Distributed collaborative analysis platform for train braking system

Abstract

The application discloses a train braking system distributed cooperative analysis platform, which comprises a system simulation area, a data acquisition area, a data intelligent analysis area and the like. The data acquisition area acquires vehicle data and transmits the vehicle data to the system simulation area. The system simulation area outputs vehicle simulation data through model-in-loop simulation, rapid control prototype simulation and hardware-in-loop simulation according to the vehicle data. The data intelligent analysis area performs fault diagnosis on a train braking system according to the vehicle data and the vehicle simulation data, and outputs a solution to eliminate faults according to a diagnosis result. The application takes an electronic brake control unit, a pneumatic brake control unit, a basic brake unit and other key components as main control objects, establishes a train braking system distributed cooperative analysis platform based on model simulation and big data analysis, and solves problems existing in system design, system test verification and system operation and maintenance.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of train braking system, and particularly relates to a distributed collaborative analysis platform for train braking system. BACKGROUND

[0002] The train braking system belongs to a typical complex mechatronic system, which highly integrates components of multiple physical domains such as mechanics, electronics and pneumatic in a modular and networked manner, including an electronic control unit (EBCU), a pneumatic control unit (PBCU) and a basic braking unit. Coupling exists between the components, and currently, a trial-and-error serial research and development driven by full physical test is generally adopted. Currently, the following problems generally exist:

[0003] 1) The braking system design is mostly based on the original pure physical prototype method or only single-component single-discipline simulation analysis. The pure physical prototype design method can directly show the feasibility of the design scheme, but it consumes a large amount of design time and cost, and the design method based on repeated prototype manufacturing is not conducive to the rapid advancement of the project, and it is difficult to optimize the overall performance of the system.

[0004] 2) The braking system verification is mostly based on the traditional bench or line test method. The bench or line test method is the most direct means to study the braking performance of the train, which can quickly master the dynamic characteristics and steady-state characteristics of the train braking. However, the bench and line test has the following problems:

[0005] a) The bench building cycle is long and the cost is high. The braking bench generally includes a control console, an air compressor, an air storage cylinder, a pneumatic unit, a pipeline, etc., and the traction bench includes a transformer, an inverter and a traction motor, etc. Currently, the motor train vehicle is 8-formation and the urban rail vehicle is 6-formation. It takes a lot of time, manpower and material resources to build a multi-formation bench, and the universality between different vehicles is poor.

[0006] b) The bench test belongs to open-loop test, and the logic verification is insufficient. The general bench cannot simulate the movement state of the vehicle such as the action of the clamp and the movement of the wheel. Only open-loop test can be performed, such as the speed generator outputting the speed value according to the pre-specified curve, and then monitoring the pipeline pressure to determine whether the EBCU and the like are working normally.

[0007] c) There are fewer test items, such as the inability to perform closed-loop anti-skid control test, the inability to perform fault-oriented test, the inability to perform braking distance performance test, etc. In addition, the bench test is generally a single system test, and the joint test of multiple systems, such as the electric air cooperation test of the braking and traction system, cannot be realized.

[0008] d) The risk is large, and there is a safety hazard. The braking system and the traction system are the core components to ensure the safety of the vehicle. If there is a problem, it will lead to a major safety accident, especially under high-speed and heavy-load conditions.

[0009] e) The test cost is too high. Line test needs to coordinate a large amount of manpower and material resources to meet the test requirements while ensuring the safety of the test. For example, the low adhesion working condition required by the anti-skid test has strict requirements on the line conditions and environment.

[0010] 3) The brake system fault analysis adopts the existing vehicle fault analysis method. When the vehicle fails, personnel need to reproduce the fault or manually read the fault time data to analyze the vehicle, the fault response cycle time is long, and the normal operation of the train is affected.

[0011] 4) The brake system maintenance adopts the planned maintenance (periodic maintenance) without considering the cost and ensuring safety, which has been difficult to adapt to the fault law of the current integrated mechanical and electrical equipment of the brake system, causing problems such as large maintenance amount, high work intensity, and insufficient accuracy.

[0012] With the continuous enrichment of rail transit vehicle brake system products, faster and faster research and development cycle, and higher and higher safety requirements, the traditional research and development and operation and maintenance mode cannot meet the vehicle demand. SUMMARY

[0013] The embodiment of the application provides a train brake system distributed collaborative analysis platform, so as to at least solve the problems of large design time and cost of the brake system design method, difficulty in optimizing the overall performance of the system, many problems in brake system verification, long fault response cycle time of the brake system fault analysis method, influence on normal operation of the train, and brake system maintenance mode difficult to adapt to the fault law of the current integrated mechanical and electrical equipment of the brake system, causing problems such as large maintenance amount, high work intensity, and insufficient accuracy.

