Freight train load calculation method and device

Abstract

The application discloses a freight train load calculation method and device. It is related to the field of railway technology, and aims to improve the operation efficiency of the train. The main technical scheme of the application is as follows: obtaining a specified control parameter value; using a load calculation module to calculate the load of the freight train in real time based on the specified control parameter value and a freight train motion formula. The application is used for calculating the load of the freight train.

Description

Technical Field

[0001] This invention relates to the field of railway technology, and in particular to a method and apparatus for calculating the load of freight trains. Background Technology

[0002] In recent years, with the continuous development of society, freight railways have also been developing towards heavier loads and greater intelligence. Currently, various control algorithms for freight trains are based on information such as the freight train's load and number of cars to establish a motion model of the freight train, and then control the freight train according to the motion model.

[0003] Currently, a maximum load value is generally selected for freight trains. However, in actual operation, it is often difficult to obtain accurate train load information. Drivers need to manually input the load information during each formation, de-formation, and shunting task of freight trains, which seriously affects the efficiency of train operation. Therefore, the maximum load value is often selected. However, when the maximum load value is selected, the number of freight trains will also increase, but the actual load value of the freight train may not reach the maximum load value. This will greatly reduce the operating efficiency of freight trains. Summary of the Invention

[0004] In view of the above problems, the present invention provides a method and apparatus for calculating the load of freight trains, the main purpose of which is to improve the operating efficiency of trains.

[0005] To solve the above-mentioned technical problems, the present invention proposes the following solution:

[0006] In a first aspect, the present invention provides a method for calculating the load capacity of a freight train, the method comprising:

[0007] Obtain the specified control parameter values ​​and freight train motion formulas;

[0008] The load calculation module is used to calculate the load of the freight train in real time based on the specified control parameter values ​​and the freight train motion formula.

[0009] Secondly, the present invention provides a load calculation device for freight trains, the device comprising:

[0010] The parameter acquisition unit is used to acquire specified control parameter values ​​and freight train motion formulas.

[0011] The load calculation unit is used to calculate the load of the freight train in real time using the load calculation module, based on the specified control parameter values ​​obtained by the parameter acquisition unit and the freight train motion formula.

[0012] To achieve the above objectives, according to a third aspect of the present invention, a storage medium is provided, the storage medium including a stored program, wherein, when the program is executed, the device on which the storage medium is located executes the freight train load calculation method of the first aspect.

[0013] To achieve the above objectives, according to a fourth aspect of the present invention, a processor is provided for running a program, wherein the program executes the freight train load calculation method of the first aspect described above.

[0014] By employing the above technical solution, the present invention provides a method and apparatus for calculating the load of a freight train. This method can obtain the specified control parameter values ​​corresponding to the specified control parameters calculated by the control module. After the control module calculates the specified control parameter values, the load calculation module can be used to calculate the load of the freight train in real time based on the specified control parameter values ​​and the freight train motion formula. This eliminates the need for the driver to manually input the load, and does not rely on the maximum load value. Instead, the load calculation module performs the calculation in real time, obtaining the train load that best suits the current operating conditions of the freight train, thus effectively improving the train's operating efficiency.

[0015] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0016] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0017] Figure 1 A flowchart illustrating a method for calculating the load capacity of a freight train according to an embodiment of the present invention is shown.

[0018] Figure 2 A flowchart of another method for calculating the load of a freight train provided by an embodiment of the present invention is shown;

[0019] Figure 3 This diagram illustrates a block diagram of a load calculation device for a freight train according to an embodiment of the present invention.

