A train stop control method and related device

Abstract

The present application discloses a train parking control method and related devices, which relate to the field of train automatic control technology, including: firstly, according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of the train braking, an equivalent model of the train braking system is established, and the parking accuracy and riding comfort are determined; then, according to the equivalent model of the train braking system, the parking accuracy and riding comfort, based on the adaptive terminal sliding mode control, a train parking controller is determined; finally, the train parking controller is used to control the train parking. Since the train parking controller is based on the adaptive terminal sliding mode control, the parking accuracy and riding comfort are taken into consideration, and therefore, precise train parking control can be achieved under the premise of ensuring passenger comfort and train operation safety.

Description

Technical Field

[0001] The present application relates to the technical field of train automatic control, and in particular to a train stop control method and related devices. Background Art

[0002] Automatic train control has been a research hotspot in recent years, and train stop control is an important part of automatic train control. Since trains run continuously for a long time, the number of passengers changes constantly, and the characteristics of each vehicle are different, the precise stopping of the train is subject to more interference and uncertainty. In order to achieve precise parking of the train, the train generally calculates the control curve, and the train uses different automatic train control methods to track the control curve to achieve the purpose of precise parking.

[0003] At present, the commonly used train automatic driving control methods mainly include PID (Proportional Integral Derivative) control algorithm, fuzzy control algorithm and adaptive control algorithm. Among them, it is difficult to determine the coefficients of the PID control algorithm in application. At the same time, due to its fixed parameters, it has poor anti-interference ability to external disturbances and model loss, and the PID control command switches frequently and the work is complicated, and the parking accuracy and stability are poor. The fuzzy control algorithm has strong learning ability, and offline learning has great advantages in effectively adjusting the algorithm parameters, but the algorithm lacks real-time performance. The adaptive control algorithm can correct the uncertainty online and better solve the adverse effects caused by system uncertainty, but the current adaptive algorithm needs to establish an appropriate and accurate model, and the model selection has a great influence on the parking accuracy.

[0004] Therefore, how to provide a train stop control method to improve the accuracy of train stop has become a technical problem that needs to be urgently solved by those skilled in the art. Summary of the invention

[0005] In view of the above problems, the present application provides a train parking control method and related devices to achieve the purpose of improving the accuracy of train parking. The specific scheme is as follows:

[0006] The first aspect of the present application provides a train stop control method, comprising:

[0007] According to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of train braking, an equivalent model of train braking system is established;

[0008] Determine parking accuracy and ride comfort;

[0009] Determining a train parking controller based on the adaptive terminal sliding mode control according to the equivalent model of the train braking system, the parking accuracy and the riding comfort;

[0010] The train stop controller is used to control the train stop.

[0011] In a possible implementation, establishing an equivalent model of a train braking system according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of train braking includes:

[0012] Establish a train electric brake system model;

[0013] Establish a train air brake system model;

[0014] An equivalent model of the train braking system is established based on the train electric braking system model and the train air braking system model.

[0015] In a possible implementation, the determining of parking accuracy and riding comfort includes:

[0016] Establish a train traction calculation model;

[0017] The parking accuracy and the riding comfort are determined based on the train traction calculation model.

[0018] In a possible implementation, determining the train parking controller based on the adaptive terminal sliding mode control according to the train braking system equivalent model, the parking accuracy and the riding comfort includes:

[0019] A non-singular terminal sliding mode control model is established according to the train braking system equivalent model, the parking accuracy and the riding comfort;

[0020] Replacing the linear sliding mode of the non-singular terminal sliding mode control model with the nonlinear sliding mode to obtain the replaced non-singular terminal sliding mode control model, so as to obtain the initial input of the train stop controller;

[0021] Based on the initial input of the train stop controller, performing a weakened chattering process and an optimized stabilization process on the replaced non-singular terminal sliding mode control model to obtain an optimized input of the train stop controller;

[0022] Based on adaptive terminal sliding mode control, the parameters of the replaced non-singular terminal sliding mode control model are adaptively adjusted to obtain an adaptive terminal sliding mode control model, the gain of the adaptive terminal sliding mode control model is dynamically switched using fuzzy control, and the train stop controller with the target acceleration of train braking as the output is set according to the optimized input of the train stop controller.