[0014] The application provides a train brake system distributed collaborative analysis platform, which comprises:

[0015] A system simulation area, a data acquisition area acquires vehicle data and transmits the vehicle data to the system simulation area, and the system simulation area outputs vehicle simulation data through model-in-loop simulation, rapid control prototype simulation, and hardware-in-loop simulation according to the vehicle data;

[0016] A data intelligent analysis area, which performs fault diagnosis on the train brake system according to the vehicle data and the vehicle simulation data, and outputs a solution to eliminate the fault according to the diagnosis result.

[0017] The train brake system distributed collaborative analysis platform comprises a semi-physical simulation cabinet, an industrial computer, a switch, and a real CCU unit.

[0018] The industrial computer collects vehicle simulation parameters output by the semi-physical simulation cabinet through the switch, wherein the semi-physical simulation cabinet outputs the vehicle simulation parameters through the model in loop simulation, the rapid control prototype simulation and the hardware in loop simulation.

[0019] In the train braking system distributed collaborative analysis platform, the semi-physical simulation cabinet includes a real-time simulation system, a plurality of real EBCU units and a plurality of real TCU units, the real-time simulation machine transmits the final simulation data to the real EBCU units and the real TCU units, and the industrial computer collects real EBCU unit data and real TCU unit data, i.e., the vehicle simulation parameters, through the real CCU unit.

[0020] In the train braking system distributed collaborative analysis platform, the real-time simulation system includes:

[0021] The real-time simulation machine includes a processor board card and an IO interface board card, the processor board card runs a simulation model to output first simulation data, and the IO interface board card converts the first simulation data into second simulation data that can be recognized.

[0022] The signal conditioning box receives the second simulation data, conditions the second simulation data to obtain third simulation data after conditioning, and outputs the third simulation data.

[0023] The fault injection test box receives the third simulation data, performs fault testing on the system according to the third simulation data, and outputs fourth simulation data after the fault testing.

[0024] The signal adaptation box receives the fourth simulation data, adapts the fourth simulation data to obtain the final simulation data.

[0025] The power management module is used by the signal conditioning box, the fault injection test box and the signal adaptation box to obtain AC and DC power and realize overcurrent, overvoltage and leakage protection.

[0026] The first simulation data includes model in loop simulation data, rapid control prototype simulation data and hardware online simulation data.

[0027] In the train braking system distributed collaborative analysis platform, the model in loop simulation includes running instruction signal models, TCU models, EBCU models, PBCU models, basic brake unit models and dynamic models in the real-time simulation machine through the processor board card, outputting the model in loop simulation data, and transmitting the model in loop simulation data to the IO interface board card through a communication bus.

[0028] The model-in-loop simulation further comprises:

[0029] The instruction signal model, the EBCU model, the TCU model and the foundation brake unit model are established by Matlab / Simulink;

[0030] The PBCU model is established by AMESim software;

[0031] The dynamics model is established by SimPack or SimulationX software.

[0032] The model-in-loop simulation further comprises:

[0033] An instruction signal model, wherein the vehicle data is imported into the real-time simulation machine according to a protocol format, and the instruction signal model outputs vehicle instructions according to the vehicle data;

[0034] A TCU model, wherein the TCU model outputs an electric brake feedback signal to the EBCU model and outputs a traction force or an electric brake force to the dynamics model according to the vehicle instructions;

[0035] An EBCU model, wherein the EBCU model comprises a logic algorithm model and a valve driving model, the logic algorithm model outputs a pre-control pressure at the current time according to the vehicle instructions and feedback signals output by the dynamics model and the electric brake feedback signal, and the valve driving model outputs a valve control signal according to the pre-control pressure and an actual brake cylinder pressure output by the PBCU model;

[0036] A PBCU model, wherein the PBCU model receives the valve control signal to output a brake cylinder pressure signal and feeds back to the EBCU model;

[0037] A foundation brake unit model, wherein the foundation brake unit model receives the brake cylinder pressure signal to output an air brake force;

[0038] A dynamics model, wherein the dynamics model receives the air brake force and the traction force or the electric brake force to output the first simulation data, feeds back to the IO interface board card, and feeds back to the TCU model and the EBCU model to form a closed-loop simulation.

[0039] The rapid control prototype simulation comprises:

[0040] The real PBCU unit and the real basic brake unit are used to replace the PBCU model and the basic brake unit model in the loop simulation, to form a rapid control prototype simulation, the instruction signal model, the TCU model, the EBCU model and the dynamics model are run by the processor board card in the real-time simulation machine to output the rapid control prototype simulation data, and the rapid control prototype simulation data are transmitted to the IO interface board card through the communication bus.