[0020] Figure 4 A block diagram of another load calculation device for freight trains provided in an embodiment of the present invention is shown. Detailed Implementation

[0021] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0022] In recent years, with the continuous development of society, freight railways have also moved towards heavier loads and greater intelligence. Currently, various control algorithms for freight trains are based on establishing a motion model of the freight train using information such as its load and number of cars, and then controlling the freight train according to this motion model. On the one hand, a maximum load value is generally selected for freight trains because in practical applications, it is often difficult to obtain accurate train load information. Drivers need to manually input the load information for each formation and shunting task, which significantly increases operating and time costs. However, when selecting the maximum load value, the number of cars in the freight train also increases, but the actual load value may not reach the maximum, thus greatly reducing the operating efficiency of the freight train. Furthermore, using the maximum load value leads to a large error in the train motion formula, which is crucial for train operation; therefore, using the maximum load value severely affects the train's operating efficiency. On the other hand, stations often do not communicate train load and train formation information to drivers, and can only use the maximum load value. To address the aforementioned problems, this invention provides a method for calculating the load capacity of freight trains, the specific steps of which are as follows: Figure 1 As shown, it includes:

[0023] 101. Obtain the specified control parameter values ​​and the motion formula of the freight train.

[0024] In this invention, the execution entity on which the implementation is based is the Automatic Train Operation (ATO) system. The ATO system mainly includes eight functional modules, namely: input / output module, speed and distance measurement module, wireless communication module, data storage module, integrity monitoring module, curve planning module, control module, and load calculation module.

[0025] In practical operation, the input / output module can output traction / braking commands from the ATO system to the train. It is also responsible for collecting information such as the traction handle position, steering handle status, brake cylinder pressure, and driver's cab status, which can then be sent to the curve planning module. Simultaneously, the speed and distance measurement module can collect information from speed sensors and satellite positioning, and through a fusion filtering algorithm, calculate the train's speed and position in real time and send it to the curve planning module. The wireless communication module can communicate wirelessly with ground and other onboard equipment, acquire information including line data, dispatching commands, and electronic maps, and report its own position and status. It can also send line data and dispatching commands to the curve planning module.

[0026] The integrity monitoring module, as a relatively independent module, is responsible for monitoring the integrity of the train body from the locomotive to the rear, preventing dangerous accidents such as coupler breakage. The data storage module is responsible for recording key information during the operation of the ATO system, used for statistical data collection and problem analysis.

[0027] After each module sends various data to the curve planning module, the curve planning module can plan the target speed curve of the freight train (i.e., the preset target speed curve of the freight train) based on the above data. Then the background service of the ATO system can obtain the preset target speed curve of the freight train.

[0028] After the ATO system obtains the preset target speed curve for the freight train, it can use this curve as input to the control algorithm in the control module. The control algorithm then calculates the specified control parameter values ​​for the freight train, where each specified control parameter value corresponds to the locomotive traction force. Furthermore, the control algorithm of this invention also includes a freight train motion formula for controlling train operation.

[0029] 102. Using the load calculation module, the load of the freight train is calculated in real time based on the specified control parameter values ​​and the freight train motion formula.

[0030] Since the control module can control train operation using the freight train motion formula, and the parameters of the freight train motion formula include specified control parameter values ​​for the freight train, after calculating the specified control parameter values, the load calculation module can first substitute these values ​​into the freight train motion formula. After substitution, the unknown load in the parameters of the freight train motion formula can be further calculated. Only after all parameters have been calculated can the control module successfully control the train operation using the freight train motion formula.

[0031] Based on the above Figure 1As can be seen from the implementation method, the freight train load calculation method provided by this invention can obtain the specified control parameter values ​​calculated by the control module, and then use the load calculation module to calculate the freight train load in real time based on the specified control parameter values. This eliminates the need for the driver to manually input the train load on the human-machine interface device, and does not rely on the maximum load value. Instead, the load calculation module performs the calculation in real time, obtaining the load most suitable for the current freight train operation, thus effectively improving the train's operating efficiency.

[0032] Furthermore, as a response to Figure 1 Further refinement and extension of the illustrated embodiment, this invention also provides another method for calculating the load capacity of freight trains, such as... Figure 2 As shown, the specific steps are as follows:

[0033] 201. Obtain the specified control parameter values ​​and the motion formula of the freight train.