[0023] In a possible implementation, the performing of a weakened chattering process and an optimized stabilization process on the replaced non-singular terminal sliding mode control model includes:

[0024] Construct saturation function;

[0025] The saturation function is used to convert the dynamic mode control in the replaced non-singular terminal sliding mode control model into a quasi-sliding mode control.

[0026] In a possible implementation, the controlling the train to stop by using the train stop controller includes:

[0027] Determining a target acceleration for train braking using the train stop controller;

[0028] Get the actual acceleration of train braking;

[0029] Obtaining error compensation for train braking according to the actual acceleration of the train braking and the target acceleration of the train braking;

[0030] The target acceleration of the train braking is adjusted in real time by utilizing the error compensation of the train braking to achieve accurate parking of the train.

[0031] In a possible implementation, obtaining error compensation for train braking according to the actual acceleration of the train braking and the target acceleration of the train braking includes:

[0032] Get measurements of the system;

[0033] Estimate the current state based on the state at the previous moment and update the prior error covariance matrix;

[0034] The a priori error covariance matrix and the measured value of the system are used to update the Kalman gain, the system optimal state estimation and the error covariance; the error covariance is the error compensation of the train braking.

[0035] A second aspect of the present application provides a train stop control device, comprising:

[0036] A train braking system equivalent model building unit is used to build a train braking system equivalent model according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of the train braking;

[0037] A parking accuracy and riding comfort determination unit, used for determining parking accuracy and riding comfort;

[0038] A train stop controller determination unit, configured to determine a train stop controller based on an adaptive terminal sliding mode control according to the train brake system equivalent model, the parking accuracy and the riding comfort;

[0039] A parking control unit is used to control the parking of a train using the train parking controller.

[0040] In a possible implementation, the train braking system equivalent model establishing unit is specifically used to:

[0041] Establish a train electric brake system model;

[0042] Establish a train air brake system model;

[0043] An equivalent model of the train braking system is established based on the train electric braking system model and the train air braking system model.

[0044] In a possible implementation, the parking accuracy and riding comfort determination unit is specifically used to:

[0045] Establish a train traction calculation model;

[0046] The parking accuracy and the riding comfort are determined based on the train traction calculation model.

[0047] In a possible implementation, the train stop controller determination unit is specifically used to:

[0048] A non-singular terminal sliding mode control model is established according to the train braking system equivalent model, the parking accuracy and the riding comfort;

[0049] Replacing the linear sliding mode of the non-singular terminal sliding mode control model with the nonlinear sliding mode to obtain the replaced non-singular terminal sliding mode control model, so as to obtain the initial input of the train stop controller;

[0050] Based on the initial input of the train stop controller, performing a weakened chattering process and an optimized stabilization process on the replaced non-singular terminal sliding mode control model to obtain an optimized input of the train stop controller;

[0051] Based on adaptive terminal sliding mode control, the parameters of the replaced non-singular terminal sliding mode control model are adaptively adjusted to obtain an adaptive terminal sliding mode control model, the gain of the adaptive terminal sliding mode control model is dynamically switched using fuzzy control, and the train stop controller with the target acceleration of train braking as the output is set according to the optimized input of the train stop controller.

[0052] In a possible implementation, the train stop controller determination unit is specifically used to:

[0053] Construct saturation function;

[0054] The saturation function is used to convert the dynamic mode control in the replaced non-singular terminal sliding mode control model into a quasi-sliding mode control.

[0055] In a possible implementation, the parking control unit includes:

[0056] a target acceleration determination unit, used to determine a target acceleration of train braking using the train stop controller;

[0057] An actual acceleration determination unit, used to obtain the actual acceleration of train braking;

[0058] an error compensation determination unit, configured to obtain error compensation for train braking according to the actual acceleration of the train braking and the target acceleration of the train braking;

[0059] The adjustment unit is used to adjust the target acceleration of the train braking in real time by using the error compensation of the train braking to achieve accurate parking of the train.

