If the control method of the present invention is not adopted and each train unit still runs according to its own recommended speed curve, the speed-time and distance-time relationships of the leading and trailing trains are as follows: Figure 4 As shown in , the difference in the stopping time between the two vehicles at the target station is 7.2 seconds, which is 5.6 seconds longer than the baseline experiment.

[0140] If the virtual marshaling train tracking control system and method of the present invention is adopted, the speed-time and distance-time relationships of the front and rear trains are as follows: Figure 5 As shown in , the difference in the time it takes for the two vehicles to stop at the target platform is 2.8 seconds. When the speed of the following vehicle is higher than 8 m / s, function 4 is enabled. At this time, the calculated control target will add a speed adjustment amount based on the recommended driving curve. The adjustment time reserved in advance is 40 seconds, which means that the speed of the following vehicle after 40 seconds should be consistent with the benchmark test results. Figure 3 and Figure 4The results in also proved this.

[0141] The second scenario is that the cumulative value of the rear vehicle control error causes the two vehicles to be out of sync. If the control method described in the present invention is not adopted and each train unit still runs according to its own recommended speed curve, the speed-time and distance-time relationships of the front and rear vehicles are as follows: Figure 6 As shown in Figure 3, the difference in stopping time between the two trains at the target platform is 4.2 seconds. This indicates that during the initial traction phase, the trailing train runs slower than the leading train due to accumulated control errors. Because both trains are tracking their own recommended speed profiles, this error accumulates until the final stop, increasing the difference in stopping time.

[0142] If the virtual marshaling train tracking control system and method of the present invention is adopted, the speed-time and distance-time relationships of the front and rear trains are as follows: Figure 7 As shown in , the difference in the time it takes for the two vehicles to stop at the target platform is 1.2 seconds.

[0143] The third scenario is that the control error of the rear train causes it to run faster than the front train. In this case, the difference between the rear train speed and the EBI speed is smaller than that in the baseline experiment. If the control method described in the present invention is not adopted and each train unit still runs according to its own recommended speed curve, the speed-time and distance-time relationships of the front and rear trains are as follows: Figure 8 As shown in . The speed of the following vehicle is greater than the EBI speed at 17 seconds, so emergency braking is performed.

[0144] If the virtual marshaling train tracking control system and method of the present invention is adopted, the speed-time and distance-time relationships of the front and rear trains are as follows: Figure 9 As shown in . It can be seen that the difference between the rear vehicle speed and the EBI speed is relative to Figure 3 The results of the benchmark experiments are smaller, but relative to Figure 8 The result is greater, and no car behind does not brake suddenly due to speeding.

[0145] By Figure 4 and Figure 5 、 Figure 6 and Figure 7 as well as Figure 8 and Figure 9 By comparing the results in , it can be proved that the present invention has the following benefits:

[0146] (1) The present invention can effectively reduce the adverse effects of the delay of the following train in virtual marshaling, reduce the tracking spacing of virtual marshaling train units, and improve the synchronization of entering the station;

[0147] (2) The virtual marshaling train controlled by the present invention can meet safety protection conditions, avoid triggering emergency braking, and ensure the stability of virtual marshaling operation.

[0148] Example 2

[0149] Embodiment 2 of the present invention provides a virtual marshaling train tracking control system, which is applied to the above method and includes:

[0150] A status acquisition module is used to obtain the actual status of each train unit in the virtual marshaling in the current cycle;

[0151] a first judgment module, configured to determine whether to execute a backup control strategy based on the actual state of each train unit in the current cycle and a target state sequence of a first preset number of cycles before the current moment, and obtain a first judgment result; the backup control strategy includes a control strategy for tracking the driving curve of the first train unit and a control strategy for tracking the i-th train unit of the i+1-th train unit, where the value of i is greater than or equal to 1;

[0152] a first control module, configured to execute a backup control strategy to control each train unit if the first judgment result is yes;

[0153] A second judgment module is configured to, if the first judgment result is negative, judge whether the synchronization of each train unit in the virtual marshaling satisfies a preset condition to obtain a second judgment result;

[0154] a first target state sequence calculation module, configured to calculate the target state sequence of each train unit in the current cycle according to the actual state of each train unit in the current cycle according to the position, if the second judgment result indicates yes;

[0155] a second state sequence calculation module, configured to calculate a target state sequence of each train unit in the current cycle using a synchronization relationship based on the actual state of each train unit in the current cycle if the second judgment result indicates no;

[0156] The second control module is used to control each train unit according to the target state sequence of the current cycle of each train unit.

[0157] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0158] A computer-readable storage medium stores a computer program, which implements the above method when executed.