[0034] The implementation method of step 201 is the same as that of step 101, and can achieve the same technical effect and solve the same technical problem, so it will not be repeated here.

[0035] 202. Using the load calculation module, the load of the freight train is calculated in real time based on the specified control parameter values ​​and the freight train motion formula.

[0036] Step 202 proposes a better implementation method that differs from step 102.

[0037] The motion formula for freight trains is as follows:

[0038] (Formula 1)

[0039] Where a represents the train's acceleration, F represents the locomotive's traction force, W represents the train's running resistance, P and G represent the locomotive's weight and the total weight of the rolling stock, respectively, P+G represents the freight train's load, and λ represents the slewing coefficient, typically taken as 0.06. This represents model error, including factors such as mechanical transmission losses of the train and longitudinal impulses during operating condition switching.

[0040] Where F is the specified control parameter value output by the control module, and W can be obtained through conventional methods, which will not be elaborated here.

[0041] In step 202, the specified freight train motion formula can be obtained by substituting the specified control parameter values ​​and the calculated parameter W values ​​into the freight train motion formula. At this point, the unknown parameters in the specified freight train motion formula include a, P+G, and... .

[0042] Therefore, freight train state variables can be set, which are used to characterize the operating speed of freight trains and constants related to the load of freight trains.

[0043] After setting the state variables of the freight train, the correlation between these state variables and the specified freight train motion formula can be established. This correlation exists because the freight train state variables characterize the train's operating speed and constants related to its load, while the unknown parameters in the specified freight train motion formula include load and train acceleration. Acceleration is related to speed, and the load-related constants are related to load. Once the correlation is established, it can be used to discretize and linearize the specified freight train motion formula to obtain the target state formula for the freight train.

[0044] The specific steps could be: selecting freight train state variables. ,in It is the train's operating speed. It is a constant related to the train's load. Furthermore, the relationship between the freight train's state variables and its motion formula is as follows:

[0045] (Formula 2)

[0046] Based on the above correlation, the nonlinear formula for train traction conditions is as follows:

[0047] (Formula 3)

[0048] Furthermore, by discretizing Formula 3 above, we can obtain:

[0049] (Formula 4)

[0050] It should be noted that this invention takes the train under traction conditions as an example. Under other conditions, only the corresponding formula needs to be changed, and the execution method is the same as that under traction conditions.

[0051] Furthermore, when the time interval of train operation... For a sufficiently short time, It can also be in Expanding to a Taylor series:

[0052] (Formula 5)

[0053] Where, in the formula It is a 2×2 matrix.

[0054] Substituting Formula 5 into Formula 4, we get The discretized motion formula for freight trains in the vicinity is as follows:

[0055] (Formula 6)

[0056] In the formula, This represents the sum of system errors and system model errors introduced during the linearization of the nonlinear state equations, assuming... Follows a Gaussian distribution, let The covariance matrix represents the systematic error.

[0057] According to the vector differential rule It can be represented as:

[0058] (Formula 7)

[0059] Finally, the target state formula for the freight train after discretization and linearization is:

[0060] (Formula 8)

[0061] Since the principle of the freight train target state formula is to predict the next state by obtaining the previous state, if only the freight train target state formula is used, the final result is a predicted value, which is not accurate. Therefore, the intervention of the freight train speed monitoring formula is also required.

[0062] Therefore, in this step, the real-time operating speed of the freight train calculated by the speed and distance measurement module can also be obtained. The real-time calculated operating speed is an observation value, which means it can reflect the relevant state value. Then, the freight train speed monitoring formula can be constructed based on the observation value, as follows:

[0063] (Formula Nine)

[0064] Then, the freight train load is calculated in real time using the freight train speed monitoring formula and the freight train target state formula.