[0060] In a possible implementation, the error compensation determination unit is specifically configured to:

[0061] Get measurements of the system;

[0062] Estimate the current state based on the state at the previous moment and update the prior error covariance matrix;

[0063] The a priori error covariance matrix and the measured value of the system are used to update the Kalman gain, the system optimal state estimation and the error covariance; the error covariance is the error compensation of the train braking.

[0064] The third aspect of the present application provides a computer program product, including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements the train stop control method of the first aspect or any implementation of the first aspect.

[0065] A fourth aspect of the present application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein:

[0066] The memory is used to store computer programs;

[0067] The processor is used to execute the computer program so that the electronic device can implement the train parking control method of the above-mentioned first aspect or any implementation method of the first aspect.

[0068] A fifth aspect of the present application provides a computer storage medium, which carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement the train stop control method of the above-mentioned first aspect or any implementation of the first aspect.

[0069] By means of the above technical scheme, the train parking control method and related devices provided by the present application first establish an equivalent model of the train braking system according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of the train braking, and determine the parking accuracy and riding comfort. Then, based on the equivalent model of the train braking system, the parking accuracy and riding comfort, the train parking controller is determined based on the adaptive terminal sliding mode control, and finally the train parking is controlled by the train parking controller. Since the train parking controller is based on the adaptive terminal sliding mode control, the parking accuracy and riding comfort are taken into consideration. Therefore, it can realize accurate train parking control under the premise of ensuring passenger comfort and train operation safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0071] Figure 1 A flow chart of a train stop control method provided in an embodiment of the present application;

[0072] Figure 2 A schematic diagram of the structure of a train stop control device provided in an embodiment of the present application;

[0073] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0074] The following describes the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. The terms used in the implementation method section of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0075] The embodiments of the present application are described below in conjunction with the accompanying drawings. Those skilled in the art will appreciate that, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0076] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, which is only to describe the distinction mode adopted by the objects of the same attributes when describing in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0077] The present application can be applied in the field of train automatic control technology. First, the application scenario of the present application is introduced.

[0078] With the emergence of the ATC (Automatic Train Control) system, trains have achieved automatic protection, automatic driving, and automatic monitoring. Among them, the ATO (Automatic Train Operation) system is an important subsystem of the ATC system. It can complete the control function of the train door opening and closing and automatic speed adjustment (including traction, cruising, coasting, braking and parking control), and realize automatic control of the main line and return line. For an ATC system, whether the train can stop accurately in the station directly affects the reliability of the entire system.

[0079] The basic idea of ​​the train control model used during the automatic driving process of the train is: under the premise of ensuring safety, the train control algorithm is used. The ATO subsystem combines the line information in the fixed database and the speed limit information from ATP (Automatic Train Protection) to calculate the most suitable train control curve. The train uses different train automatic driving control methods to track the train control curve to achieve the purpose of precise parking.

[0080] Specifically, when the train uses the train automatic driving control method to track the train control curve, the corresponding train control strategy can be determined according to the deviation between the actual speed of the train and the recommended speed corresponding to the train control curve: traction, braking or coasting. Among them, the train control curve can be a corresponding relationship curve between the distance between the train and the operating stop point and the recommended speed. The train control model will monitor the deviation between the current speed of the train and the recommended speed of the train control curve in real time, and adjust the current speed of the train by adjusting the output of the train control gear according to the range and trend of the deviation, so that the current speed of the train is within the deviation range.