[0041] In the train brake system distributed collaborative analysis platform, the hardware-in-the-loop simulation comprises:

[0042] The real EBCU unit and the real TCU unit are used to replace the EBCU model and the TCU model in the loop simulation, to form a hardware-in-the-loop simulation, the instruction signal model, the PBCU model, the basic brake unit model and the dynamics model are run by the processor board card in the real-time simulation machine to output the hardware-in-the-loop simulation data, and the hardware-in-the-loop simulation data are transmitted to the IO interface board card through the communication bus.

[0043] In the train brake system distributed collaborative analysis platform, the data intelligent analysis area comprises that according to the vehicle data and the vehicle simulation data, the train brake system is subjected to remote fault reproduction and fault diagnosis through a fault injection function of the fault injection test box.

[0044] Compared with the related art, the train brake system distributed collaborative analysis platform can simulate the running environment of the vehicle brake system in each design stage through the test environment built by the distributed real-time simulation machine and the physical object, can meet the test points difficult to be realized in the single system bench and the line test such as the electric air coordination test and the anti-skid logic test, can meet the design and test requirements of the brake system of any marshalling motor car, passenger car and urban rail vehicle, has good universality and scalability, the simulation machine cabinet hardware structure, especially the non-intrusive fault injection test box design, can meet the fault-oriented safety test requirements, the overall hardware structure adopts the modular design, when different components of the brake system are tested, only the corresponding module can be replaced, and the applicability is high, the data intelligent analysis area can realize the remote fault diagnosis and analysis, the fault prediction and the health evaluation according to the real vehicle data transmitted by the data acquisition area and the simulation data transmitted by the system simulation area.

[0045] Details of one or more embodiments of the present application are presented in the following drawings and description to make other features, objects and advantages of the present application more clear and simple. BRIEF DESCRIPTION OF DRAWINGS

[0046] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0047] Figure 1 is a distributed collaborative analysis platform architecture according to an embodiment of the application;

[0048] Figure 2 is a pneumatic model modeling architecture according to an embodiment of the application;

[0049] Figure 3 is a dynamics model modeling architecture according to an embodiment of the application;

[0050] Figure 4 is a simulation machine cabinet hardware structure according to an embodiment of the application;

[0051] Figure 5 is a fault injection test box architecture according to an embodiment of the application;

[0052] Figure 6 is a hardware-in-the-loop simulation hardware topology structure according to an embodiment of the application;

[0053] Figure 7 is a hardware-in-the-loop simulation software topology structure according to an embodiment of the application. DETAILED DESCRIPTION

[0054] In order to make the objects, technical solutions and advantages of the application clearer, the application will be described and illustrated below in connection with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the application and should not be used to limit the application. Based on the embodiments provided in the application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the application.

[0055] Obviously, the drawings in the following description are only some examples or embodiments of the application, and for those of ordinary skill in the art, the application can be applied to other similar scenarios without creative labor on the basis of these drawings. In addition, it can be understood that although the efforts made in this development process can be complex and lengthy, for those of ordinary skill in the art related to the content disclosed in the application, some design, manufacture or production changes based on the technical content disclosed in the application are only routine technical means and should not be understood as insufficient disclosure of the application.

[0056] Reference to an“embodiment” in this application means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. It is expressly understood that that the embodiments described in this application are open to be combined with each other in their various permutations and combinations.

[0057] Unless otherwise defined, technical terms and scientific terms used in the present application shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terms“a,”“an,” and“the” used in the application do not denote a limitation of quantity, and can mean one or more. The terms“including,”“comprising,”“having,” and the like are meant to encompass the occurrence of zero, one or more of the stated steps or units thereof. The terms“connected,”“coupled,”“linked,” and the like are not limited to direct connections or physical connections, but can include indirect connections or physical connections, whether or not they are direct. The term“multiple” means two or more. The term“and / or” describes associated objects in association relationship, which means that there can be three relationships, for example, “A and / or B” can mean that A exists alone, A and B exist together, and B exists alone. The character“ / ” generally means that the associated objects are in an“or” relationship. The terms“first,”“second,”“third,” and the like are merely used to distinguish similar objects, and do not represent a specific order of the objects.

[0058] The train braking system distributed collaborative analysis platform provided by the application takes key components such as electronic brake control units, pneumatic brake control units, and foundation brake units as the main control objects, establishes a train braking system distributed collaborative analysis platform based on model simulation and big data analysis, and solves the problems existing in system design, system test verification, and system operation and maintenance.

[0059] The embodiments of the application will be described below with the train braking system distributed collaborative analysis platform as an example.

