A dynamic real-time simulation method and system suitable for train differential control

Abstract

The application provides a kind of dynamics real-time simulation method and system suitable for train differentiation control.The system realizes real-time dynamics simulation under each working condition by quickly calculating the air brake working condition of differentiation control train.In addition, the instructions output by the differentiation control device in real time are dynamically calculated, and the dynamics indicators such as the coupler force of all locomotives and vehicles on the current running train can be displayed in real time. In addition, the maximum coupler force of all locomotives in the future distance and the position where the maximum coupler force occurs obtained by parallel computing are used as the basis for the optimization planning curve of the differentiation control device, so as to realize the online optimization of the dynamics performance of the differentiation control system and ensure the good coupler force performance of the train under differentiation control. In addition, through real-time simulation of the state of each locomotive, the dynamics response of the differentiation control train under abnormal state can be simulated in real time.

Description

Technical Field

[0001] This invention relates to the field of railway heavy-haul train simulation technology, and in particular to a real-time dynamic simulation method and system suitable for differentiated train control. Background Technology

[0002] Due to the long length and heavy load of heavy-haul combined trains, some trains are going uphill while others are going downhill on some undulating slopes, making the existing synchronous control system prone to excessive impulses. Furthermore, heavy-haul trains using automatic air braking systems experience braking delays, leading to significant impulses when using the existing synchronous control system on sections with recirculating air braking. Differential control systems, which can issue different commands to the master and slave cars separately, have gradually become a feasible means to reduce impulses in heavy-haul trains. However, due to the significant differences in control commands between the master and slave cars, improper control commands can easily result in excessive impulses and coupler forces. Direct field testing poses significant safety risks; therefore, the system's dynamic performance must be verified in the laboratory before conducting field tests.

[0003] The current dynamic calculation system for differentiated control has the following problems: (1) It can only perform calculations for traction electric circuit conditions, or use fluid calculation methods for air braking conditions, which takes a long time and cannot achieve rapid calculations for air braking conditions; (2) It can only perform offline simulations or post-simulations, and cannot be linked with differentiated control devices in real time, resulting in low verification efficiency; (3) It cannot perform dynamic simulation calculations in advance for the instructions of differentiated control planning, and differentiated control devices cannot perform online optimization of dynamic performance; (4) It cannot simulate the locomotive's operating status in real time, and cannot simulate the train's dynamic response under abnormal conditions. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a real-time dynamic simulation method and system suitable for train differential control.

[0005] In a first aspect, embodiments of the present invention provide a real-time dynamics simulation system suitable for differentiated train control, comprising a locomotive simulation module, a longitudinal dynamics real-time calculation module, a longitudinal dynamics multi-core parallel calculation module, and a differentiated control device, wherein:

[0006] The locomotive simulation module is used to simulate the key components of each locomotive on the train, obtain the actual locomotive status information of each locomotive on the train, and calculate the current actual operation commands of each locomotive on the train based on the current target operation commands of each locomotive on the train output by the differentiated control device. The locomotive includes the master control locomotive and the slave control locomotive, and the operation commands include traction commands, electric braking commands and air braking commands to control the operation of the train.

[0007] The longitudinal dynamics real-time calculation module is used to perform real-time calculations based on the current actual operating commands of each locomotive on the train, through a pre-established longitudinal dynamics model, to obtain the dynamic indicators of all locomotives and vehicles on the train.

[0008] The longitudinal dynamics multi-core parallel computing module is used to obtain the maximum coupler force of all locomotives and the location where the maximum coupler force occurs within a future distance based on the target maneuvering commands of each locomotive on the train over a future distance through longitudinal dynamics multi-core parallel computing.

[0009] The differentiated control device is used to replan the train's journey based on the train's route and location information, the actual locomotive status information of each locomotive on the train, and the maximum coupler force and the location where the maximum coupler force occurs for all locomotives over a future distance, to obtain the train's journey planning information. The journey planning information includes the train's target speed, target control command, and corresponding train position over the future distance. Based on the train's journey planning information, the device generates new target control commands for each locomotive on the train and sends them to the locomotive simulation module to calculate the new actual control commands for each locomotive.

[0010] In some implementations, each locomotive and rolling stock on the train in the longitudinal dynamics model has independent degrees of freedom; the process of calculating dynamic parameters through the longitudinal dynamics model includes:

[0011] The air braking system, locomotive traction system, environmental resistance, and coupler system are modeled separately to obtain the air braking system model, locomotive traction system model, environmental resistance model, and coupler system model.

[0012] Simulations were performed on the air braking system model, locomotive traction system model, environmental resistance model, and coupler system model to obtain the air braking force, traction electric braking force, environmental resistance, coupler force, and coupler displacement of each locomotive.

[0013] The relationship between the pneumatic braking force, traction electric braking force, environmental resistance, coupler force and coupler displacement of each locomotive is integrated into the longitudinal dynamic equation of the train, and iterative solution is performed to obtain the resultant force on the train, and the relative acceleration, relative velocity and relative displacement of the train are calculated.

[0014] The coupling forces at the front and rear of the train were calculated based on different coupling and buffer system models.

[0015] In some implementations, the air braking system model includes an empirical model, and the modeling process of the empirical model includes:

[0016] Test data of the brake cylinders of locomotives and vehicles under all delay scenario categories corresponding to the differentiated control type are obtained respectively; the delay scenario categories are divided according to the order of execution commands of the master locomotive and the slave locomotive and the length of the interval between execution commands.

[0017] The brake cylinder pressure curves for each locomotive and vehicle are determined based on the brake cylinder test data corresponding to the target differentiated control type.

[0018] Based on the time delay information of the actual operating commands of the master locomotive and slave locomotive, the corresponding differentiated operation type is determined, and then the brake cylinder pressure curve of each locomotive and car is matched according to the determined differentiated operation type.

[0019] Based on the obtained brake cylinder pressure curves of each locomotive and vehicle, the air braking force of all locomotives and vehicles is calculated using the air braking force calculation formula.

