An Optimization Method for Generating Speed ​​Curves of High-Speed ​​Maglev Trains

Abstract

This invention discloses an optimized method for generating speed curves of high-speed maglev trains. At the start of speed curve calculation, based on movement authorization and temporary speed limit information, the target distance and roof speed of the speed curve are determined. An initial value for the discrete speed step size is set, and speed segments are sequentially set from roof speed to 0. Within each speed segment, the discrete speed step size with the smallest braking distance calculation error is selected. Through iteration, a set of discrete speed step sizes for all speed segments is obtained. The displacement of the train within the current speed segment and the remaining target distance of the train are obtained. If the remaining target distance of the train is positive, the discrete speed step size for the next speed segment is calculated; otherwise, the calculation is terminated, and a suitable discrete speed step size is selected to make the remaining target distance of the train zero. This method reduces the braking distance error in the overall speed curve calculation process and improves calculation accuracy without increasing computational complexity.

Description

Technical Field

[0001] This invention relates to the field of train operation control technology, and in particular to a method for generating and optimizing the speed curve of a high-speed maglev train. Background Technology

[0002] As the core of the rail transit system, the train operation control system is one of the key devices for ensuring train operation safety and improving train operation efficiency. The operation control system of the ultra-high-speed maglev system mainly uses ground control and supplemented by train control to achieve safety protection functions. The speed curve monitoring function is the core protection function of the operation control system. It calculates the allowable speed limit based on train data and track data, and then adopts a target-distance continuous speed control mode for speed protection. The calculation principle of the typical safety braking model is to directly calculate different types of safety braking curves by maintaining a safety protection distance before the target protection point and through train traction. However, the operating speed of the ultra-high-speed maglev system has increased to over 600 km / h, and a new traction braking scheme has been adopted. The generation time and tracking accuracy of the safety braking curve have increased, and new requirements have been placed on the calculation efficiency and accuracy of the safety braking curve. The higher the operating speed, the longer the train travels within the same time step. Therefore, the step size setting has a greater impact on the accuracy of the calculation results, the convergence of the function, and the calculation time. If the step size is too small, the algorithm converges too slowly and takes too long to calculate; if the step size is too large, the calculation accuracy is insufficient and it is difficult to meet the train's control precision requirements.

[0003] Speed ​​curve calculation is fundamental to speed monitoring. Considering engineering feasibility and equipment computational performance, current high-speed maglev systems use discrete step length methods to approximate the speed curve. When an ultra-high-speed maglev train applies emergency braking, the operation control system first safely disconnects the traction power supply system. Then, the onboard equipment activates the eddy current brakes to reduce the train's speed. When the train speed decreases to a certain level, the eddy current braking force weakens sharply, and the train activates its brake wear plates, clamping the guide rails for friction braking. When the train speed approaches a stop, the skids are lowered, the eddy current braking system is deactivated, the train detaches from its levitation state, and stops at an auxiliary stopping point relying on the friction between the skids at the bottom of the train and the track.

[0004] Therefore, researching a speed curve generation optimization method based on variable step size, and using quantitative analysis of the vehicle braking process and vehicle dynamics equations as a basis, compares the impact of different discrete time steps on emergency braking distance deviation and computational complexity by selecting different discrete time steps. Based on this, an optimization method is proposed to solve the discrete step size strategy set in the speed curve calculation process, which meets the control accuracy and computational efficiency requirements of ultra-high-speed maglev systems with operating speeds of 600 km / h and above. This has become an urgent problem to be solved. Summary of the Invention

[0005] The purpose of this invention is to provide an optimized method for generating speed curves of high-speed maglev trains. This method reduces braking distance errors in the overall speed curve calculation process and improves calculation accuracy without increasing computational complexity.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] A method for generating and optimizing the speed curve of a high-speed maglev train, the method comprising:

[0008] Step 1: When starting the speed curve calculation, determine the target distance and roof speed of the speed curve based on the movement authorization and temporary speed limit information, set the initial value of the discrete speed step size calculation, and set the speed segment sequentially from the roof speed to 0.