[0060] Embodiment One

[0061] The embodiment provides a train braking system distributed collaborative analysis platform. Please refer to Figures 1 to 7 , Figure 1 is a distributed collaborative analysis platform architecture according to the embodiment of the application;Figure 2 is a pneumatic model modeling architecture according to an embodiment of the present application; Figure 3 is a dynamics model modeling architecture according to an embodiment of the present application; Figure 4 is a simulation cabinet hardware structure according to an embodiment of the present application; Figure 5 is a fault injection test box architecture according to an embodiment of the present application; Figure 6 is a hardware-in-the-loop simulation hardware topology structure according to an embodiment of the present application; Figure 7 is a hardware-in-the-loop simulation software topology structure according to an embodiment of the present application, as shown in Figures 1 to 7 The train braking system distributed collaborative analysis platform comprises:

[0062] a system simulation area, a data acquisition area, the data acquisition area acquiring vehicle data and transmitting the vehicle data to the system simulation area, the system simulation area outputting vehicle simulation data through model-in-the-loop simulation, rapid control prototype simulation and hardware-in-the-loop simulation according to the vehicle data;

[0063] a data intelligent analysis area, the data intelligent analysis area performing fault diagnosis on the train braking system according to the vehicle data and the vehicle simulation data, and outputting a solution to eliminate faults according to a diagnosis result.

[0064] In an embodiment, the system simulation area comprises a semi-physical simulation cabinet industrial personal computer, a switch and real CCU units.

[0065] The industrial personal computer acquires vehicle simulation parameters output by the semi-physical simulation cabinet through the switch, wherein the semi-physical simulation cabinet outputs the vehicle simulation parameters through model-in-the-loop simulation, rapid control prototype simulation and hardware-in-the-loop simulation.

[0066] The semi-physical simulation cabinet comprises a real-time simulation machine, a plurality of real EBCU units and a plurality of real TCU units, the real-time simulation machine transmits final simulation data to the real EBCU units and the real TCU units, and the industrial personal computer acquires real EBCU unit data and real TCU unit data, i.e. the vehicle simulation parameters, through the real CCU units.

[0067] The real-time simulation system comprises:

[0068] a real-time simulation machine, the real-time simulation machine comprising a processor board card and an IO interface board card, the processor board card running a simulation model to output first simulation data, and the IO interface board card converting the first simulation data into second simulation data recognizable.

[0069] a signal conditioning box, the signal conditioning box receiving the second simulation data, conditioning the second simulation data to obtain third simulation data after conditioning.

[0070] a fault injection test box, which receives the third simulation data, performs fault test on the system according to the third simulation data, and outputs fourth simulation data;

[0071] a signal adaptation box, which receives the fourth simulation data, performs adaptation on the fourth simulation data, and obtains the final simulation data;

[0072] a power management module, through which the signal conditioning box, the fault injection test box and the signal adaptation box obtain AC and DC power, and realize overcurrent, overvoltage and electric leakage protection;

[0073] The first simulation data includes model-in-the-loop simulation data, rapid control prototype simulation data and hardware-in-the-loop simulation data.

[0074] In a specific implementation, the platform mainly includes a system simulation area, a data acquisition area, a data intelligent analysis and visualization area, as shown in Figure 1 .

[0075] The data acquisition area includes real-time data and non-real-time data, and the data are all from online vehicles. The vehicle braking system maintenance terminal acquires vehicle braking system operation data, i.e. real-time data, in real time, and sends the real-time data to the collaborative analysis platform server in real time through a train-ground wireless communication network. Meanwhile, after the train returns to the vehicle depot, the braking system maintenance terminal sends large-capacity data stored locally, i.e. offline data, to the collaborative analysis platform server through an in-warehouse train-ground wireless communication network, i.e. FTP transmission protocol. The real vehicle data can be imported into the system simulation area, the data intelligent analysis and visualization area according to a protocol format; the system simulation area can perform model verification and iterative optimization according to the real vehicle data, so as to improve the model maturity and confidence.

[0076] The system simulation area includes pure digital simulation model-in-the-loop simulation and semi-physical simulation, and the semi-physical simulation includes rapid control prototype simulation and hardware-in-the-loop simulation. The model-in-the-loop simulation includes an instruction signal model, an EBCU model, a PBCU model, a basic braking unit model and a dynamics model, each model is provided with a real vehicle data injection software interface, the real vehicle data are from the data acquisition area, and the software interface can support different data formats through configuration.

[0077] The signal model simulates the controller command or signal system command, including traction command, braking command, working mode, etc. The EBCU model includes a logic algorithm model and a valve drive model. The logic algorithm model outputs the pre-control pressure at the current time according to the signal model command, in combination with the speed, acceleration and other feedback signals output by the dynamics model, and the electric braking force information of the TCU model. The TCU model receives the signal model command and the electric braking request signal of the EBCU model, and outputs the electric braking feedback signal to the EBCU model and the traction force or electric braking force to the dynamics model. The valve drive model outputs the valve control signal according to the pre-control pressure and the actual brake cylinder pressure output by the PBCU model. The PBCU model receives the valve control signal and outputs the brake cylinder pressure and feeds it back to the EBCU model. The basic brake unit model receives the brake cylinder pressure signal and outputs the air braking force. The dynamics model receives the air braking force and the electric braking force or traction force, and outputs the distance, speed and acceleration signals, and feeds them back to the EBCU model, thereby forming a model-in-loop simulation.