[0065] Specifically, the freight train speed monitoring formula and the freight train target state formula can be substituted into the extended Kalman filter algorithm for processing, resulting in the following iterative expression:

[0066] (Formula 10)

[0067] (Formula Eleven)

[0068] (Formula 12)

[0069] (Formula Thirteen)

[0070] (Formula Fourteen)

[0071] In the formula, The state prediction value of the extended Kalman filter algorithm at time k+1. Let be the covariance matrix of the state prediction at time k+1; Let be the gain matrix at time k+1; The state estimate of the extended Kalman filter algorithm at time k+1. Let be the covariance matrix of the state estimate at time k+1.

[0072] The above-mentioned state prediction values ​​are the predicted values ​​corresponding to the state variables of the freight train, and the estimated values ​​are the variable values ​​corresponding to the calculated state variables of the freight train.

[0073] After obtaining the variable value, it can be substituted back into Formula 2 above to obtain the load capacity of the freight train.

[0074] It should be noted that this application only uses the train under traction conditions as an example, and the above steps can also be used to perform other operating conditions of freight trains.

[0075] 203. Load control of freight trains for freight train operation.

[0076] In step 203, after calculating the freight train's load, the calculated load can be used to correct the specified freight train motion formula. Then, the control module controls the freight train's operation according to the corrected motion formula. This makes the freight train's control and operation more reliable, thus making train operation safer.

[0077] Of course, when correcting the formula for a specified freight train, it can also be done by combining the number of freight trains. The specific process for obtaining the number of freight trains is as follows:

[0078] Step 1: When a freight train departs and enters the departure route, and the rear of the train leaves the departure route, the radio block center can detect that the departure route has been unlocked.

[0079] Step 2: When the radio block center detects that the departure route has been unlocked, it can request the train's current position from the automatic train protection system.

[0080] Step 3: After receiving the request, the Automatic Train Protection System (ATPS) can send the current position of the train to the Radio Block Center. The Radio Block Center calculates the train length based on the distance between the current position of the train and the end of the departure route, and then sends the calculated train length to the APS according to the communication protocol.

[0081] Step 4: After receiving the train length information, the Automatic Train Protection (ATP) system can obtain the number of cars in the freight train based on the conversion relationship between train length and number of cars. The conversion relationship between train length and number of cars is as follows:

[0082] When the RBC calculates an invalid car length, the number of cars = (maximum car length - minimum locomotive length) / minimum car length;

[0083] When RBC calculates the effective car length, the number of cars = (RBC calculated car length - maximum locomotive length) / maximum car length;

[0084] The above parameters, including maximum car length, minimum locomotive length, minimum car length, maximum locomotive length, and maximum car length, are all determined based on the train formation type and operational conditions of the train operating line.

[0085] Each time a train enters a station, regardless of whether the train's scheduled operation is underway or if station work is being carried out, the RBC sets the train length to an invalid value. When the ATP receives an invalid train length calculated by the RBC, it monitors train operations using the maximum train length. Each time a train leaves a station, the RBC recalculates the train length and sends it to the ATP.

[0086] The invalid value is the preset default maximum vehicle length.

[0087] The Automatic Train Protection (ATP) system then sends the train car count information to the Automatic Train Control (ATO). The ATO combines the freight train's load and car count information to determine the current status of the freight train, including whether it is empty or loaded (a train is considered loaded when its load is half or more of its maximum load; otherwise, it is empty; the empty / loaded status affects the train's braking parameters). Based on the current status of the freight train, the ATO corrects the specified freight train motion formula to obtain the corrected freight train motion formula. The train operation is then controlled using the corrected freight train motion formula. By incorporating the train car count parameter, the corrected freight train motion formula becomes more accurate, thus enabling better control of the freight train's operation.

[0088] Furthermore, as a response to the above Figure 1 In addition to the implementation of the method shown, this embodiment of the invention also provides a load calculation device for freight trains, used for calculating the load of the aforementioned... Figure 1 The method shown is implemented accordingly. This device embodiment corresponds to the foregoing method embodiment. For ease of reading, this device embodiment will not repeat the details of the foregoing method embodiment, but it should be clear that the device in this embodiment can implement all the contents of the foregoing method embodiment. Figure 3 As shown, the device includes:

[0089] The parameter acquisition unit 301 is used to acquire specified control parameter values ​​and freight train motion formulas.