[0081] Among them, during the driving process of the train, the basic train control strategy can specifically include the following points:

[0082] When the actual speed of the train on the current track is lower than the speed limit, and it is guaranteed that the train can also be lower than the speed limit when entering the next section, the traction gear can be output;

[0083] When the speed limit of the next section is lower than the current speed, the train needs to calculate the braking distance in advance and output the braking gear at the appropriate distance to ensure safe deceleration;

[0084] When the train is about to stop, it is necessary to output a reasonable brake gear to ensure that the train stops accurately and stably;

[0085] When the train has reached the ceiling speed, or is about to stop and the train speed is slow, it can output coasting to reduce energy consumption.

[0086] At present, the commonly used train automatic driving control methods mainly include PID (Proportional Integral Derivative) control algorithm, fuzzy control algorithm and adaptive control algorithm. Among them, it is difficult to determine the coefficients of the PID control algorithm in application. At the same time, due to its fixed parameters, it has poor anti-interference ability to external disturbances and model loss, and the PID control command switches frequently and the work is complicated, and the parking accuracy and stability are poor. The fuzzy control algorithm has strong learning ability, and offline learning has great advantages in effectively adjusting the algorithm parameters, but the algorithm lacks real-time performance. The adaptive control algorithm can correct the uncertainty online and better solve the adverse effects caused by system uncertainty, but the current adaptive algorithm needs to establish an appropriate and accurate model, and the model selection has a great influence on the parking accuracy.

[0087] It can be seen that the existing train automatic driving control method cannot guarantee the accuracy of train stopping.

[0088] In order to solve the above problems, the embodiment of the present application provides a train parking control method. The train parking control method of the embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0089] Reference Figure 1 , Figure 1 A flow chart of a train stop control method provided in an embodiment of the present application is shown as follows: Figure 1 As shown, a train stop control method provided in an embodiment of the present application may include steps S101 to S104, and these steps are described in detail below.

[0090] S101: establishing an equivalent model of the train braking system according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of the train braking;

[0091] The time delay characteristic refers to the time delay between the issuance of the braking command and its actual execution. This delay may be caused by a variety of factors, including signal transmission time, control system processing time, and actuator response time. In order to accurately simulate this time delay, a time delay link can be introduced into the model to reflect the time difference between command transmission and execution during the actual braking process. The air-electric separation characteristic refers to the working mechanism of air brakes and electric brakes in the train braking system. Air brakes are usually used for rapid deceleration, while electric brakes are used to maintain a certain deceleration. In the equivalent model, this characteristic can be reflected by modeling the dynamic characteristics of air brakes and electric brakes separately and considering the switching logic between them. This can better simulate the response of the braking system under different working conditions. The braking force output efficiency refers to the effectiveness of the braking system in actual applications, including the size and distribution of the braking force. In order to improve the accuracy of the model, the change of the braking force output efficiency can be considered in the equivalent model.

[0092] S102: Determine parking accuracy and riding comfort;

[0093] Parking accuracy is the difference between the actual parking position of the train and the reference parking position; ride comfort is an evaluation function related to the train acceleration.

[0094] S103: determining a train parking controller based on the adaptive terminal sliding mode control according to the train braking system equivalent model, the parking accuracy and the riding comfort;

[0095] S104: Using the train stop controller to control the train to stop.

[0096] The train parking control method provided in this embodiment first establishes an equivalent model of the train braking system according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of the train braking, and determines the parking accuracy and riding comfort. Then, based on the equivalent model of the train braking system, the parking accuracy and riding comfort, the train parking controller is determined based on the adaptive terminal sliding mode control, and finally the train parking is controlled by the train parking controller. Since the train parking controller is based on the adaptive terminal sliding mode control, the parking accuracy and riding comfort are taken into consideration, and therefore, the precise parking control of the train can be achieved under the premise of ensuring passenger comfort and train operation safety.

[0097] In another embodiment of the present application, a specific implementation method of establishing an equivalent model of a train braking system according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of train braking in step S101 is described, and the method may include the following steps:

[0098] S201: Establishing a train electric brake system model;

[0099] In this application, the train electric brake system model can be expressed as:

[0100]

[0101] in, is the derivative of the control acceleration output by the electric brake system at time t, τ is the response time constant of the brake system, is the control acceleration output by the electric brake system at time t, a t (t) is the target acceleration of the braking system at time t.