[0159] The beneficial effects of the technical solution of the present invention based on the above embodiments are:

[0160] Under normal circumstances, the present invention uses the recommended driving curve as the control target. Under disturbance conditions, it can actively and adaptively adjust the real-time control target based on the recommended driving curve. Then, control commands are calculated and output to the train based on the control target. Therefore, the present invention can control the virtual marshaling train units to enter the station synchronously in the presence of disturbances and avoid the following train triggering emergency braking due to overspeeding.

[0161] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0162] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A virtual train tracking control method, characterized in that: The method comprises the following steps: Get the actual status of the current cycle of each train unit in the virtual formation; Based on the actual state of each train unit in the current cycle and the target state sequence of a first preset number of cycles before the current moment, determining whether to execute a backup control strategy to obtain a first determination result; the backup control strategy includes a control strategy for tracking the driving curve of the first train unit and a control strategy for tracking the i-th train unit of the i+1-th train unit, where the value of i is greater than or equal to 1; If the first judgment result is yes, then executing the backup control strategy to control each train unit; If the first judgment result is no, perform the following operations: Determining whether the synchronization of each train unit in the virtual marshaling satisfies a preset condition, and obtaining a second determination result; If the second judgment result indicates yes, then calculating the target state sequence of each train unit in the current cycle according to the actual state of each train unit in the current cycle according to the position; If the second judgment result indicates no, then calculating the target state sequence of each train unit in the current cycle using the synchronization relationship according to the actual state of each train unit in the current cycle; Each train unit is controlled according to the target state sequence of the current cycle of each train unit.

2. The virtual train tracking control method according to claim 1, characterized in that: The determining whether to execute the backup control strategy based on the actual state of each train unit in the current cycle and the target state sequence of a first preset number of cycles before the current moment to obtain the first determination result specifically includes: Determine whether the flag bit of the first cycle before the current moment is displayed normally, and obtain a third determination result; If the third judgment result indicates yes, then determine whether the difference between the actual speed of the current cycle of each train unit and the first target speed in the target state sequence within n cycles before the current moment is less than the speed difference threshold; if the difference between the speed of the current cycle of each train unit and the first target speed in the target state sequence within n cycles before the current moment is less than the speed difference threshold, then determine that the first judgment result is yes, and set the flag bit of the current cycle to normal; otherwise, determine that the first judgment result is no, and set the flag bit of the current cycle to abnormal; If the third judgment result indicates no, then determine whether the difference between the actual speed of the current cycle of each train unit and the first target speed in the target state sequence within m cycles before the current moment is less than the speed difference threshold. If the difference between the speed of the current cycle of each train unit and the first target speed in the target state sequence within m cycles before the current moment is less than the speed difference threshold, then determine that the first judgment result is yes, and set the flag bit of the current cycle to normal; otherwise, determine that the first judgment result is no, and set the flag bit of the current cycle to abnormal, n and m are the values ​​of the first preset number in different situations, m≥n.

3. The virtual train tracking control method according to claim 1, characterized in that: The determining whether the synchronization of each train unit in the virtual marshaling satisfies a preset condition to obtain a second determination result specifically includes: When the time index deviations between any two adjacent train units in the virtual marshaling are less than the time index deviation threshold, determining that the second judgment result is yes; When the time index deviations between any two adjacent train units in the virtual formation are not all less than the time index deviation threshold, the second judgment result is determined to be no.

4. The virtual train tracking control method according to claim 1, characterized in that: The target state sequence of each train unit in the current cycle is calculated according to the actual state of each train unit in the current cycle, specifically including: According to the actual position and actual speed of each train unit in the current cycle, the initial target state is determined as: in, is the initial target position in the target state sequence of the current cycle of the i-th train unit, is the initial target speed in the target state sequence of the current cycle of the i-th train unit, s i,k and v i,k are the actual position and actual speed of the current cycle of the i-th train unit, V() is the calculation function of the target speed, and represent the qth and q+1th recommended position values ​​on the driving curve of the i-th train unit, respectively. and represents the qth and q+1th recommended speed values ​​on the driving curve of the i-th train unit, where I is the number of train units in the virtual formation; Based on the initial target position and the initial target speed, the target position and target speed in the target state sequence of the current cycle of each train unit are calculated based on the following formula; in, and are the j+1th target position and j+1th target speed in the target state sequence of the current cycle of the i-th train unit, and are the jth target position and jth target speed in the target state sequence of the current cycle of the i-th train unit, N is the number of target states in the target state sequence, τ is the sampling interval, is the calculation function of the target speed, and represent the pth and p+1th recommended position values ​​on the driving curve of the i-th train unit, respectively. and represents the pth and p+1th recommended speed values ​​on the driving curve of the i-th train unit; A differential calculation is performed on the target speed in the target state sequence of the current cycle of each train unit to obtain the target acceleration in the target state sequence of the current cycle of each train unit.