[0020] The step of determining the brake cylinder curves for each locomotive and vehicle based on the brake cylinder test data corresponding to the target differentiated control type includes: fitting the brake cylinder pressure curves to the brake cylinder test data for the first stage and the second stage of the initial pressurization, respectively. The fitting process includes:

[0021] When the brake cylinder is in the first stage of the initial pressurization, the brake cylinder test data is normalized in terms of time and value. Based on the current normalized braking time, the normalized brake cylinder pressure is calculated by the characteristic function of the first stage of normalized brake cylinder pressurization obtained after feature extraction based on the brake cylinder test data. After the locomotive performs anti-normalization processing on the normalized brake cylinder pressure by the maximum value of the first stage anti-normalization initialization, the current vehicle brake cylinder pressure is obtained.

[0022] When the brake cylinder is in the second stage of pressure increase, the characteristic values ​​of each brake cylinder position are initialized. These characteristic values ​​include the pressure increase time threshold, the smoothing time threshold, and the step amplification factor. When the braking time is greater than the smoothing time threshold, the brake cylinder is in the step pressure increase segment. It is determined whether the pressure increase time is greater than the preset pressure increase threshold. If the pressure increase time is greater than the preset pressure increase threshold, the smoothing time threshold is amplified by the step amplification factor. If the pressure increase time is less than or equal to the preset pressure increase threshold, it is further determined whether the steady-state pressure is exceeded. If the steady-state pressure is exceeded, the steady-state pressure is output and the pressure increase ends. If the steady-state pressure is not exceeded, the current vehicle brake cylinder pressure is output. Additionally, when the braking time is less than or equal to the smoothing time threshold, the brake cylinder pressure is fitted using the following formula:

[0023]

[0024] In the formula, α is the leakage percentage, and t leak,maxThis is the maximum leakage time; after this time, the brake cylinder pressure will remain stable. leak,i The duration of the current smooth phase and steady-state phase for the i-th locomotive.

[0025] In some implementations, the locomotive simulation module has built-in locomotive simulation software. The locomotive simulation software is used to simulate the locomotive braking system, traction system, high-voltage equipment, auxiliary system and low-voltage equipment of each locomotive to obtain the actual locomotive status information of each locomotive. The locomotive simulation software includes master control locomotive simulation software and slave control locomotive simulation software.

[0026] In some implementations, the longitudinal dynamics real-time calculation module further includes:

[0027] After initializing the longitudinal dynamic parameters, determine whether the simulation type is real-time simulation mode. Real-time simulation mode is a simulation time to actual time ratio of 1:1.

[0028] If the simulation type is real-time simulation mode, then it includes:

[0029] Record the current initial local time, and initialize the current local time and the time difference between the current local time and the initialized local time;

[0030] Enter the main simulation loop. In the main simulation loop, first determine whether the number of iterations for the current longitudinal dynamics calculation is less than the total number of iterations.

[0031] If the current number of iterations in the longitudinal dynamics calculation is less than or equal to the total number of iterations, then it is further determined whether the time difference between the current local time and the initial local time is less than the virtual time of the current iteration, which is calculated based on the current number of iterations; if the time difference between the current local time and the initial local time is less than the virtual time of the current iteration, then the determination is continued until the time difference between the current local time and the initial local time is greater than or equal to the virtual time of the current iteration, then the longitudinal dynamics iterative calculation is performed first, then the number of iterations and the virtual time are updated, and then it is determined whether the number of iterations in the longitudinal dynamics calculation is less than the total number of iterations.

[0032] If the current number of iterations in the longitudinal dynamics calculation exceeds the total number of iterations, then release the memory and end the longitudinal dynamics simulation.

[0033] In some implementations, based on the target maneuvering commands of each locomotive on the train over a future distance, the maximum coupler force of all locomotives and the location where the maximum coupler force occurs over the future distance are obtained through longitudinal dynamics multi-core parallel calculations, including:

[0034] Initialize the master core and slave core, wherein the slave core supports dynamic simulation calculations for one or more locomotives;

[0035] The master core sends initialization parameters to all slave cores, the initialization parameters including the coupling force between vehicles;

[0036] After receiving the initialization parameters, each slave core performs a parallel dynamic simulation. After the slave core finishes its calculation at the current time step, it sends the calculated locomotive displacement and velocity back to the master core.

[0037] The master core calculates the coupler force based on the locomotive displacement and speed returned by the slave core and determines the next time step for simulation. Then, it sends the calculated coupler force to the slave core. At the same time, it counts the maximum coupler force and the location of the maximum coupler force in each time step, and compares the maximum coupler force in the current time step with the maximum coupler force in the previous time step, saving the larger value.

[0038] Until the simulation time for a certain distance in the future ends, the main kernel obtains the maximum coupler force of all locomotives within that distance and the location where the maximum coupler force occurs.

[0039] In some implementations, the system further includes a current coupler force display module for receiving and displaying the current dynamic parameters of all locomotives and vehicles on the train sent by the longitudinal dynamics real-time calculation module.

[0040] Secondly, embodiments of the present invention provide a real-time dynamic simulation method suitable for train differentiated control, comprising:

[0041] The key components of each locomotive on the train are simulated to obtain the actual locomotive status information of each locomotive, including the master locomotive and the slave locomotive;

[0042] Based on the current target control commands of each locomotive on the train, calculate the current actual control commands of each locomotive on the train. The control commands include traction commands, electric braking commands, and air braking commands to control the operation of the train.

[0043] Based on the current actual operating commands of each locomotive on the train, the current dynamic indicators of all locomotives and vehicles on the train are obtained through real-time calculation using a pre-established longitudinal dynamics model.

[0044] Based on the target maneuvering commands of each locomotive on the train over a future distance, the maximum coupler force of all locomotives and the location where the maximum coupler force occurs are obtained through longitudinal dynamics multi-core parallel calculation.

[0045] Based on the train's route and location information, the actual locomotive status information of each locomotive on the train, and the maximum coupler force of all locomotives and the location where the maximum coupler force occurs over a future distance, the train's journey is re-planned to obtain the train's journey planning information. The journey planning information includes the train's target speed, target control command, and corresponding train position over a future distance.

[0046] Based on the train's travel planning information, new target control commands are generated for each locomotive on the train to calculate the new actual control commands for each locomotive.

[0047] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by at least one processor, implements the method described in the second aspect.