[0009] Step 2: In each speed segment, select the discrete speed step value with the smallest braking distance calculation error, and obtain the set of discrete speed step values ​​for all speed segments through iteration.

[0010] Step 3: Obtain the displacement of the train in the current speed segment and the remaining target distance of the train. When the remaining target distance of the train is positive, calculate the discrete speed step size for the next speed segment; otherwise, terminate the calculation and select an appropriate discrete speed step size to make the remaining target distance of the train 0.

[0011] Step 4: After the calculation is terminated, the velocity curve corresponding to the optimal discrete velocity step size strategy is obtained based on the set of discrete velocity step sizes for all velocity segments obtained in Step 2.

[0012] As can be seen from the technical solution provided by the present invention, the above method reduces the braking distance error in the overall speed curve calculation process and improves the calculation accuracy without increasing the computational complexity. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart illustrating the method for generating and optimizing the speed curve of a high-speed maglev train according to an embodiment of the present invention. Detailed Implementation

[0015] 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 some embodiments of the present invention, and not all embodiments, and do not constitute a limitation of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0016] The terms “including,” “comprising,” “containing,” “having,” or other similar semantic descriptions should be interpreted as non-exclusive inclusion. For example, “including a technical feature element (such as raw material, component, ingredient, carrier, dosage form, material, size, part, component, mechanism, device, step, process, method, reaction conditions, processing conditions, parameter, algorithm, signal, data, product or article of manufacture, etc.)” should be interpreted as including not only the expressly listed technical feature element, but also other technical feature elements that are not expressly listed and are well-known in the art.

[0017] like Figure 1 The diagram shown is a flowchart illustrating the method for generating and optimizing the speed curve of a high-speed maglev train according to an embodiment of the present invention. The method includes:

[0018] Step 1: When starting the speed curve calculation, determine the target distance and roof speed of the speed curve based on the movement authorization and temporary speed limit information, set the initial value of the discrete speed step size calculation, and set the speed segments sequentially from the roof speed to 0.

[0019] Step 2: In each speed segment, select the discrete speed step value with the smallest braking distance calculation error, and obtain the set of discrete speed step values ​​for all speed segments through iteration.

[0020] In this step, within each speed segment, the range of discrete speed step sizes with positive integer values ​​is determined based on the current speed.

[0021] By traversing all feasible discrete speed step values, the objective function that comprehensively considers the braking distance calculation error and the speed curve iteration calculation complexity is minimized. The discrete speed step value when the objective function is minimized is used as the discrete speed step value of the current speed segment.

[0022] Taking the i-th speed segment as an example, the objective function J, which comprehensively considers the braking distance calculation error and the complexity of the speed curve iterative calculation, is expressed as:

[0023]

[0024] Among them, J shift J represents the displacement deviation within the current velocity range. iterationdenoted as the expected number of feasible iterations; α is the weighting factor; i is the velocity segment number, initially set to 1. Given the current velocity, Δ j Let be the discrete velocity step size of the j-th velocity segment, where j is the velocity segment symbol in the summation formula, and j takes the value [1, i-1]; Δ represents the selectable discrete velocity step size, which takes the value of a positive integer. This is a temporary value for the discrete velocity step size of the i-th velocity segment during the iteration process; INT(·) is the floor function;

[0025] and S i,ideal These are the train displacements within the i-th speed segment calculated based on the discrete speed step size principle and the train displacements within the i-th speed segment calculated based on the ideal speed curve, respectively. The calculation formulas are as follows:

[0026]

[0027]

[0028] Where M is the train mass; F T (v) represents the resultant resistance force acting on the train, a function of velocity v. Within the i-th velocity segment, the range of velocity v is... The principle of discrete velocity step size calculation requires that the resultant force within the velocity segment be taken as the minimum value within the velocity segment to ensure safety. However, in the ideal velocity curve, the resultant force changes with the velocity v, and integrals are used for calculation.