[0078] The model is modeled according to the test requirements, which can be divided into three types: modeling based on theoretical equations, modeling oriented to physical objects and hybrid modeling. The basic brake unit model is an example of modeling based on theoretical equations, the pneumatic control unit model is an example of modeling oriented to physical objects, and the dynamics model is an example of hybrid modeling. The modeling is not limited to any software, and it is recommended to use FMU / FMI interface for data interaction between models.

[0079] The basic brake unit design principle is clear, and modeling based on theoretical equations is adopted, as follows:

[0080] The clamp unit output force is:

[0081] F_z = ((P x A - f_h) x η1) x γ2 x η2

[0082] Braking torque calculation formula:

[0083] J = F_z x μ_0 x r_0 x n_c

[0084] Wherein, the meanings of various parameters are shown in the following table:

[0085]

[0086]

[0087] The pneumatic control unit involves many components, and modeling oriented to physical objects is adopted. First, based on the basic element combination modeling concept, the system is divided into a hierarchical structure of component level, unit level and system level, such as Figure 2The model is shown in Fig. 1. First, the component model is described as detailed and accurate as possible, and then the module level and system level structure are formed by combination and optimization. The component level modeling includes electromagnetic valve, anti-skid valve, pressure reducing valve, pressure regulating module, relay valve, filter, overflow valve, parking valve, plug valve, etc. The unit level modeling includes auxiliary control unit, main control unit, pipeline accessories, etc. The system level includes air source, single vehicle model, whole vehicle pipeline, etc.

[0088] The dynamic model adopts hybrid modeling. First, the physical objects are divided into vehicle longitudinal dynamics model and wheel-rail contact model. In the longitudinal dynamics model, there are car coupler model, axle load calculation model, inertial resistance model and comprehensive calculation model, as shown in Fig. 2. Figure 3 Considering the anti-skid control verification, the wheel-rail contact model considers the adhesion change, and can adopt the Polach wheel-rail adhesion reduction theory formula for modeling:

[0089]

[0090] Wherein:

[0091] f——adhesion coefficient;

[0092] k A , k s ——adhesion reduction factor in adhesion zone and sliding zone;

[0093] ε——gradient of shear stress in adhesion zone;

[0094] μ——wheel-rail friction coefficient;

[0095] The real-time simulation machine main processor board runs the simulation model, and communicates with the I / O interface board through the communication bus, which can be PCI bus, PCI-Express bus, etc. The I / O interface board outputs the simulation data of the main processor board to the recognizable hardware signals, and collects the hardware signals as the input of the simulation model, to realize closed-loop simulation.

[0096] The real-time simulation machine includes signal conditioning box, fault injection test box, signal adaptation box, power management module;

[0097] The signal conditioning box realizes the electrical consistency adjustment of the real unit and the model signal, and the main functions include: 1) adjusting the output signal of the real unit to the input permission range of the real-time simulation machine, so that the simulation machine can collect and test the real unit signal; 2) adjusting the output signal of the real-time simulation machine, and the adjusted signal can meet the input requirements of the real unit excitation signal;

[0098] The fault injection test box is a third-party device connected in series in the signal line, and the test box is a non-intrusive fault injection product, such as Figure 4 , 5As shown, when fault injection is performed, no changes need to be made to the connection system. By simulating abnormalities that can occur in signals and their transmission paths, such as signal short circuits, open circuits, etc., reverse testing of the system can be completed; in cooperation with the signal fault injection system host computer software, parameter configuration of the fault injection test box and self-checking of the fault injection equipment can be achieved;

[0099] The signal adaptation box is used to adapt various types of connectors in the test platform, and the signals are distributed through the internal circuit board or wires of the adaptation box to convert into corresponding interface forms.

[0100] The power management module is responsible for power management of the test bench equipment, provides AC and DC power to the electrical equipment of the test bench, and provides functions such as overcurrent, overvoltage and leakage protection.

[0101] Among them, according to the consideration of universality and scalability, all semi-physical simulation cabinets have the same hardware structure layout, as shown in Figure 5 .

[0102] In the embodiment, the model-in-loop simulation comprises: running an instruction signal model, a TCU model, an EBCU model, a PBCU model, a basic brake unit model and a dynamics model in the real-time simulation machine through the processor board card, outputting model-in-loop simulation data, and transmitting the model-in-loop simulation data to the IO interface board card through a communication bus.

