Pressure wave control method of railway vehicle, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a pressure wave control method for a railway vehicle, electronic equipment and a storage medium, and the method comprises the steps: determining a first carriage internal pressure value of the railway vehicle at the current moment based on a carriage external pressure value and a carriage internal and external pressure transmission model of the railway vehicle on a target running route at the current moment; and based on the first carriage internal pressure value and a second carriage internal pressure value of the railway vehicle at the previous moment, the carriage internal pressure change rate corresponding to the railway vehicle is determined. And determining the carbon dioxide concentration in the railway vehicle at the current moment based on the pressure wave protection valve state information at the current moment. Based on the carriage internal pressure change rate and the carbon dioxide concentration at the current moment, whether the pressure wave protection valve corresponding to the railway vehicle is opened or not is controlled, and cooperative control over opening of the pressure protection valve based on the carriage internal pressure change rate and the carbon dioxide concentration in the line environment is achieved. The pressure change and the carbon dioxide concentration in the compartment are adjusted, and the comfort of the environment in the vehicle is ensured.

Description

Technical Field

[0001] The present application relates to a pressure control technology, and in particular to a pressure wave control method for a rail vehicle, an electronic device, and a storage medium. Background Art

[0002] In the rail transit sector, trains encounter a variety of complex operating conditions during operation. For example, when passing through tunnels or passing other trains, the external pressure of the train can fluctuate significantly. Due to the lack of airtightness in trains, these external pressure changes are directly or indirectly transmitted to the interior of the train, causing internal pressure fluctuations. These internal pressure fluctuations can cause a sense of pressure on passengers' eardrums, leading to discomfort and even health risks. Therefore, how to effectively suppress the transmission of external pressure fluctuations into the train and control internal pressure fluctuations has become a key issue in improving train ride comfort.

[0003] At present, many rail vehicles use a passive pressure protection system, which is mainly based on the single environmental factor of the tunnel. By controlling the opening and closing status of the fresh air valve and the exhaust valve, the system adjusts the fresh air volume, exhaust air volume and pressure fluctuations in the vehicle.

[0004] However, this passive pressure protection system lacks specific prediction and design based on line characteristics (such as tunnel length, tunnel shape, and train speed), resulting in insufficient adaptability of the pressure wave control method to the actual operating line. This incompatibility can lead to problems such as excessive pressure change rates or excessive CO2 concentrations within the vehicle, reducing passenger comfort and potentially adversely affecting the health of the onboard environment. Summary of the Invention

[0005] In order to solve one of the above-mentioned technical defects, the embodiments of the present application provide a pressure wave control method for a rail vehicle, as well as electronic equipment and storage media, for dynamically predicting the internal pressure change rate and carbon dioxide concentration of the car according to the line characteristics and train operating conditions, so as to coordinately control the opening of the pressure protection valve and ensure the comfort of the interior environment.

[0006] According to a first aspect of an embodiment of the present application, a pressure wave control method for a rail vehicle is provided, the method comprising:

[0007] Using a geometric model corresponding to the rail vehicle, determining a current external pressure value of the rail vehicle on the target operating route;

[0008] Determining a first compartment internal pressure value of the rail vehicle at a current moment based on the compartment external pressure value and a compartment internal and external pressure transmission model corresponding to the rail vehicle at a current moment;

[0009] Determining a pressure change rate of the compartment corresponding to the rail vehicle based on the first compartment internal pressure value and a second compartment internal pressure value of the rail vehicle at a previous moment;

[0010] determining a carbon dioxide concentration in the rail vehicle at a current moment based on the pressure wave protection valve state information at a current moment;

[0011] Based on the pressure change rate inside the carriage and the carbon dioxide concentration, it is determined whether the target valve opening condition of the pressure wave protection valve is met at the current moment. If so, the pressure wave protection valve corresponding to the rail vehicle is controlled to open.

[0012] According to a second aspect of an embodiment of the present application, a pressure wave control device for a rail vehicle is provided, the device comprising:

[0013] A first determining module is configured to determine a vehicle compartment external pressure value of the rail vehicle on a target operating route at a current moment using a geometric model corresponding to the rail vehicle;

[0014] a second determining module, configured to determine a first compartment internal pressure value of the rail vehicle at a current moment based on the compartment external pressure value and a compartment internal and external pressure transmission model corresponding to the rail vehicle at a current moment;

[0015] a third determining module, configured to determine a rate of change of the compartment internal pressure corresponding to the rail vehicle based on the first compartment internal pressure value and a second compartment internal pressure value of the rail vehicle at a previous moment;

[0016] a fourth determining module, configured to determine the carbon dioxide concentration in the rail vehicle at a current moment based on the state information of the pressure wave protection valve at a current moment;

[0017] The control module is used to determine whether the target valve opening condition of the pressure wave protection valve is met at the current moment based on the pressure change rate inside the carriage and the carbon dioxide concentration. If so, the pressure wave protection valve corresponding to the rail vehicle is controlled to open.

[0018] According to a third aspect of an embodiment of the present application, a pressure wave control device is provided, comprising: a memory and a processor; the memory is used to store a computer program; the processor is coupled to the memory and is used to execute the computer program to implement each step in the pressure wave control method for a rail vehicle provided in an embodiment of the present application.

[0019] An embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor implements the steps of the pressure wave control method for a rail vehicle provided in the embodiment of the present application.