[0048] Fourthly, embodiments of the present invention provide an electronic device, including a memory and at least one processor, wherein the memory stores a computer program, and the computer program, when executed by the at least one processor, implements the method as described in the second aspect.

[0049] One or more embodiments of the present invention provide at least the following beneficial effects:

[0050] This invention achieves real-time dynamic simulation under various operating conditions by rapidly calculating the air braking conditions of differentiated control trains. Furthermore, it performs dynamic calculations on the real-time output commands of the differentiated control device, displaying dynamic indicators such as coupler forces for all locomotives and cars on the currently operating train. Additionally, the maximum coupler forces of all locomotives and their locations over a future distance, obtained through parallel computing, serve as the basis for optimizing the planning curve of the differentiated control device, enabling online optimization of the dynamic performance of the differentiated control system and ensuring good coupler force performance for cars under differentiated control. Moreover, real-time simulation of the states of each locomotive allows for real-time simulation of the train's dynamic response under abnormal conditions. Attached Figure Description

[0051] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope.

[0052] Figure 1 A framework diagram of a real-time dynamic simulation system suitable for differentiated train control is provided in this embodiment of the invention.

[0053] Figure 2 This is a schematic diagram illustrating the working principle of the locomotive simulation software simulating the actual state of a locomotive, as provided in this embodiment of the invention.

[0054] Figure 3 This is a flowchart of the longitudinal dynamics calculation of a train using a multi-mass model provided in an embodiment of the present invention.

[0055] Figure 4 This is a schematic diagram of the pressure rise curve of the basic brake cylinder of a train locomotive provided in an embodiment of the present invention;

[0056] Figure 5 This is a schematic diagram of the fitting logic for the second stage of brake cylinder pressure boosting provided in an embodiment of the present invention;

[0057] Figure 6 This is a comparison chart of the simulation / experimental pressures of the basic brake cylinder of a train locomotive provided in an embodiment of the present invention;

[0058] Figure 7 A schematic diagram of the real-time dynamics calculation logic provided in an embodiment of the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0060] Example 1

[0061] The current dynamic calculation system for differentiated control has the following technical problems: (1) It can only perform calculations for traction electric circuit conditions, or use fluid calculation methods for air braking conditions, which takes a long time and cannot achieve rapid calculations for air braking conditions; (2) It can only perform offline simulations or post-simulations, and cannot be linked with differentiated control devices in real time, resulting in low verification efficiency; (3) It cannot perform dynamic simulation calculations in advance for the instructions of differentiated control planning, and differentiated control devices cannot perform online optimization of dynamic performance; (4) It cannot simulate the locomotive's operating status in real time, and cannot simulate the train's dynamic response under abnormal conditions.

[0062] To address the technical problems existing in current dynamics calculation systems for differentiated control, this application proposes a real-time dynamics simulation system suitable for train differentiated control, such as... Figure 1As shown, it includes a differentiated control device, a locomotive simulation module, a longitudinal dynamics real-time calculation module, and a longitudinal dynamics multi-core parallel calculation module.

[0063] The locomotive simulation module is used to simulate the key components of each locomotive on the train, obtain the actual locomotive status information, and calculate the current actual operation commands of each locomotive based on the current target operation commands output by the differentiated control device. The locomotives include a master control locomotive and a slave control locomotive. The operation commands include traction commands, electric braking commands, and air braking commands to control train operation. The locomotive simulation module includes locomotive simulation software used to simulate all subsystems of the locomotive. It can simulate various normal and abnormal working scenarios and obtain the actual locomotive status information under various scenarios. The actual locomotive status information includes the locomotive's maximum traction / electric braking force, brake cylinder pressure, equalization cylinder pressure, and total cylinder pressure. In this embodiment, the locomotive simulation software includes master control locomotive simulation software and slave control locomotive simulation software, which respectively simulate the actual locomotive status of the master control locomotive and the slave control locomotive. The locomotive simulation module sends the calculated actual operating commands of each locomotive on the train to the longitudinal dynamics real-time calculation module. Simultaneously, it forwards the target operating commands for each locomotive over a future distance, output by the differentiated control device, to the longitudinal dynamics multi-core parallel calculation module. Furthermore, it feeds back the current dynamic indicators of all locomotives and vehicles from the longitudinal dynamics real-time calculation module to the differentiated control device. These dynamic indicators include data such as locomotive speed, traction / electric braking force, brake cylinder pressure, and train tail pressure. The locomotive's subsystems include the locomotive braking system, traction system, high-voltage equipment, auxiliary systems, and low-voltage equipment. The locomotive braking system includes brake cylinders, equalizing air cylinders, main air cylinders, main compressors, brake circuits, and parking brakes; the traction system includes main converters and traction motors; high-voltage equipment includes pantographs, main circuit breakers, main loop-breaking circuits, roof-mounted isolating switches, high-voltage transformers, and main transformers; auxiliary systems include auxiliary converters, auxiliary transformers, variable frequency and voltage loads, and constant frequency and constant voltage loads; low-voltage equipment includes I / O lines for sections A and B (driver's cab, engine room, and mechanical room), multiple-unit hardwires, and locomotive power supply. Taking a simulated actual locomotive condition under a motor malfunction scenario as an example, its working principle is as follows: Figure 2As shown. Upon receiving the locomotive's control commands, if the simulated motor malfunctions, the motor status detection is abnormal, indicating the motor is inoperable. The traction / electric braking force envelope is recalculated, where the traction / electric braking force envelope refers to the maximum traction electric braking force the train can exert at different speeds. Then, the actual traction electric braking force is calculated using adhesion, and the actual control command is determined based on this calculated actual traction electric braking force. If the simulated motor is normal, the motor status detection is normal. The existing traction / electric braking force envelope is queried, and the actual traction electric braking force is calculated using adhesion, and the actual control command is determined based on this calculated actual traction electric braking force.

[0064] The longitudinal dynamics real-time calculation module is used to perform real-time calculations based on the current actual operating commands of each locomotive on the train, using a pre-established longitudinal dynamics model, to obtain the current dynamic indicators of all locomotives and vehicles. These dynamic indicators include data such as coupler force, acceleration, speed, and tail pressure. The longitudinal dynamics real-time calculation module feeds back the speed, tail pressure, and other dynamic indicators of each locomotive to the corresponding locomotive simulation software, and sends the speed of each locomotive to the train operation record monitoring device.