[0103] The instruction signal model, the EBCU model, the TCU model and the basic brake unit model are established by Matlab / Simulink.

[0104] The PBCU model is established by AMESim software.

[0105] The dynamics model is established by SimPack or SimulationX software.

[0106] The instruction signal model, the vehicle data is imported into the real-time simulation machine according to the protocol format, and the instruction signal model outputs vehicle instructions according to the vehicle data.

[0107] The TCU model outputs an electric brake feedback signal to the EBCU model and outputs a traction force or an electric brake force to the dynamics model according to the vehicle instructions.

[0108] The EBCU model comprises a logic algorithm model and a valve drive model, the logic algorithm model outputs a pre-control pressure at the current time according to the vehicle instructions and feedback signals output by the dynamics model and the electric brake feedback signal, and the valve drive model outputs a valve control signal according to the pre-control pressure and an actual brake cylinder pressure output by the PBCU model.

[0109] a PBCU model receiving the valve control signal output brake cylinder pressure signal and feeding back to the EBCU model;

[0110] a foundation brake unit model receiving the brake cylinder pressure signal output air brake force;

[0111] a dynamics model receiving the air brake force and the traction force or electric brake force, outputting the first simulation data, feeding back to the IO interface board card, and feeding back to the TCU model and the EBCU model to form a closed-loop simulation.

[0112] In a specific implementation, first, a signal model, an EBCU model, a TCU model and a foundation brake unit model are respectively established by Matlab / Simulink, where an EBCU model is as shown in Figure 6 Second, a PBCU model is established by AMESim software, and a Simulink S-Function module is output after debugging. A dynamics model is established by SimPack or SimulationX software, and a Simulink S-Function module is output after debugging. Third, all modules are integrated and simulated in a Simulink environment. Finally, a real PBCU unit and a real foundation brake unit replace the PBCU model and the foundation brake unit model in the loop simulation to form a rapid control prototype simulation, as shown in Figure 7 wherein the rapid control prototype simulation mainly verifies the EBCU control algorithm logic. The verified EBCU control algorithm logic can be generated into product-level embedded code by an automatic code generation tool, such as a Simulink Coder toolbox, to realize synchronous development of brake EBCU software and hardware.

[0113] In an embodiment, the rapid control prototype simulation includes:

[0114] The real PBCU unit and the real foundation brake unit replace the PBCU model and the foundation brake unit model in the loop simulation to form a rapid control prototype simulation. The instruction signal model, the TCU model, the EBCU model and the dynamics model are run in the real-time simulation machine by the processor board card to output the rapid control prototype simulation data, and the rapid control prototype simulation data are transmitted to the IO interface board card through the communication bus.

[0115] In an embodiment, the hardware-in-the-loop simulation includes:

[0116] The real EBCU unit and the real TCU unit are used to replace the EBCU model and the TCU model in the loop simulation, a hardware-in-the-loop simulation is formed, the instruction signal model, the PBCU model, the foundation brake unit model and the dynamics model are run in the real-time simulator through the processor board card, the hardware-in-the-loop simulation data is output, and is transmitted to the IO interface board card through the communication bus.

[0117] In a specific implementation, the EBCU model, the TCU model and the dynamics model are run in the NI real-time simulator, project engineering management and simulation control are performed by the NI Veristand software; the real EBCU unit and the real TCU unit are used to replace the EBCU model and the TCU model in the loop simulation, the peripheral components of the whole vehicle EBCU and TCU are run on different hardware, and the distributed collaborative closed-loop simulation of the hardware-in-the-loop is realized.

[0118] The whole vehicle brake system and the traction system are decomposed according to the vehicle marshalling, simulation of each vehicle is first realized independently, and then simulation data between vehicles, at least including pipeline flow and pressure, hook buffer force and the like, is synchronously transmitted through a data bus, that is, an Ethernet or a reflective memory. The hardware-in-the-loop simulation includes a system joint test console, multiple semi-physical simulation cabinets and multiple communication networks, is compatible with motor cars, passenger cars and urban rail vehicles, and can meet the test requirements of any marshalling vehicle.

[0119] The system joint test console hardware includes semi-physical simulation cabinets, an industrial computer, a switch 1 and a real CCU, as shown in Figures 1 to 7 The industrial computer is topologically connected with each cabinet real-time simulator through the switch 1, can index each real-time simulator through an IP address, and correspondingly, a test management software run in the industrial computer configures a vehicle test environment, realizes model compilation, model download, debugging and testing and the like. The industrial computer accesses the real CCU unit, collects internal data of the real EBCU, the TCU and the CCU in a real vehicle network such as an MVB, a TRDP and the like, and correspondingly, a vehicle comprehensive monitoring software run in the industrial computer performs real-time monitoring on the internal data.