[0102] S202: Establishing a train air brake system model;

[0103] In this application, the train air brake system model can be expressed as:

[0104]

[0105] in, is the derivative of the control acceleration output by the air brake system at time t, τ is the response time constant of the brake system, is the control acceleration output by the air brake system at time t, a t (tT) is the target acceleration of the braking system at time (tT), and T is the system transmission delay.

[0106] S203: Establishing an equivalent model of the train braking system according to the train electric braking system model and the train air braking system model.

[0107] In this application, the equivalent model of the train braking system can be expressed as:

[0108]

[0109] in, is the derivative of the control acceleration output by the equivalent model of the train braking system at time t, is the maximum acceleration corresponding to the electric brake characteristic curve, is the maximum acceleration corresponding to the comprehensive braking characteristic curve.

[0110] It should be noted that the electric braking characteristic curve is a graph showing the relationship between the electric braking force and the speed of the train during the electric braking process. The acceleration corresponding to the electric braking characteristic curve can be obtained indirectly through Newton's second law based on the electric braking force corresponding to the speed. The maximum acceleration corresponding to the electric braking characteristic curve is the maximum value of the accelerations corresponding to the electric braking characteristic curve. The comprehensive braking characteristic curve describes the comprehensive braking force that the vehicle can achieve and its changing trend through the synergy of electric braking and air braking under different speed and load conditions. The acceleration corresponding to the comprehensive braking characteristic curve can be obtained indirectly through Newton's second law based on the comprehensive braking force corresponding to the speed. The maximum acceleration corresponding to the comprehensive braking characteristic curve is the maximum value of the accelerations corresponding to the comprehensive braking characteristic curve.

[0111] In another embodiment of the present application, a specific implementation method for determining the parking accuracy and the riding comfort in step S102 is described, and the method may include the following steps:

[0112] S301: Establishing a train traction calculation model;

[0113] In this application, the train traction calculation model can be expressed as:

[0114]

[0115] in, is the real-time position of the train, v(t) is the real-time speed of the train, is the train acceleration, F t (t) is the traction force provided by the train traction system, F b (t) is the braking force provided by the train braking system, W(t) is the total resistance experienced by the train, M(1+γ) is the total mass of the train, and γ is the train rotation mass coefficient.

[0116] S302: Determine the parking accuracy and the riding comfort based on the train traction calculation model.

[0117] In this application, parking accuracy can be expressed as:

[0118]

[0119] Where: PA is the parking accuracy, x end is the actual parking location, For reference parking location;

[0120] The riding comfort is expressed as:

[0121]

[0122] Among them: PC is the riding comfort, N is the total number of samples, k represents the kth sampling point, ak+1 is the train running acceleration corresponding to the k+1th sampling point, a k is the train running acceleration corresponding to the kth sampling point, and Δt is the sampling time step.

[0123] In another embodiment of the present application, a specific implementation method of determining the train parking controller based on the adaptive terminal sliding mode control according to the equivalent model of the train braking system, the parking accuracy and the riding comfort in step S103 is described, and the method may include the following steps:

[0124] S401: establishing a non-singular terminal sliding mode control model according to the train braking system equivalent model, the parking accuracy and the riding comfort;

[0125] S402: replacing the linear sliding mode of the non-singular terminal sliding mode control model with the non-linear sliding mode to obtain the replaced non-singular terminal sliding mode control model, so as to obtain the initial input of the train stop controller;

[0126] In the present application, since the train control system is nonlinear and the sliding mode of the non-singular terminal sliding mode control model is linear, the linear sliding mode of the non-singular terminal sliding mode control model is replaced by a nonlinear sliding mode.

[0127] In the present application, the initial input of the train stop controller can be calculated based on the replaced non-singular terminal sliding mode control model and the current state of the system. The current state of the system is the current position speed and reference position speed of the train.