[0090] The load calculation unit 302 is used to calculate the load of the freight train in real time using the load calculation module, based on the specified control parameter values ​​obtained by the parameter acquisition unit 301 and the freight train motion formula.

[0091] Furthermore, as a response to the above Figure 2 In addition to the implementation of the method shown, this embodiment of the invention also provides another load calculation device for freight trains, used for calculating the load of the aforementioned... Figure 2 The method shown is implemented accordingly. This device embodiment corresponds to the foregoing method embodiment. For ease of reading, this device embodiment will not repeat the details of the foregoing method embodiment, but it should be clear that the device in this embodiment can implement all the contents of the foregoing method embodiment. Figure 4 As shown, the device includes:

[0092] The parameter acquisition unit 301 is used to acquire specified control parameter values ​​and freight train motion formulas.

[0093] The load calculation unit 302 is used to calculate the load of the freight train in real time using the load calculation module, based on the specified control parameter values ​​obtained by the parameter acquisition unit 301 and the freight train motion formula.

[0094] In one optional implementation, the load calculation unit 302 includes:

[0095] The parameter substitution module 3021 is used to substitute the specified control parameter value into the freight train motion formula to obtain the specified freight train motion formula. The constituent parameters of the freight train motion formula include the freight train's load and the freight train's acceleration.

[0096] The variable setting module 3022 is used to set the freight train status variables, which are used to characterize the operating speed of the freight train and constants related to the load of the freight train.

[0097] Formula processing module 3023 is used to process the specified freight train motion formula obtained by parameter substitution module 3021 based on the freight train state variable set by variable setting module 3022 to obtain the freight train target state formula.

[0098] The load calculation module 3024 is used to calculate the load of the freight train in real time based on the target state formula of the freight train obtained by the formula processing module 3023.

[0099] In one optional implementation, the formula processing module 3023 is specifically used for:

[0100] Determine the relationship between the freight train state variables and the specified freight train motion formula;

[0101] Based on the aforementioned correlation, the motion formula of the specified freight train is discretized and linearized to obtain the target state formula of the freight train.

[0102] In one optional implementation, the load calculation module 3024 includes:

[0103] The speed acquisition submodule 30241 is used to acquire the real-time operating speed of the freight train calculated by the speed and distance measurement module;

[0104] Formula construction submodule 30242 is used to construct a freight train speed monitoring formula based on the real-time operating speed of the freight train obtained by the speed acquisition submodule 30241.

[0105] The load calculation submodule 30243 is used to calculate the load of the freight train in real time based on the freight train speed monitoring formula and the freight train target state formula constructed by the formula construction submodule 30242.

[0106] In one optional implementation, the load calculation submodule 30243 is specifically used for:

[0107] Substituting the freight train speed monitoring formula and the freight train target state formula into the extended Kalman filter algorithm, the variable values ​​corresponding to the freight train state variables are obtained.

[0108] The load capacity of the freight train is calculated based on the correlation between the variable values ​​and the state variables of the freight train and the specified motion formula of the freight train.

[0109] In one optional embodiment, after the load calculation submodule 30243 calculates the load of the freight train, the device further includes a first formula correction unit 303, the first formula correction unit 303 comprising:

[0110] The first formula correction module 3031 is used to correct the specified freight train motion formula based on the load of the freight train to obtain the corrected freight train motion formula.

[0111] The first train control module 3032 is used to control the operation of the freight train based on the corrected freight train motion formula obtained by the first formula correction module 3031.