[0120] The main processor board card of the real-time simulator runs simulation models, and communicates with the I / O interface board card through a communication bus, the communication bus can adopt a PCI bus, a PCI-Express bus and the like, the I / O interface board card outputs simulation data of the main processor board card as identifiable hardware signals, and simultaneously collects hardware signals as simulation model inputs, so that closed-loop simulation is realized. In particular, the simulation models run differently according to whether there is an air compressor and whether the vehicle is a motor car or a trailer.

[0121] The whole vehicle hardware-in-the-loop simulation architecture is as shown in Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 1 Figure 1 Figure 6 Figure 7As shown, the real-time simulator runs the controller model, the pneumatic control unit simulation model, the foundation brake unit model, the traction main circuit model, i.e. the motor vehicle and the dynamics model. The controller model outputs vehicle instructions such as traction and braking. The EBCU and TCU receive the instructions, and then output control instructions to the pneumatic control unit and the traction main circuit model after calculation. The relevant models receive the instructions, and then perform relevant simulation calculation and processing. The brake torque and traction torque are output to the dynamics model. The dynamics model combines the basic parameters of the vehicle to perform calculation, and outputs parameters such as shaft speed and braking distance. The parameters are fed back to the EBCU and TCU for collection, thereby forming a closed-loop simulation.

[0122] In the embodiment, the data intelligent analysis area comprises that according to the vehicle data and the vehicle simulation data, the data intelligent analysis area performs remote fault reproduction and fault diagnosis on the train braking system through the fault injection function of the fault injection test box.

[0123] In the specific implementation, the data intelligent analysis area contains an expert diagnosis system, and the functions include: 1) to realize comparative analysis of simulation data and real vehicle data, and to give simulation credibility; 2) to perform remote fault reproduction and fault diagnosis on the operating vehicle, to reproduce real vehicle faults through the fault injection function of the system simulation area, to remotely analyze fault causes, and to give recommended fault elimination schemes; 3) to evaluate the current health status of parts according to the system state degradation trend, working condition and load, and historical maintenance data, in combination with real-time real vehicle data, to provide basis for fault prediction and operation and maintenance decision. Part of the model prediction and operation and maintenance decision is as follows, and the threshold in the model is determined according to comprehensive analysis of real vehicle data of the data acquisition area and simulation data of the system simulation area:

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[0129] In summary, the train brake system distributed collaborative analysis platform proposed in the application builds a simulation scene library, a data synchronous acquisition area and a data intelligent analysis area, realizes synchronous access of real vehicle data of the brake system, completes calibration of the model based on the data, and completes data analysis through expert systems and other automated intelligent means, thereby realizing parallel research and development simulation test collaborative design, reducing the research and development cycle and comprehensive cost of the product. The simulation scene library of the application covers all stages of research and development, including model-in-the-loop, rapid control prototype and hardware-in-the-loop simulation scenes, and meets different research and development needs with real-time simulation machines and software model schemes. Virtual simulation or semi-physical simulation is used to replace whole-vehicle physical bench test or line test, which is good in universality and scalability, shortens the research and development cycle and greatly reduces the research and development cost. The simulation scenes of the application all adopt closed-loop simulation testing, especially for anti-skid control logic verification, and the system test result has high confidence and wide test coverage. In an absolutely safe environment, control logic verification under low adhesion and ultra-low adhesion conditions is realized. The simulation scenes of the application meet the safety logic verification of each product fault of the brake system, and test is performed through a fault test injection box to simulate fault conditions, such as sensor short circuit, open circuit and drift, thereby reducing the risk coefficient of real vehicle line test. The application can be self-upgraded through real vehicle data injection, comparison of real vehicle test data and simulation data, optimization of the simulation model, and improvement of the model maturity and confidence. The data intelligent analysis area of the application contains an expert diagnosis system, and can realize remote fault reproduction, fault diagnosis and fault prediction of the brake system, and improve the operation and maintenance level of the brake system.

[0130] The above-described embodiments only express several embodiments of the application, and the description is relatively specific and detailed, but it should not be understood as limiting the scope of the patent. It should be noted that for ordinary skilled in the art, without departing from the concept of the application, several modifications and improvements can be made, which are all within the protection scope of the application. Therefore, the protection scope of the patent of the application should be subject to the protection scope of the appended claims.