[0128] S403: Based on the initial input of the train stop controller, performing a weakened chattering process and an optimized stabilization process on the replaced non-singular terminal sliding mode control model to obtain an optimized input of the train stop controller;

[0129] In the present application, a saturation function can be constructed; the saturation function is used to convert the dynamic mode control in the replaced non-singular terminal sliding mode control model into a quasi-sliding mode control to weaken the vibration processing and optimize the stability processing, so as to obtain the optimized input of the train stop controller.

[0130] In this application, the saturation function can be:

[0131]

[0132] S404: Based on adaptive terminal sliding mode control, the parameters of the replaced non-singular terminal sliding mode control model are adaptively adjusted to obtain an adaptive terminal sliding mode control model, the gain of the adaptive terminal sliding mode control model is dynamically switched using fuzzy control, and the train stop controller with the target acceleration of train braking as the output is set according to the optimized input of the train stop controller.

[0133] In another embodiment of the present application, a specific implementation method of controlling the train parking by using the train parking controller in step S104 is described, and the method may include:

[0134] S501: Determine the target acceleration of train braking by using the train stop controller;

[0135] In the present application, based on the adaptive terminal sliding mode control and in accordance with the parking accuracy and the riding comfort, a train stopping controller with the target acceleration of train braking as output can be set to determine the target acceleration of train braking.

[0136] S502: Acquire the actual acceleration of train braking;

[0137] S503: Obtaining error compensation of train braking according to the actual acceleration of the train braking and the target acceleration of the train braking;

[0138] S504: Using the error compensation of the train braking, the target acceleration of the train braking is adjusted in real time to achieve accurate parking of the train.

[0139] In another embodiment of the present application, a specific implementation method of obtaining error compensation for train braking according to the actual acceleration of the train braking and the target acceleration of the train braking in step S503 is described, and the method may include:

[0140] S601: Obtaining system measurement values;

[0141] In this application, the measurements of the system are expressed as:

[0142]

[0143] Where: Z k is the measured value of the system, H is the observation matrix, X k is the state variable of the system, To measure noise;

[0144] S602: Estimate the current state according to the state at the previous moment and update the prior error covariance matrix;

[0145] In this application, the prior error covariance matrix is ​​expressed as:

[0146]

[0147] in: is the prior estimate of the state variable, is the optimal estimate of the state variables at the previous moment, A is the first system parameter, B is the second system parameter, U k is the control quantity of the system, is the prior estimate of the error covariance, P k-1 is the error covariance of the previous moment, T is, and Q is the variance of the process noise; the first system parameter is the system state transfer matrix, which is used to describe how the state of the system is transferred from one moment to the next. It reflects the dynamic characteristics of the system. The second system parameter is the control input matrix, which is used to describe how the control input of the system affects the state variable.

[0148] In this application, the position, speed, and acceleration of the train can be selected as state variables; the system equation of the state variables is expressed as:

[0149]

[0150] Where: Δu is the change in the control output of the system, is the change in nominal basic resistance.

[0151] S603: Using the prior error covariance matrix and the measurement value of the system, the Kalman gain, the system optimal state estimation and the error covariance are updated; the error covariance is the error compensation of the train braking.

[0152] In this application, the Kalman gain, the system optimal state estimate and the error covariance can be expressed as:

[0153]

[0154]

[0155]

[0156] Where: K k is the Kalman gain, is the optimal state estimate of the system, P k is the error covariance.

[0157] A train stop control method provided by an embodiment of the present application is introduced above, and a device for executing the above train stop control method will be introduced below.

[0158] See also Figure 2 , Figure 2This is a schematic diagram of the structure of a train stop control device provided in an embodiment of the present application. Figure 2 As shown, the train stop control device comprises:

[0159] The train braking system equivalent model establishing unit 11 is used to establish the train braking system equivalent model according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of the train braking;

[0160] A parking accuracy and riding comfort determination unit 12, used to determine parking accuracy and riding comfort;

[0161] A train stop controller determination unit 13, configured to determine a train stop controller based on an adaptive terminal sliding mode control according to the train brake system equivalent model, the parking accuracy and the riding comfort;

[0162] The parking control unit 14 is used to control the parking of the train using the train parking controller.