[0112] In an optional embodiment, the device further includes a second formula correction unit 304, the second formula correction unit 304 comprising:

[0113] The information receiving module 3041 is used to receive the number of cars of the freight train. The number of cars is information that the automatic train protection system calculates and sends in advance based on the correlation between the train length and the number of cars. The train length is information that the radio block center calculates and sends in advance based on the distance between the current position of the train and the end point of the departure route and sends to the automatic train protection system. The current position of the train is the position that the radio block center requests to obtain when it detects the unlocking of the departure route during the train's departure process.

[0114] The second formula correction module 3042 is used to correct the specified freight train motion formula based on the number of vehicles received by the information receiving module 3041 and the load of the freight train, so as to obtain the corrected freight train motion formula.

[0115] The second train control module 3043 is used to control the operation of the freight train based on the corrected freight train motion formula obtained by the second formula correction module 3042.

[0116] Furthermore, embodiments of the present invention also provide a storage medium for storing a computer program, wherein the computer program, when running, controls the device where the storage medium is located to execute the above-described... Figure 1-2 The method for calculating the load capacity of freight trains as described in the document.

[0117] Furthermore, embodiments of the present invention also provide a processor for running a program, wherein the program executes the above-described... Figure 1-2 The method for calculating the load capacity of freight trains as described in the document.

[0118] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0119] It is understood that the relevant features in the above methods and apparatus can be referenced interchangeably. Furthermore, the terms "first," "second," etc., in the above embodiments are used to distinguish between embodiments and do not represent the superiority or inferiority of any particular embodiment.

[0120] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0121] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0122] In addition, the memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0123] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0124] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0125] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0126] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0127] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0128] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0129] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0130] It should also be noted that 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 process, method, article, or apparatus. Unless otherwise specified, 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 that element.

[0131] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0132] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for calculating the load capacity of a freight train, characterized in that, The method includes: Obtain the specified control parameter values ​​and freight train motion formulas; Using the load calculation module, the load of the freight train is calculated in real time based on the specified control parameter values ​​and the freight train motion formula, including: Substituting the specified control parameter values ​​into the freight train motion formula yields the specified freight train motion formula. The parameters of the freight train motion formula include the freight train's load and its acceleration. The freight train motion formula is as follows: Where a represents the train's acceleration, F represents the locomotive's traction force, W represents the train's running resistance, P and G represent the locomotive's weight and the total weight of the vehicles, respectively, P+G represents the freight train's load, and λ represents the slewing coefficient. This represents model error, including mechanical transmission losses of the train and longitudinal impulses during operating condition switching. Set up freight train state variables, which are used to characterize the operating speed of the freight train and constants related to the load of the freight train; Based on the state variables of the freight train, the motion formula of the specified freight train is processed to obtain the target state formula of the freight train, including: Determine the correlation between the freight train state variables and the specified freight train motion formula, wherein the correlation is as follows: in, It is the train's operating speed. It is a constant related to the train's load capacity; Based on the aforementioned correlation, the motion formula of the specified freight train is discretized and linearized to obtain the target state formula of the freight train. The discretization and linearization steps of the target state formula of the freight train are as follows: Based on the correlation, the nonlinear formula for train traction conditions is obtained: Discretizing the nonlinear formula yields: exist Expanding to a Taylor series: Where, in the formula It is a 2×2 matrix; Substituting the formula for developing a Taylor series into the formula obtained by discretizing the nonlinear formula, we get... The discretized motion formula for freight trains in the vicinity is as follows: In the formula, This represents the sum of system errors and system model errors introduced during the linearization of the nonlinear state equations, assuming... Follows a Gaussian distribution, let The covariance matrix represents the systematic error; According to the vector differential rule It can be represented as: The target state formula for the freight train after discretization and linearization is as follows: ; The load of the freight train is calculated in real time based on the target state formula of the freight train.

2. The method according to claim 1, characterized in that, The load of the freight train is calculated in real time based on the target state formula of the freight train, including: Obtain the real-time operating speed of the freight train calculated by the speed and distance measurement module; A freight train speed monitoring formula is constructed based on the real-time operating speed of the freight train. The load of the freight train is calculated in real time based on the freight train speed monitoring formula and the freight train target state formula.