Claims

1. A distributed collaborative analysis platform for train braking systems, characterized in that, The distributed collaborative analysis platform for the train braking system includes: The system simulation area and the data acquisition area collect vehicle data and transmit it to the system simulation area. The system simulation area outputs vehicle simulation data based on the vehicle data through model-in-the-loop simulation, rapid control prototype simulation and hardware-in-the-loop simulation. The data intelligent analysis area diagnoses the train braking system based on the vehicle data and the vehicle simulation data, and outputs solutions to eliminate the faults based on the diagnosis results. The system simulation area includes a hardware-in-the-loop cabinet, an industrial computer, a switch, and a real CCU unit. The industrial control computer collects vehicle simulation data output from the hardware-in-the-loop simulation cabinet through the switch. The hardware-in-the-loop simulation cabinet outputs the vehicle simulation data through the model-in-the-loop simulation, the rapid control prototype simulation, and the hardware-in-the-loop simulation. The semi-physical simulation cabinet includes a real-time simulation system, multiple real EBCU units, and multiple real TCU units. The real-time simulation system transmits the final simulation data to the real EBCU units and the real TCU units. The industrial control computer collects the real EBCU unit data and the real TCU unit data, i.e., the vehicle simulation data, through the real CCU units.

2. The distributed collaborative analysis platform for train braking systems according to claim 1, characterized in that, The real-time simulation system includes: A real-time simulator, comprising a processor board and an I / O interface board, wherein the processor board runs a simulation model and outputs first simulation data, and the I / O interface board converts the first simulation data into second simulation data that can be recognized. A signal conditioning box, which, after receiving the second simulation data, conditions the second simulation data to obtain the conditioned third simulation data; A fault injection test chamber receives the third simulation data, performs fault testing on the system based on the third simulation data, and then outputs fourth simulation data. A signal adapter box receives the fourth simulation data and adapts it to obtain the final simulation data. The power management module provides AC / DC power to the signal conditioning box, the fault injection test box, and the signal adapter box, and enables overcurrent, overvoltage, and leakage protection. The first simulation data includes model-in-the-loop simulation data, rapid control prototype simulation data, and hardware online simulation data.

3. The distributed collaborative analysis platform for train braking systems according to claim 2, characterized in that, The model-in-the-loop simulation includes running the instruction signal model, TCU model, EBCU model, PBCU model, basic braking unit model, and dynamic model through the processor board in the real-time simulator, outputting the model-in-the-loop simulation data, and transmitting it to the IO interface board through the communication bus.

4. The distributed collaborative analysis platform for train braking systems according to claim 3, characterized in that, The model-in-the-loop simulation also includes: The command signal model, the EBCU model, the TCU model, and the basic braking unit model were established using Matlab / Simulink. The PBCU model was established using AMESim software. The dynamic model is established using SimPack or SimulationX software.

5. The distributed collaborative analysis platform for train braking systems according to claim 3, characterized in that, The model-in-the-loop simulation also includes; The command signal model is used to import vehicle data into the real-time simulator according to a protocol format, and the command signal model outputs vehicle commands based on the vehicle data. The TCU model outputs an electric braking feedback signal to the EBCU model and outputs traction force or electric braking force to the dynamics model according to the vehicle command. The EBCU model includes a logic algorithm model and a valve drive model. The logic algorithm model outputs the pre-control pressure at the current moment based on the vehicle command, the feedback signal output by the dynamics model, and the electric braking feedback signal. The valve drive model outputs the valve control signal based on the pre-control pressure and the actual brake cylinder pressure output by the PBCU model. The PBCU model receives the valve control signal, outputs the brake cylinder pressure signal, and feeds it back to the EBCU model. A basic braking unit model, wherein the basic braking unit model receives the brake cylinder pressure signal and outputs air braking force; The dynamic model receives the air braking force and the traction force or electric braking force, outputs the first simulation data, feeds it back to the IO interface board, and simultaneously feeds it back to the TCU model and the EBCU model to form a closed-loop simulation.

6. The distributed collaborative analysis platform for train braking systems according to claim 3, characterized in that, The rapid control prototype simulation includes: The PBCU model and the basic braking unit model in the model-in-the-loop simulation are replaced by real PBCU units and real basic braking units to form a rapid control prototype simulation. The instruction signal model, the TCU model, the EBCU model and the dynamic model are run in the real-time simulator through the processor board to output the rapid control prototype simulation data, and the data is transmitted to the IO interface board through the communication bus.

7. The distributed collaborative analysis platform for train braking systems according to claim 3, characterized in that, The hardware-in-the-loop simulation includes: The hardware-in-the-loop simulation is formed by replacing the EBCU model and the TCU model in the model-in-the-loop simulation with real EBCU and real TCU units. The instruction signal model, the PBCU model, the basic braking unit model and the dynamic model are run in the real-time simulator through the processor board, and the hardware-in-the-loop simulation data is output and transmitted to the IO interface board through the communication bus.

8. The distributed collaborative analysis platform for train braking systems according to claim 2, characterized in that, The intelligent data analysis area includes a function that, based on the vehicle data and the vehicle simulation data, remotely reproduces and diagnoses faults in the train braking system using the fault injection function of the fault injection test box.

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