[0163] In a possible implementation, the train braking system equivalent model establishing unit is specifically used to:

[0164] Establish a train electric brake system model;

[0165] Establish a train air brake system model;

[0166] An equivalent model of the train braking system is established based on the train electric braking system model and the train air braking system model.

[0167] In a possible implementation, the parking accuracy and riding comfort determination unit is specifically used to:

[0168] Establish a train traction calculation model;

[0169] The parking accuracy and the riding comfort are determined based on the train traction calculation model.

[0170] In a possible implementation, the train stop controller determination unit is specifically used to:

[0171] A non-singular terminal sliding mode control model is established according to the train braking system equivalent model, the parking accuracy and the riding comfort;

[0172] Replacing the linear sliding mode of the non-singular terminal sliding mode control model with the nonlinear sliding mode to obtain the replaced non-singular terminal sliding mode control model, so as to obtain the initial input of the train stop controller;

[0173] Based on the initial input of the train stop controller, performing a weakened chattering process and an optimized stabilization process on the replaced non-singular terminal sliding mode control model to obtain an optimized input of the train stop controller;

[0174] Based on adaptive terminal sliding mode control, the parameters of the replaced non-singular terminal sliding mode control model are adaptively adjusted to obtain an adaptive terminal sliding mode control model, the gain of the adaptive terminal sliding mode control model is dynamically switched using fuzzy control, and the train stop controller with the target acceleration of train braking as the output is set according to the optimized input of the train stop controller.

[0175] In a possible implementation, the train stop controller determination unit is specifically used to:

[0176] Construct saturation function;

[0177] The saturation function is used to convert the dynamic mode control in the replaced non-singular terminal sliding mode control model into a quasi-sliding mode control.

[0178] In a possible implementation, the parking control unit includes:

[0179] a target acceleration determination unit, used to determine a target acceleration of train braking using the train stop controller;

[0180] An actual acceleration determination unit, used to obtain the actual acceleration of train braking;

[0181] an error compensation determination unit, configured to obtain error compensation for train braking according to the actual acceleration of the train braking and the target acceleration of the train braking;

[0182] The adjustment unit is used to adjust the target acceleration of the train braking in real time by using the error compensation of the train braking to achieve accurate parking of the train.

[0183] In a possible implementation, the error compensation determination unit is specifically configured to:

[0184] Get measurements of the system;

[0185] Estimate the current state based on the state at the previous moment and update the prior error covariance matrix;

[0186] The a priori error covariance matrix and the measured value of the system are used to update the Kalman gain, the system optimal state estimation and the error covariance; the error covariance is the error compensation of the train braking.

[0187] The present application also provides an electronic device in an embodiment. Figure 3As shown, it shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic device in the embodiments of the present application may include but is not limited to fixed terminals such as mobile phones, notebook computers, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0188] like Figure 3 As shown, the electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. When the electronic device is powered on, various programs and data required for the operation of the electronic device are also stored in the RAM 603. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0189] Typically, the following devices may be connected to the I / O interface 605: an input device 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a memory card, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 An electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0190] An embodiment of the present application also provides a computer program product, including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any one of the train stop control methods provided in the embodiments of the present application.

[0191] A computer-readable storage medium is also provided in an embodiment of the present application. The computer storage medium carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any train stop control method provided in the embodiment of the present application.

[0192] It should also be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the device embodiments provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.