3. The method according to claim 2, characterized in that, The load of the freight train is calculated in real time based on the freight train speed monitoring formula and the freight train target state formula, including: Substituting the freight train speed monitoring formula and the freight train target state formula into the extended Kalman filter algorithm, the variable values ​​corresponding to the freight train state variables are obtained. The load capacity of the freight train is calculated based on the correlation between the variable values ​​and the state variables of the freight train and the specified motion formula of the freight train.

4. The method according to any one of claims 1-3, characterized in that, After calculating the load capacity of the freight train, the method further includes: The motion formula of the specified freight train is corrected based on the load of the freight train to obtain the corrected motion formula of the freight train. The operation of the freight train is controlled based on the corrected freight train motion formula.

5. The method according to claim 1, characterized in that, The method further includes: The system receives information on the number of freight trains. This information is calculated and sent in advance by the Automatic Train Protection System based on the correlation between the train length and the number of trains. The train length is calculated and sent in advance by the Radio Block Center based on the distance between the current position of the train and the end point of the departure route. The current position of the train is the position requested by the Radio Block Center when it detects the unlocking of the departure route during the train's departure process. The motion formula of the specified freight train is corrected based on the number of vehicles and the load of the freight train to obtain the corrected freight train motion formula. The operation of the freight train is controlled based on the corrected freight train motion formula.

6. A load calculation device for freight trains, characterized in that, The device includes: The parameter acquisition unit is used to acquire specified control parameter values ​​and freight train motion formulas. A load calculation unit is used to calculate the load of the freight train in real time using the load calculation module, based on the specified control parameter values ​​obtained by the parameter acquisition unit and the freight train motion formula. The load calculation unit includes: The parameter substitution module is used to substitute the specified control parameter values ​​into the freight train motion formula to obtain the specified freight train motion formula. The parameters of the freight train motion formula include the freight train's load and the freight train's acceleration. The freight train motion formula is as follows: Where a represents the train's acceleration, F represents the locomotive's traction force, W represents the train's running resistance, P and G represent the locomotive's weight and the total weight of the vehicles, respectively, P+G represents the freight train's load, and λ represents the slewing coefficient. This represents model error, including mechanical transmission losses of the train and longitudinal impulses during operating condition switching. The variable setting module is used to set the freight train status variables, which are used to characterize the freight train's operating speed and constants related to the freight train's load. The formula processing module is used to process the specified freight train motion formula obtained by the parameter substitution module based on the freight train state variables set by the variable setting module, to obtain the freight train target state formula. Specifically, the formula processing module is used for: Determine the correlation between the freight train state variables and the specified freight train motion formula, wherein the correlation is as follows: in, It is the train's operating speed. It is a constant related to the train's load capacity; Based on the aforementioned correlation, the motion formula of the specified freight train is discretized and linearized to obtain the target state formula of the freight train. The discretization and linearization steps of the target state formula of the freight train are as follows: Based on the correlation, the nonlinear formula for train traction conditions is obtained: Discretizing the nonlinear formula yields: exist Expanding to a Taylor series: Where, in the formula It is a 2×2 matrix; Substituting the formula for developing a Taylor series into the formula obtained by discretizing the nonlinear formula, we get... The discretized motion formula for freight trains in the vicinity is as follows: In the formula, This represents the sum of system errors and system model errors introduced during the linearization of the nonlinear state equations, assuming... Follows a Gaussian distribution, let The covariance matrix represents the systematic error; According to the vector differential rule It can be represented as: The target state formula for the freight train after discretization and linearization is as follows: ; The load calculation module is used to calculate the load of the freight train in real time based on the target state formula of the freight train obtained by the formula processing module.

7. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the storage medium to perform the load calculation method for freight trains as described in any one of claims 1 to 5.

8. A processor, characterized in that, The processor is used to run a program, wherein the program executes the load calculation method for freight trains as described in any one of claims 1 to 5.

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