[0065] In some embodiments, the system further includes a current coupler force display module, wherein the longitudinal dynamics real-time calculation module sends the current coupler force, acceleration, and other dynamic indicators of all locomotives and vehicles on the train to the current coupler force display module for display.

[0066] In some embodiments, the longitudinal dynamics model treats the train as a multi-point model, with each locomotive and rolling stock possessing independent degrees of freedom. The process of calculating dynamic parameters using the longitudinal dynamics model includes: firstly, modeling the air braking system, locomotive traction system, environmental resistance, and coupler system separately to obtain the air braking system model, locomotive traction system model, environmental resistance model, and coupler system model; then, simulating the air braking system model, locomotive traction system model, environmental resistance model, and coupler system model respectively to obtain the air braking force, traction electric braking force, environmental resistance, coupler force, and coupler displacement relationship for each locomotive; and then... Figure 3 As shown, the relationships between the aerodynamic braking force, traction electric braking force, environmental resistance, coupler force, and coupler displacement of each locomotive are integrated into the longitudinal dynamic equation of the train. An iterative solution is then performed to obtain the resultant force on the train, and the relative acceleration, relative velocity, and relative displacement of the train are calculated. Finally, the coupler forces at the front and rear of the train are calculated based on different coupler system models. The longitudinal dynamic equation of the train that needs to be solved is as follows:

[0067]

[0068] m i Let x be the mass of the i-th locomotive;i Let be the displacement of the i-th locomotive; For locomotive traction or electric braking force; Let i be the aerodynamic braking force of the i-th locomotive; The sum of the running resistances; Let be the coupling force between the i-th locomotive and the (i-1)-th locomotive; Let be the coupling force between the i-th locomotive and the (i+1)-th locomotive.

[0069] In some embodiments, the air braking system model includes an empirical model, and the modeling process of the empirical model includes:

[0070] S1: Obtain brake cylinder test data for locomotives and rolling stock under all delay scenario categories corresponding to the differentiated control category. The delay scenario categories are divided according to the order of execution commands from the master locomotive and slave locomotive, and the length of the interval between command executions. For example, if the slave locomotive executes a command after the master locomotive, it is category 1; if the master locomotive executes a command after the slave locomotive, it is category 2. For category 1, if the slave locomotive executes a command 1 second after the master locomotive, it is category 1; if the slave locomotive executes a command 2 seconds after the master locomotive, it is category 2. Specifically, for the scenarios involving differentiated control in air braking conditions, conduct air braking tests on heavy-haul trains to obtain brake cylinder test data for each locomotive and rolling stock under each scenario. During the specific test, the time range for the master locomotive to start braking before the slave locomotive is 0 to 6 seconds; the time range for the master locomotive to start braking after the slave locomotive is 0 to 10 seconds. The priority and delay times are rounded down, meaning there are 17 scenarios with the same decompression amount, requiring 17 sets of tests to obtain brake cylinder test data.

[0071] S2, determine the brake cylinder pressure curve for each locomotive and vehicle based on the brake cylinder test data corresponding to the target differentiated control category. The brake cylinder pressure curve is expressed as a function of the brake cylinder pressure changing with time.

[0072] Conventional brake cylinder models typically only fit or segmentally fit the brake cylinder pressure rise curve, resulting in a smooth curve with high linearity. However, the actual brake cylinder pressure curve is... Figure 4As shown, the pressure typically fluctuates dramatically, exhibiting pressure jumps and step-like increases, demonstrating high nonlinearity. Conventional brake cylinder models struggle to simulate this situation. This application segments the brake cylinder pressure curve based on observed characteristics, dividing it into two phases: the first phase of initial pressure increase, characterized by a pressure jump within approximately 5 seconds followed by a slight drop, and the second phase of pressure increase, which is a step-like increase. In some implementations, determining the brake cylinder pressure curve for each locomotive and vehicle based on the brake cylinder test data corresponding to the target differentiated control type includes: fitting the brake cylinder pressure curves to the brake cylinder test data for the first and second phases of initial pressure increase, respectively. The fitting process includes:

[0073] S21, when the brake cylinder is in the first stage of initial pressure increase, the brake cylinder test data is normalized in terms of time and value assignment. Based on the current normalized braking time, the normalized brake cylinder pressure is calculated using the characteristic function of the first stage of normalized brake cylinder pressure increase obtained after feature extraction from the brake cylinder test data. After the locomotive performs inverse normalization initialization and maximum assignment in the first stage, the normalized brake cylinder pressure is inversely normalized to obtain the current vehicle brake cylinder pressure. In the initial stage of the system, the characteristic values ​​of the brake cylinder at each position are initialized. During the simulation calculation, the normalized data is inversely normalized to obtain the brake cylinder pressure curve in the first stage of initial pressure increase. The calculation formula used is as follows:

[0074]

[0075] P nori,max Let t be the maximum amplitude value of the first-stage inverse normalization initialization for the i-th locomotive. si The duration of braking initiated when the i-th locomotive receives the braking wave air signal is t. nori,max P represents the maximum normalized time of the first stage of the brake cylinder pressurization of the i-th locomotive. nor This is the normalized brake cylinder pressure boosting first-stage characteristic function obtained after feature extraction from experimental data. This function obtains the normalized brake cylinder pressure based on the current normalized braking time, and then passes it through P... nori,max Inverse normalization is used to obtain the current brake cylinder pressure P of the locomotive and rolling stock. i .

[0076] S22, when the brake cylinder is in the second stage of pressurization, the characteristic values ​​of the brake cylinders at each position are initialized during the system initialization phase. These characteristic values ​​include the pressurization time threshold, the smoothing time threshold, the step amplification factor, and the pressurization slope. The specific correction process is as follows: Figure 5As shown, when the braking time is greater than the smoothing time threshold, the brake cylinder is in the stepped pressure increase phase. It checks whether the pressure increase time is greater than the preset pressure increase threshold. If the pressure increase time is greater than the preset pressure increase threshold, the smoothing time threshold is amplified by a stepped amplification factor. If the pressure increase time is less than or equal to the preset pressure increase threshold, it further checks whether the steady-state pressure is exceeded. If the steady-state pressure is exceeded, the steady-state pressure is output and the pressure increase ends. If the steady-state pressure is not exceeded, the current vehicle brake cylinder pressure is output. Additionally, when the braking time is less than or equal to the smoothing time threshold, the brake cylinder is in the pressure increase smoothing phase and the steady-state phase, which may result in a small amount of pressure leakage. The following calculation formula is used to fit the brake cylinder pressure:

[0077]

[0078] In the formula, α is the leakage percentage, and t leak,max This is the maximum leakage time; after this time, the brake cylinder pressure will remain stable. leak,i The duration of the current smooth phase and steady-state phase for the i-th locomotive.