[0193] Through the description of the above implementation mode, the technicians in the field can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course, it can also be implemented by special hardware including special integrated circuits, special CPUs, special memories, special components, etc. In general, all functions completed by computer programs can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be various, such as analog circuits, digital circuits or special circuits. However, for the present application, software program implementation is a better implementation mode in more cases. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, a U disk, a mobile hard disk, a ROM, a RAM, a disk or an optical disk, etc., including a number of instructions to enable a computer device (which can be a personal computer, a training device, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0194] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0195] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, a computer, a training device, or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, training device, or data center. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

Claims

1. A train stop control method, characterized in that: include: According to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of train braking, an equivalent model of train braking system is established; Determine parking accuracy and ride comfort; Determining a train parking controller based on the adaptive terminal sliding mode control according to the equivalent model of the train braking system, the parking accuracy and the riding comfort; The train stop controller is used to control the train stop.

2. The method according to claim 1, characterized in that: The train braking system equivalent model is established according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of the train braking, including: Establish a train electric brake system model; Establish a train air brake system model; An equivalent model of the train braking system is established based on the train electric braking system model and the train air braking system model.

3. The method according to claim 1, characterized in that The determining of parking accuracy and riding comfort includes: Establish a train traction calculation model; The parking accuracy and the riding comfort are determined based on the train traction calculation model.

4. The method according to claim 1, characterized in that: The method of determining a train parking controller based on the train braking system equivalent model, the parking accuracy and the riding comfort and based on the adaptive terminal sliding mode control includes: A non-singular terminal sliding mode control model is established according to the train braking system equivalent model, the parking accuracy and the riding comfort; Replacing the linear sliding mode of the non-singular terminal sliding mode control model with the nonlinear sliding mode to obtain the replaced non-singular terminal sliding mode control model, so as to obtain the initial input of the train stop controller; Based on the initial input of the train stop controller, performing a weakened chattering process and an optimized stabilization process on the replaced non-singular terminal sliding mode control model to obtain an optimized input of the train stop controller; Based on adaptive terminal sliding mode control, the parameters of the replaced non-singular terminal sliding mode control model are adaptively adjusted to obtain an adaptive terminal sliding mode control model, the gain of the adaptive terminal sliding mode control model is dynamically switched using fuzzy control, and the train stop controller with the target acceleration of train braking as the output is set according to the optimized input of the train stop controller.

5. The method according to claim 4, characterized in that The performing of a weakened chattering process and an optimized stabilization process on the replaced non-singular terminal sliding mode control model includes: Construct saturation function; The saturation function is used to convert the dynamic mode control in the replaced non-singular terminal sliding mode control model into a quasi-sliding mode control.

6. The method according to claim 1, characterized in that The method of controlling the train to stop by using the train stop controller comprises: Determining a target acceleration for train braking using the train stop controller; Get the actual acceleration of train braking; Obtaining error compensation for train braking according to the actual acceleration of the train braking and the target acceleration of the train braking; The target acceleration of the train braking is adjusted in real time by utilizing the error compensation of the train braking to achieve accurate parking of the train.

7. The method according to claim 6, characterized in that The step of obtaining error compensation for train braking according to the actual acceleration of the train braking and the target acceleration of the train braking comprises: Get measurements of the system; Estimate the current state based on the state at the previous moment and update the prior error covariance matrix; The a priori error covariance matrix and the measured value of the system are used to update the Kalman gain, the system optimal state estimation and the error covariance; the error covariance is the error compensation of the train braking.

8. A train stop control device, characterized in that: include: A train braking system equivalent model building unit is used to build a train braking system equivalent model according to the time delay characteristics, air-electric separation characteristics and braking force output efficiency of the train braking; A parking accuracy and riding comfort determination unit, used for determining parking accuracy and riding comfort; A train stop controller determination unit, configured to determine a train stop controller based on an adaptive terminal sliding mode control according to the train brake system equivalent model, the parking accuracy and the riding comfort; A parking control unit is used to control the parking of a train using the train parking controller.

9. A computer program product, characterized in that It comprises computer-readable instructions, and when the computer-readable instructions are executed on an electronic device, the electronic device implements the train stop control method as described in any one of claims 1 to 7.

10. An electronic device, characterized in that: The method comprises at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the electronic device can implement the train stop control method as described in any one of claims 1 to 7.

Images