[0029] The final objective function J is expressed as:

[0030]

[0031] Within the i-th velocity segment, the discrete velocity step size is temporarily set to... For positive integers, the discrete velocity step size is determined by iterating through all possible values ​​[1, v]. i To obtain the minimum value of the objective function J that comprehensively considers the braking distance calculation error and the iteration calculation complexity of the speed curve, the minimum value corresponds to... The discrete velocity step size Δ for the i-th velocity segment i .

[0032] In specific implementation, the objective function J adjusts the weighting factor α to adjust the weight of minimizing the braking distance calculation error in the decision optimization objective, thereby achieving the selection of different speed curve calculation accuracies. During model usage, the weighting factor α should be designed to maximize the expected number of overall feasible iterations J. iteration The deviation J of the displacement within the current velocity range shift The values ​​are of similar magnitude;

[0033] When it is necessary to improve the accuracy of the velocity curve calculation of the model, the weighting factor α can be reduced to increase the displacement deviation J within the current velocity segment. shift The weight in the overall objective function J, in special cases the weighting factor α = 0, that is, the number of iterations is not considered in the optimization process, only the displacement calculation deviation is minimized, so as to maximize the accuracy of the velocity curve calculation.

[0034] When it is necessary to reduce computational complexity, the weight factor α can be increased to improve the expected number of overall feasible iterations J. iteration The weight of the component in the overall objective function J is used to reduce the number of iterations and computational complexity without reducing computational accuracy.

[0035] Step 3: Obtain the displacement of the train in the current speed segment and the remaining target distance of the train. When the remaining target distance of the train is positive, calculate the discrete speed step size for the next speed segment; otherwise, terminate the calculation and select an appropriate discrete speed step size to make the remaining target distance of the train 0.

[0036] In this step, if the calculation is terminated, the current discrete velocity step size is set to [value]. Among them, v Top For the ceiling speed; Δ j Let be the discrete speed step size of the j-th speed segment, where j is the speed segment symbol in the summation formula, and j takes the value [1, i-1]. Ensure that the minimum speed of this speed segment is 0 and the remaining train target distance is 0. Define the current speed segment number i as ij. stop .

[0037] Step 4: After the calculation is terminated, the velocity curve corresponding to the optimal discrete velocity step size strategy is obtained based on the set of discrete velocity step sizes for all velocity segments obtained in Step 2.

[0038] In this step, the cumulative distance within each speed range is first calculated using the following formula:

[0039]

[0040] Where i is the speed section number; M is the train mass; F T (v) represents the resultant resistance force acting on the train, and its value ranges from v∈[v] in the i-th speed segment. i ,v i -Δ i ];Δ i Let be the discrete velocity step size of the i-th velocity segment;

[0041] Next, calculate the cumulative velocity from the velocity of 0 to the i-th velocity segment. Simultaneously calculate the corresponding cumulative distance. Δ jLet be the discrete velocity step size of the j-th velocity segment, where j is the velocity segment symbol in the summation formula, and j takes the value [1, i].

[0042] Perform the above calculations on the discrete velocity step size sets of all velocity segments obtained in step 2. When the cumulative velocity reaches the ceiling velocity v... Top Then, complete the calculations for all speed ranges;

[0043] Finally, the set of points obtained from the above operations is... Plotting this on a two-dimensional velocity-position plane yields the velocity curve corresponding to the optimal discrete velocity step size strategy; where i stop The speed section number is used when the remaining train target distance is 0.

[0044] It is worth noting that the contents not described in detail in the embodiments of the present invention belong to the prior art known to those skilled in the art.

[0045] To facilitate understanding, the method described in this invention will be explained in detail below using a specific application scenario as an example:

[0046] Step a: Receive movement authorization and temporary speed limit information, and determine the target distance S of the speed curve. EoA And the roof speed v Top .