[0079] After obtaining the brake cylinder pressure curves of the differentiated control scenarios of air braking conditions through segmented fitting, the empirical model of the air braking system is obtained by storing the curves.

[0080] In the relief condition, the pressure curve of the brake cylinder is clearly segmented and each segment has a high degree of linearity. It is sufficient to describe the pressure drop slope and inflection point of each segment based only on the test data.

[0081] Conventional train air braking system models often focus more on steady-state pressure and total pressure rise time, resulting in a relatively coarse description of the brake cylinder pressure rise curve characteristics, such as... Figure 6 As shown, the segmented fitting method proposed in this application can well simulate the stepped pressure increase characteristics of the brake cylinder. That is, the brake cylinder pressure curves of different times of the same brake cylinder are different. Therefore, the brake cylinder pressure increase curve only simulates the corresponding characteristics and does not deliberately constrain the brake cylinder pressure curve of a certain time to fit perfectly.

[0082] S3 determines the corresponding differentiated operation type based on the time delay information of the actual operation commands of the master locomotive and slave locomotive, and then matches the corresponding brake cylinder pressure curves of each locomotive and car according to the determined differentiated operation type.

[0083] S4. Based on the obtained brake cylinder pressure curves of each locomotive and vehicle, the air braking force of all locomotives and vehicles is calculated using the air braking force calculation formula, which is as follows:

[0084]

[0085] In the formula, d is the diameter of the brake cylinder piston, p z It is the brake cylinder pressure, ηz It is the transmission efficiency of the basic braking device, γ z It is the braking ratio, n z It is the number of brake cylinders, n k It is the number of brake shoes, f z It is the actual calculated coefficient of friction.

[0086] In some embodiments, after adopting a rapid calculation method for air braking, the longitudinal dynamics simulation time is faster than the actual time, requiring real-time calculation processing to achieve a simulation time to actual time ratio of 1:1. Therefore, as Figure 7 As shown, the longitudinal dynamics real-time calculation module also includes: after initializing the longitudinal dynamics parameters, determining whether the simulation type is real-time simulation mode. In real-time simulation mode, the ratio of simulation time to actual time is 1:1. If the simulation type is real-time simulation mode, then first recording the current initial local time (hour H0, minute M0, second S0, and millisecond MS0), and initializing the current local time and the time difference T between the current local time and the initialized local time. diff =0; then enter the main simulation loop. In real-time simulation mode, iterative calculations of longitudinal dynamics are performed repeatedly. In real-time simulation mode, the i-th iteration calculates a virtual time T = i·Δt, typically Δt = 0.001s, taking 1 millisecond as an example. Then, longitudinal dynamics calculations are performed. The virtual time is only used as a basis for control signal judgment. In the main simulation loop, it first checks whether the current iteration number of the longitudinal dynamics calculation is less than the total number of iterations. If the current iteration number of the longitudinal dynamics calculation is less than or equal to the total number of iterations, then before the iterative calculation, it is necessary to determine the local time (time H) after the end of the i-th dynamics iteration. i 、M i , seconds i and milliseconds (MS) i The time difference T between the initial local time and the time T diff Whether it is less than the virtual time of the current iteration, 1000·T milliseconds, where the virtual time is determined based on the current iteration number. Where: T diff =((60·H i +M i )·60+S i 1000+ MS i -(((60·H0+M0)·60+S0)·1000+MS0). If the time difference T between the current local time and the initialized local time is... diff If the virtual time is less than 1000·T milliseconds of the current iteration, then this judgment continues until the time difference T between the current local time and the initialized local time is reached. diffIf the virtual time of the current iteration is greater than or equal to 1000·T milliseconds, then the longitudinal dynamics iterative calculation is performed first, followed by updating the iteration count and virtual time; until the current iteration count of the longitudinal dynamics calculation exceeds the total iteration count, then the memory is released and the longitudinal dynamics simulation calculation ends. This method achieves a 1:1 iteration ratio between simulation time and actual time.

[0087] The longitudinal dynamics multi-core parallel computing module is used to obtain the maximum coupler force of all locomotives and the location where the maximum coupler force occurs within a future distance based on the target maneuvering commands of each locomotive on the train over a future distance through longitudinal dynamics multi-core parallel computing.

[0088] In some embodiments, based on the target maneuvering commands of each locomotive on the train over a future distance, the maximum coupler force of all locomotives and the location where the maximum coupler force occurs over the future distance are obtained through longitudinal dynamics multi-core parallel calculation, including:

[0089] The master and slave cores are initialized, with each slave core supporting dynamic simulation calculations for one or more locomotives. Specifically, a multi-core computer is used for parallel computing, with a master and slave core. The master core is responsible for communication with the slave cores, using an MPI (Message Passing Interface) parallel computing framework. The master core sends initialization parameters, including the coupler forces between the vehicles, to all slave cores. Each slave core performs parallel dynamic simulation upon receiving the initialization parameters. After completing its calculation at the current time step, each slave core sends the calculated locomotive displacement and velocity back to the master core. The master core calculates the coupler forces based on the locomotive displacement and velocity returned by the slave cores and determines the next time step for simulation. It then sends the calculated coupler forces back to the slave cores, simultaneously recording the maximum coupler force and its location within each time step, comparing the maximum coupler force in the current time step with the maximum coupler force in the previous time step, and saving the larger value. Until the simulation time for a certain distance in the future ends, the main core obtains the maximum coupler force of all locomotives within that distance and the location where the maximum coupler force occurs, and sends it to the differential control device.