5. The virtual train tracking control method according to claim 1, characterized in that: The target state sequence of each train unit in the current cycle is calculated by using the synchronization relationship according to the actual state of each train unit in the current cycle, specifically including: According to the actual position and actual speed of each train unit in the current cycle, the initial target state of each train unit is determined as: in, is the initial target position in the target state sequence of the current cycle of the i-th train unit, s i,k is the actual position of the i-th train unit in the current cycle, and are the initial target speeds in the target state sequences of the 1st train unit and the i'th train unit in the current cycle, v a (0) is the adjustment amount of the initial target speed in the target state sequence of the current cycle of the i-th train unit, is the calculation function of the target speed, and represent the qth and q+1th recommended position values ​​on the driving curve of the i-th train unit, respectively. and represents the qth and q+1th recommended speed values ​​on the driving curve of the i-th train unit; I is the number of train units; Based on the initial target state, the target position and target speed in the target state sequence of the current cycle of each train unit are calculated based on the following formula; in, and are the j+1th target position and j+1th target speed in the target state sequence of the current cycle of the i-th train unit, and are the jth target position and jth target speed in the target state sequence of the current cycle of the i-th train unit, τ is the sampling interval, is the calculation function of the target speed, and represent the pth and p+1th recommended position values ​​on the driving curve of the i-th train unit, respectively. and represents the pth and p+1th recommended speed values ​​on the driving curve of the i-th train unit, v a (j) is the adjustment amount of the jth target speed in the target state sequence; A differential calculation is performed on the target speed in the target state sequence of the current cycle of each train unit to obtain the target acceleration in the target state sequence of the current cycle of each train unit.

6. The virtual train tracking control method according to claim 5, characterized in that: The calculation formula for the adjustment amount of the jth target speed in the target state sequence is: Among them, c a The number of cycles between the current cycle and the cycle where the distance is first adjusted by the adjustment amount, a a is the preset adjustment acceleration, τ is the sampling interval, Δv a is the maximum adjustment speed, T a Adjust the time for the preset.

7. The virtual train tracking control method according to claim 1, characterized in that: The controlling of each train unit according to the target state sequence of the current cycle of each train unit further includes: When the difference between the actual speed of each train unit and the EBI speed at a second preset number of moments between the previous moment and the current moment does not meet the preset condition, the following operations are performed: Adjust the target speed and target position in the target state sequence of the current cycle of each train unit based on the following formula; in, is the jth adjusted target speed in the target state sequence of the current cycle of the i-th train unit, and are the jth and j+1th adjusted target positions in the target state sequence of the current cycle of the i-th train unit, respectively. is the jth target speed in the target state sequence of the current cycle of the i-th train unit, k e is the compensation ratio coefficient, τ is the sampling interval, Δv e is the speed compensation, v i,l is the actual speed at the lth moment before the current moment, l-1 is the second preset number, is the EBI speed of the i-th train unit, v e is the EBI speed margin value; A differential calculation is performed on the adjusted target speed in the target state sequence of the current cycle of each train unit to obtain the adjusted target acceleration in the target state sequence of the current cycle of each train unit.

8. A virtual train tracking control system, characterized in that: The system is applied to the method according to any one of claims 1 to 7, and the system includes: A status acquisition module is used to obtain the actual status of each train unit in the virtual marshaling in the current cycle; a first judgment module, configured to determine whether to execute a backup control strategy based on the actual state of each train unit in the current cycle and a target state sequence of a first preset number of cycles before the current moment, and obtain a first judgment result; the backup control strategy includes a control strategy for tracking the driving curve of the first train unit and a control strategy for tracking the i-th train unit of the i+1-th train unit, where the value of i is greater than or equal to 1; a first control module, configured to execute a backup control strategy to control each train unit if the first judgment result is yes; A second judgment module is configured to, if the first judgment result is negative, judge whether the synchronization of each train unit in the virtual marshaling satisfies a preset condition to obtain a second judgment result; a first target state sequence calculation module, configured to calculate the target state sequence of each train unit in the current cycle according to the actual state of each train unit in the current cycle according to the position, if the second judgment result indicates yes; a second state sequence calculation module, configured to calculate a target state sequence of each train unit in the current cycle using a synchronization relationship based on the actual state of each train unit in the current cycle if the second judgment result indicates no; The second control module is used to control each train unit according to the target state sequence of the current cycle of each train unit.

9. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, which implements the method according to any one of claims 1 to 7 when executed.

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