[0047] Step b: Initialize the speed curve calculation, and define the current speed v0 as the ceiling speed v Top The velocity segment i is initialized to 1, and the 0th discrete velocity step Δ0 is defined to be 0.

[0048] Step c: Calculate the discrete velocity step size Δ used for the i-th velocity segment. i .

[0049] The specific process is as follows: First, calculate the current speed of the i-th speed. Δ j Let be the discrete velocity step size of the j-th velocity segment, where j is the velocity segment symbol in the summation formula, and j takes the value [1, i-1].

[0050] In this algorithm, the discrete velocity step size is a positive integer value, ranging from 1 to the highest achievable velocity within the current velocity segment, i.e.:

[0051]

[0052] At the start of the calculation for the i-th velocity segment, the discrete velocity step size is decided by considering both the displacement calculation accuracy and the overall computational complexity, so that the objective function J of the decision optimization within the current velocity segment reaches its minimum value.

[0053] In this embodiment of the invention, the objective function J is determined by the displacement deviation J within the current velocity segment. shift Expected number of overall feasible iterations J iteration Composed of a weighting factor α, when the discrete velocity step size takes a value of When the decision optimization objective function J is expressed as:

[0054]

[0055] Where INT(·) is the floor function. and S i,ideal These are the train displacement within the current speed section calculated based on the discrete speed step principle and the train displacement within the current speed section calculated based on the ideal speed curve, respectively. Their calculation formulas are as follows:

[0056]

[0057]

[0058] By traversing the integer set [1, v] i To obtain the minimum value of the objective function that comprehensively considers the calculation error of braking distance and the iterative calculation complexity of speed curve, the minimum value corresponds to... The numerical value serves as the discrete velocity step size Δ for the current velocity segment. i .

[0059] Step d: Determine the remaining train target distance If the value is greater than 0, then i = i + 1, return to step c, and calculate the discrete velocity step size for the next velocity segment; otherwise, the current discrete velocity step size is taken as... Proceed to step e.

[0060] Step e: End the calculation, generate the optimal discrete velocity step size strategy, and calculate the velocity-position curve.

[0061] Furthermore, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware, and the corresponding program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0062] In summary, by using the discrete speed step size decision in the speed curve calculation process described in the embodiments of the present invention, the discrete speed step size value with the smallest braking distance calculation error and without significantly increasing the complexity of iterative calculation is selected in each speed segment. Through iteration, a set of discrete speed step sizes from the roof speed to 0 can be obtained, thereby reducing the braking distance error in the overall speed curve calculation process and improving the calculation accuracy.

[0063] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims. The information disclosed in the background section is intended only to enhance the understanding of the overall background technology of the present invention and should not be construed as an admission or implication in any way that such information constitutes prior art known to those skilled in the art.