[0090] The differentiated control device is used to replan the train's journey based on the train's route and location information, the actual locomotive status information of each locomotive on the train, and the maximum coupler force and the location where the maximum coupler force occurs for all locomotives over a future distance, to obtain the train's journey planning information. The journey planning information includes the train's target speed, target control command, and corresponding train position over the future distance. Based on the train's journey planning information, the device generates new current target control commands for each locomotive on the train and sends them to the locomotive simulation module to calculate the actual control commands for each locomotive.

[0091] The system provided in this embodiment is designed with master locomotive simulation software and slave locomotive simulation software to simulate the real-time states of the locomotive, such as actual available force and adhesion state, and to calculate the actual operating commands of the master and slave locomotives. Through real-time simulation of locomotive states, the system can simulate the dynamic response of the train under normal and abnormal conditions. Furthermore, based on the brake cylinder test data of differentiated control, an empirical model of the air braking system is established, enabling rapid calculation of the air braking conditions of the differentiated control train. In addition, the longitudinal dynamics real-time calculation module performs dynamic calculations on the commands output in real time by the differentiated control device and displays dynamic indicators such as coupler force. It can also output the train dynamic response of differentiated operating commands in real time, such as acceleration and coupler force. Furthermore, the system sends the future control commands planned by the differentiated control device to the longitudinal dynamics multi-core parallel calculation module, which feeds back the dynamic response of the future commands to the differentiated control device in real time. The differentiated control device uses this as a constraint to re-plan, achieving online optimization of the dynamic performance of the differentiated control system.

[0092] Example 2

[0093] This embodiment provides a real-time dynamic simulation method suitable for differentiated train control, including:

[0094] Step 1: Simulate the key components of each locomotive on the train to obtain the actual locomotive status information of each locomotive on the train, wherein the locomotive includes the master control locomotive and the slave control locomotive;

[0095] Step 2: Based on the current target control commands of each locomotive on the train, calculate the current actual control commands of each locomotive on the train. The control commands include traction commands, electric braking commands, and air braking commands to control the operation of the train.

[0096] Step 3: Based on the current actual operation commands of each locomotive on the train, real-time calculations are performed using a pre-established longitudinal dynamics model to obtain the current dynamic indicators of all locomotives and vehicles on the train; at the same time, based on the target operation commands of each locomotive on the train over a future distance, the maximum coupler force of all locomotives and the location where the maximum coupler force occurs are obtained through longitudinal dynamics multi-core parallel calculations.

[0097] Step 4: Based on the train's route and location information, the actual locomotive status information of each locomotive on the train, and the maximum coupler force of all locomotives and the location where the maximum coupler force occurs over a future distance, the train's journey is re-planned to obtain the train's journey planning information. The journey planning information includes the train's target speed, target control command, and corresponding train position over the future distance.

[0098] Step 5: Based on the train's travel planning information, generate new target control commands for each locomotive on the train to calculate the new actual control commands for each locomotive.

[0099] This embodiment is based on the system provided in Embodiment 1. The specific technical details are the same as in Embodiment 1, and will not be repeated here.

[0100] The method provided in this embodiment designs master control locomotive simulation software and slave control locomotive simulation software to simulate the real-time states of the locomotive, such as actual available force and adhesion state, and calculates the actual operating commands of the master control locomotive and slave control locomotive. Thus, through real-time simulation of locomotive state, the dynamic response of the train under normal and abnormal states can be simulated. Based on the brake cylinder test data of differentiated control, an empirical model of the air braking system is established, which can quickly calculate the air braking conditions of the differentiated control train. In addition, the longitudinal dynamics real-time calculation module performs dynamic calculations on the commands output in real time by the differentiated control device and displays dynamic indicators such as coupler force. It can also output the train dynamic response of differentiated operation commands in real time, such as acceleration and coupler force. Furthermore, the future control commands planned by the differentiated control device are sent to the longitudinal dynamics multi-core parallel calculation module, and the dynamic response of the future commands is fed back to the differentiated control device in real time. The differentiated control device uses this as a constraint to re-plan, realizing online optimization of the dynamic performance of the differentiated control system.

[0101] Example 3

[0102] This embodiment provides a computer-readable storage medium storing a computer program. When the computer program is executed by at least one processor, it implements the dynamic real-time simulation method for train differential control described in the foregoing embodiment.

[0103] The computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0104] Example 4

[0105] This embodiment provides an electronic device, including a memory and at least one processor. The memory stores a computer program, which, when executed by the at least one processor, implements the method of the aforementioned embodiment.

[0106] The processor can be implemented using an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a Microcontroller Unit (MCU), a microprocessor, or other electronic components, and is used to execute the real-time dynamic simulation method for train differentiated control described in the above embodiments.

[0107] Example 5

[0108] This embodiment provides a computer program product that, when run on a processor, executes the dynamic real-time simulation method for train differential control described in the foregoing embodiment.

[0109] In practical applications, computer program products can run on electronic devices.

[0110] In the several embodiments provided in this invention, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus and method embodiments described above are merely illustrative.

[0111] It should be noted that, in this document, the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0112] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and variations in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection for this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A real-time dynamic simulation system suitable for differentiated control of trains, characterized in that, It includes a locomotive simulation module, a real-time longitudinal dynamics calculation module, a multi-core parallel longitudinal dynamics calculation module, and a differentiated control device, among which: The locomotive simulation module is used to simulate the key components of each locomotive on the train, obtain the actual locomotive status information of each locomotive on the train, and calculate the current actual operation commands of each locomotive on the train based on the current target operation commands of each locomotive on the train output by the differentiated control device. The locomotive includes the master control locomotive and the slave control locomotive, and the operation commands include traction commands, electric braking commands and air braking commands to control the operation of the train. The longitudinal dynamics real-time calculation module is used to perform real-time calculations based on the current actual operating commands of each locomotive on the train, using a pre-established longitudinal dynamics model to obtain the current dynamic indicators of all locomotives and vehicles on the train. Each locomotive and vehicle on the train in the longitudinal dynamics model has independent degrees of freedom. The process of calculating the dynamic indicators using the longitudinal dynamics model includes: modeling the air braking system, locomotive traction system, environmental resistance, and coupler system respectively, obtaining air braking system model, locomotive traction system model, environmental resistance model, and coupler system model; simulating the air braking system model, locomotive traction system model, environmental resistance model, and coupler system model respectively, obtaining the air braking force, traction electric braking force, environmental resistance, coupler force, and coupler displacement relationship of each locomotive; integrating the air braking force, traction electric braking force, environmental resistance, coupler force, and coupler displacement relationship of each locomotive into the train longitudinal dynamics equation, performing iterative solutions to obtain the resultant force on the train, and calculating the relative acceleration, relative velocity, and relative displacement of the train; calculating the coupler force at the front and rear of the train based on different coupler system models; wherein, the train longitudinal dynamics equation is: ； For the first i The mass of the locomotive; For the first i The displacement of the locomotive; For locomotive traction or electric braking force; For the first i The air braking force of a locomotive; The sum of the running resistances; For the first i locomotive and the first i -1 locomotive coupler force; For the first i locomotive and the first i +1 locomotive coupler force; The longitudinal dynamics multi-core parallel computing module is used to obtain the maximum coupler force of all locomotives and the location where the maximum coupler force occurs within a future distance based on the target maneuvering commands of each locomotive on the train over a future distance using the MPI parallel computing framework. The differentiated control device is used to replan the train's journey based on the train's route and location information, the actual locomotive status information of each locomotive on the train, and the maximum coupler force and the location where the maximum coupler force occurs for all locomotives over a future distance, to obtain the train's journey planning information. The journey planning information includes the train's target speed, target control command, and corresponding train position over the future distance. Based on the train's journey planning information, the device generates new target control commands for each locomotive on the train and sends them to the locomotive simulation module to calculate the new actual control commands for each locomotive. The longitudinal dynamics real-time calculation module also includes: After initializing the longitudinal dynamic parameters, determine whether the simulation type is real-time simulation mode. Real-time simulation mode is a simulation time to actual time ratio of 1:

1. If the simulation type is real-time simulation mode, then it includes: Record the current initial local time, and initialize the current local time and the time difference between the current local time and the initialized local time; Enter the main simulation loop. In the main simulation loop, first determine whether the number of iterations for the current longitudinal dynamics calculation is less than the total number of iterations. If the current number of iterations in the longitudinal dynamics calculation is less than or equal to the total number of iterations, then it is further determined whether the time difference between the current local time and the initial local time is less than the virtual time of the current iteration, which is calculated based on the current number of iterations; if the time difference between the current local time and the initial local time is less than the virtual time of the current iteration, then the determination is continued until the time difference between the current local time and the initial local time is greater than or equal to the virtual time of the current iteration, then the longitudinal dynamics iterative calculation is performed first, then the number of iterations and the virtual time are updated, and then it is determined whether the number of iterations in the longitudinal dynamics calculation is less than the total number of iterations. If the current number of iterations in the longitudinal dynamics calculation exceeds the total number of iterations, then release the memory and end the simulation of the longitudinal dynamics model.

2. The real-time dynamic simulation system for train differentiated control according to claim 1, characterized in that, The air braking system model includes an empirical model, and the modeling process of the empirical model includes: Test data of the brake cylinders of locomotives and vehicles under all delay scenario categories corresponding to the differentiated control type are obtained respectively; the delay scenario categories are divided according to the order of execution commands of the master locomotive and the slave locomotive and the length of the interval between execution commands. Based on the brake cylinder test data corresponding to the target differentiated control type, the brake cylinder pressure curves for each locomotive and vehicle are determined. The brake cylinder pressure curves are expressed as a function of the brake cylinder pressure changing with time. Based on the time delay information of the actual operation commands of the master locomotive and slave locomotive, the corresponding differentiated operation type is determined, and then the brake cylinder pressure curve of each locomotive and car is obtained according to the determined differentiated operation type. Based on the obtained brake cylinder pressure curves of each locomotive and vehicle, the air braking force of all locomotives and vehicles is calculated using the air braking force calculation formula. The air braking force calculation formula is as follows: ； In the formula, d It is the diameter of the brake cylinder piston. It is the brake cylinder pressure. It refers to the transmission efficiency of the basic braking device. It is the braking ratio. It is the number of brake cylinders. It refers to the number of brake shoes. It is the actual calculated coefficient of friction; The step of determining the brake cylinder pressure curves for each locomotive and vehicle based on the brake cylinder test data corresponding to the target differentiated control type includes: fitting the brake cylinder pressure curves to the brake cylinder test data for the first stage of the initial pressurization and the second stage of the pressurization, respectively. The fitting process includes: When the brake cylinder is in the first stage of initial pressure increase, the brake cylinder test data is normalized in terms of time and value assignment. Based on the current normalized braking time, the normalized brake cylinder pressure is calculated using the characteristic function of the first stage of normalized brake cylinder pressure increase obtained after feature extraction from the brake cylinder test data. After the locomotive performs inverse normalization initialization and maximum assignment in the first stage, the normalized brake cylinder pressure is inversely normalized to obtain the current vehicle brake cylinder pressure. The calculation formula for the vehicle brake cylinder pressure when the brake cylinder is in the first stage of initial pressure increase is as follows: ； For the first i The maximum amplitude of the first-stage inverse normalization initialization of the locomotive. The duration of braking initiated when the i-th locomotive receives the braking wave air signal. For the first i The maximum normalized time for the first stage of brake cylinder pressurization on a locomotive. The first-stage normalized brake cylinder pressure-boosting feature function is obtained after feature extraction from experimental data. This function, based on the current normalized braking time, obtains the normalized brake cylinder pressure and then... Inverse normalization is used to obtain the current brake cylinder pressure of the locomotive and rolling stock. ; When the brake cylinder is in the second stage of pressure increase, the characteristic values ​​of each brake cylinder position are initialized. These characteristic values ​​include the pressure increase time threshold, the smoothing time threshold, and the step amplification factor. When the braking time is greater than the smoothing time threshold, the brake cylinder is in the step pressure increase segment. It is determined whether the pressure increase time is greater than the preset pressure increase threshold. If the pressure increase time is greater than the preset pressure increase threshold, the smoothing time threshold is amplified by the step amplification factor. If the pressure increase time is less than or equal to the preset pressure increase threshold, it is further determined whether the steady-state pressure is exceeded. If the steady-state pressure is exceeded, the steady-state pressure is output and the pressure increase ends. If the steady-state pressure is not exceeded, the current vehicle brake cylinder pressure is output. Additionally, when the braking time is less than or equal to the smoothing time threshold, the brake cylinder pressure is fitted using the following formula: ； In the formula, For the percentage of leakage, This is the maximum leakage time; after this time, the brake cylinder pressure will remain stable. For the first The duration of the current smooth and steady-state phases for each locomotive.