Claims

1. A method for optimizing the generation of speed curves for high-speed maglev trains, characterized in that, The method includes: Step 1: When starting the speed curve calculation, determine the target distance and roof speed of the speed curve based on the movement authorization and temporary speed limit information, set the initial value of the discrete speed step size calculation, and set the speed segment sequentially from the roof speed to 0. Step 2: In each speed segment, select the discrete speed step value with the smallest braking distance calculation error, and obtain the set of discrete speed step values ​​for all speed segments through iteration. The process of step 2 is as follows: Within each speed segment, the range of discrete speed step sizes with positive integer values ​​is determined based on the current speed. By traversing all feasible discrete speed step values, the objective function that comprehensively considers the braking distance calculation error and the speed curve iterative calculation complexity is minimized. The discrete speed step value when the objective function is minimized is used as the discrete speed step value of the current speed segment. The discrete speed step value set of all speed segments is obtained through iteration. Taking the i-th speed segment as an example, the objective function J, which comprehensively considers the braking distance calculation error and the complexity of the speed curve iterative calculation, is expressed as: Among them, J shift J represents the displacement deviation within the current velocity range. iteration denoted as the expected number of feasible iterations; α is the weighting factor; i is the velocity segment number, initially set to 1. Given the current velocity, Δ j Let be the discrete velocity step size of the j-th velocity segment, where j is the velocity segment symbol in the summation formula, and j takes the value [1, i-1]; Δ represents the selectable discrete velocity step size, which takes the value of a positive integer. This is a temporary value for the discrete velocity step size of the i-th velocity segment during the iteration process; INT(·) is the floor function; and S i,ideal These are the train displacements within the i-th speed segment calculated based on the discrete speed step size principle and the train displacements within the i-th speed segment calculated based on the ideal speed curve, respectively. The calculation formulas are as follows: Where M is the train mass; F T (v) represents the resultant resistance force acting on the train, a function of velocity v. Within the i-th velocity segment, the range of velocity v is... The final objective function J is expressed as: Within the i-th velocity segment, the discrete velocity step size is temporarily set to... For positive integers, the discrete velocity step size is determined by iterating through all possible values ​​[1, v]. i To obtain the minimum value of the objective function J that comprehensively considers the braking distance calculation error and the iteration calculation complexity of the speed curve, the minimum value corresponds to... The discrete velocity step size Δ for the i-th velocity segment i ; Step 3: Obtain the displacement of the train in the current speed segment and the remaining target distance of the train. When the remaining target distance of the train is positive, calculate the discrete speed step size for the next speed segment; otherwise, terminate the calculation and select an appropriate discrete speed step size to make the remaining target distance of the train 0. Step 4: After the calculation is terminated, the velocity curve corresponding to the optimal discrete velocity step size strategy is obtained based on the set of discrete velocity step sizes for all velocity segments obtained in Step 2.

2. The method for generating and optimizing the speed curve of a high-speed maglev train according to claim 1, characterized in that, The objective function J adjusts the weighting factor α to adjust the weight of minimizing the braking distance calculation error in the decision optimization objective, thereby enabling the selection of different speed curve calculation accuracies. Specifically, when it is necessary to improve the accuracy of the velocity curve calculation of the model, the value of the weighting factor α is reduced to increase the displacement deviation J within the current velocity segment. shift The proportion in the overall objective function J; When it is necessary to reduce computational complexity, the weight factor α is increased, thereby increasing the expected number of overall feasible iterations J. iteration The weight of the component in the overall objective function J is used to reduce the number of iterations and computational complexity without reducing computational accuracy.

3. The method for generating and optimizing the speed curve of a high-speed maglev train according to claim 1, characterized in that, In step 3, if the calculation is terminated, the current discrete velocity step size is set to [value]. Among them, v Top For the ceiling speed; Δ j Let be the discrete speed step size of the j-th speed segment, where j is the speed segment symbol in the summation formula, and j takes the value [1, i-1]. Ensure that the minimum speed of this speed segment is 0 and the remaining train target distance is 0. Define the current speed segment number i as ij. stop .

4. The method for generating and optimizing the speed curve of a high-speed maglev train according to claim 1, characterized in that, In step 4, the cumulative distance within each speed range is first calculated using the following formula: Where i is the speed section number; M is the train mass; F T (v) represents the resultant resistance force acting on the train, and its value ranges from v∈[v] in the i-th speed segment. i ,v i -Δ i ];Δ i Let be the discrete velocity step size of the i-th velocity segment; Next, calculate the cumulative velocity from the velocity of 0 to the i-th velocity segment. Simultaneously calculate the corresponding cumulative distance. Δ j Let be the discrete velocity step size of the j-th velocity segment, where j is the velocity segment symbol in the summation formula, and j takes the value [1, i]. Perform the above calculations on the discrete velocity step size sets of all velocity segments obtained in step 2. When the cumulative velocity reaches the ceiling velocity v... Top Then, complete the calculations for all speed ranges; Finally, the set of points obtained from the above operations is... Plotting this on a two-dimensional velocity-position plane yields the velocity curve corresponding to the optimal discrete velocity step size strategy; where i stop The speed section number is used when the remaining train target distance is 0.

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