3. The real-time dynamic simulation system for train differentiated control according to claim 2, characterized in that, The locomotive simulation module has built-in locomotive simulation software, which is used to simulate the locomotive braking system, traction system, high-voltage equipment, auxiliary system and low-voltage equipment of each locomotive to obtain the actual locomotive status information of each locomotive. The locomotive simulation software includes master control locomotive simulation software and slave control locomotive simulation software.

4. The real-time dynamic simulation system for train differentiated control according to claim 1, characterized in that, Based on the target maneuvering commands of each locomotive on the train over a future distance, the MPI parallel computing framework is used to perform longitudinal dynamics multi-core parallel computation to obtain the maximum coupler force of all locomotives over the future distance and the location where the maximum coupler force occurs, including: Using the MPI parallel computing framework, a master core and slave cores are initialized, with the slave cores supporting dynamic simulation calculations for one or more locomotives; The master core sends initialization parameters to all slave cores, the initialization parameters including the coupling force between vehicles; After receiving the initialization parameters, each slave core performs a parallel dynamic simulation. After the slave core finishes its calculation at the current time step, it sends the calculated locomotive displacement and velocity back to the master core. The master core calculates the coupler force based on the locomotive displacement and speed returned by the slave core and determines the next time step for simulation. Then, it sends the calculated coupler force to the slave core. At the same time, it counts the maximum coupler force and the location of the maximum coupler force in each time step, and compares the maximum coupler force in the current time step with the maximum coupler force in the previous time step, saving the larger value. Until the simulation time for a certain distance in the future ends, the main kernel obtains the maximum coupler force of all locomotives within that distance and the location where the maximum coupler force occurs.

5. A real-time dynamic simulation system for train differentiated control according to claim 1, characterized in that, It also includes a current coupler force display module, which is used to receive and display the current dynamic indicators of all locomotives and vehicles on the train sent by the longitudinal dynamics real-time calculation module.

6. A real-time dynamic simulation method suitable for differentiated control of trains, characterized in that, include: The key components of each locomotive on the train are simulated to obtain the actual locomotive status information of each locomotive, including the master locomotive and the slave locomotive; Based on the current target control commands of each locomotive on the train, calculate the current actual control commands of each locomotive on the train. The control commands include traction commands, electric braking commands, and air braking commands to control the operation of the train. Based on the current actual operating commands of each locomotive on the train, the current dynamic indicators of all locomotives and vehicles on the train are obtained through real-time calculation using a pre-established longitudinal dynamics model. In the longitudinal dynamics model, each locomotive and rolling stock on the train possesses independent degrees of freedom. The process of calculating dynamic indicators through the longitudinal dynamics model includes: modeling the air braking system, locomotive traction system, environmental resistance, and coupler system respectively, obtaining the air braking system model, locomotive traction system model, environmental resistance model, and coupler system model; performing simulations on the air braking system model, locomotive traction system model, environmental resistance model, and coupler system model respectively, obtaining the air braking force, traction electric braking force, environmental resistance, coupler force, and coupler displacement relationship of each locomotive; integrating the air braking force, traction electric braking force, environmental resistance, coupler force, and coupler displacement relationship of each locomotive into the train longitudinal dynamics equation, performing iterative solutions to obtain the resultant force on the train, and calculating the relative acceleration, relative velocity, and relative displacement of the train; calculating the coupler force at the front and rear of the train based on different coupler system models; wherein, the train longitudinal dynamics equation is: ； For the first i The mass of the locomotive; For the first i The displacement of the locomotive; For locomotive traction or electric braking force; For the first i The air braking force of a locomotive; The sum of the running resistances; For the first i locomotive and the first i -1 locomotive coupler force; For the first i locomotive and the first i +1 locomotive coupler force; Based on the target maneuvering commands of each locomotive on the train over a future distance, the MPI parallel computing framework is used to obtain the maximum coupler force of all locomotives and the location where the maximum coupler force occurs over a future distance through longitudinal dynamic multi-core parallel computing. Based on the train's route and location information, the actual locomotive status information of each locomotive on the train, and the maximum coupler force of all locomotives and the location where the maximum coupler force occurs over a future distance, the train's journey is re-planned to obtain the train's journey planning information. The journey planning information includes the train's target speed, target control command, and corresponding train position over a future distance. Based on the train's travel planning information, new target control instructions are generated for each locomotive on the train to calculate the new actual control instructions for each locomotive. The method further includes: After initializing the longitudinal dynamic parameters, determine whether the simulation type is real-time simulation mode. Real-time simulation mode is a simulation time to actual time ratio of 1:

1. If the simulation type is real-time simulation mode, then it includes: Record the current initial local time, and initialize the current local time and the time difference between the current local time and the initialized local time; Enter the main simulation loop. In the main simulation loop, first determine whether the number of iterations for the current longitudinal dynamics calculation is less than the total number of iterations. If the current number of iterations in the longitudinal dynamics calculation is less than or equal to the total number of iterations, then it is further determined whether the time difference between the current local time and the initial local time is less than the virtual time of the current iteration, which is calculated based on the current number of iterations; if the time difference between the current local time and the initial local time is less than the virtual time of the current iteration, then the determination is continued until the time difference between the current local time and the initial local time is greater than or equal to the virtual time of the current iteration, then the longitudinal dynamics iterative calculation is performed first, then the number of iterations and the virtual time are updated, and then it is determined whether the number of iterations in the longitudinal dynamics calculation is less than the total number of iterations. If the current number of iterations in the longitudinal dynamics calculation exceeds the total number of iterations, then release the memory and end the simulation of the longitudinal dynamics model.

7. An electronic device, characterized in that, It includes a memory and at least one processor, wherein the memory stores a computer program that, when executed by the at least one processor, implements the method of claim 6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by at least one processor, implements the method as described in claim 6.

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