[0020] Using the pressure wave control scheme for rail vehicles provided in the embodiments of the present application, the current operating state of the rail vehicle is simulated using a numerical simulation of the rail vehicle's corresponding geometric model to determine the current external pressure value of the rail vehicle on the target operating route. This allows for an accurate prediction of the external pressure value experienced by the rail vehicle under the current train operating conditions. Furthermore, based on the external pressure value and the current internal and external pressure transmission model corresponding to the rail vehicle, the first internal pressure value experienced by the rail vehicle under the current train operating conditions is accurately predicted. Based on the current first internal pressure value and the second internal pressure value experienced by the rail vehicle at the previous moment, the corresponding internal pressure change rate is determined to accurately determine the internal pressure change of the rail vehicle under the current train operating conditions. Furthermore, based on the current pressure wave protection valve status information, the carbon dioxide concentration within the rail vehicle is predicted. Furthermore, based on the predicted changes in the vehicle's internal pressure under the current train operating conditions and the carbon dioxide concentration in the rail vehicle, it is determined whether to open the pressure wave protection valve, so as to dynamically predict the pressure change rate and carbon dioxide concentration inside the car according to the line characteristics and train operating conditions, so as to coordinately control the opening of the pressure protection valve, and then adjust the pressure changes and carbon dioxide concentration in the car to ensure the comfort of the interior environment, so as to solve the problems of insufficient adaptability and poor control effect of the existing passive pressure protection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0022] Figure 1 A flow chart of a pressure wave control method for a rail vehicle provided in an embodiment of the present application;

[0023] Figure 2 A flow chart of another pressure wave control method for a rail vehicle provided in an embodiment of the present application;

[0024] Figure 3 A flow chart of determining a pressure transmission model inside and outside the carriage corresponding to a rail vehicle at the current moment provided in an embodiment of the present application;

[0025] Figure 4 A first internal pressure curve and a schematic diagram of a measured internal pressure curve provided in an embodiment of the present application;

[0026] Figure 5 A pressure wave control device for a rail vehicle is provided as an exemplary embodiment of the present application;

[0027] Figure 6A schematic structural diagram of a pressure wave control device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the technical solutions and advantages of the embodiments of the present application more clearly understood, the exemplary embodiments of the present application are further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, and are not an exhaustive list of all the embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other unless they conflict.

[0029] In the process of implementing this application, the inventor discovered that in order to meet the operating conditions in high-altitude continuous tunnels and avoid the influence of the external environment on the internal pressure of the car, the switch of the pressure wave protection valve is closed. However, when entering a longer continuous tunnel, the switch of the pressure wave protection valve is closed for a long time, which will cause the carbon dioxide concentration in the car to increase rapidly. After the switch of the pressure wave protection valve is opened, the air is thin and the ability to replenish fresh air is insufficient, threatening the health of passengers. It is impossible to achieve the technical problem of coordinated control of the pressure change in the car and the carbon dioxide in the car in line environments such as altitude differences, large slopes and multiple tunnels.

[0030] To address the above-mentioned issues, embodiments of the present application provide a method for controlling pressure waves in rail vehicles. This method uses numerical simulation to predict the external pressure value experienced by the rail vehicle under the current train operating conditions. Based on the external pressure value and the current internal and external pressure transmission model for the rail vehicle, a first internal pressure value experienced by the rail vehicle under the current train operating conditions is predicted. Furthermore, based on the current first internal pressure value and the previous second internal pressure value, the corresponding internal pressure change rate for the rail vehicle under the current train operating conditions is determined. Furthermore, based on the current state information of the pressure wave protection valve, the carbon dioxide concentration within the rail vehicle is predicted. Based on the predicted internal pressure change and carbon dioxide concentration within the rail vehicle under the current train operating conditions, whether to open the pressure wave protection valve is determined. This method dynamically predicts the internal pressure change rate and carbon dioxide concentration based on line characteristics and train operating conditions, allowing for coordinated control of the opening of the pressure protection valve, thereby adjusting the internal pressure change and carbon dioxide concentration to ensure a comfortable interior environment at all times along the target route.

[0031] The pressure wave control scheme for rail vehicles provided in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0032] The pressure wave control method for a rail vehicle provided in the embodiments of the present application can be performed by an electronic device, which can be a terminal device such as a PC, a laptop, a smartphone, or a server. The server can be a physical server including an independent host, a virtual server, a cloud server, or a server cluster.

[0033] Figure 1 A flow chart of a pressure wave control method for a rail vehicle provided in an embodiment of the present application is shown as follows: Figure 1 As shown, the following steps may be included:

[0034] 101. Using the geometric model corresponding to the rail vehicle, determine the external pressure value of the rail vehicle on the target running route at the current moment.

[0035] 102. Determine a first compartment internal pressure value of the rail vehicle at the current moment based on the compartment external pressure value and a compartment internal and external pressure transmission model corresponding to the rail vehicle at the current moment.

[0036] 103. Determine a corresponding carriage internal pressure change rate of the rail vehicle based on the first carriage internal pressure value and the second carriage internal pressure value of the rail vehicle at a previous moment.

[0037] 104. Determine the carbon dioxide concentration in the rail vehicle at the current moment based on the current state information of the pressure wave protection valve.

[0038] 105. Based on the pressure change rate and carbon dioxide concentration inside the carriage, determine whether the target valve opening condition of the pressure wave protection valve is met at the current moment. If so, control the opening of the pressure wave protection valve corresponding to the rail vehicle.

[0039] In practical applications, in order to ensure that the pressure change rate and carbon dioxide concentration within the rail vehicle meet standard requirements in various environments along various operating routes, thereby ensuring passenger comfort within the rail vehicle, the rail vehicle pressure wave control method provided in the embodiments of the present application can be used to control the opening and closing of the pressure wave protection valves within each rail vehicle. The rail vehicle can be a high-speed train, subway, or other vehicle that runs along tracks.

[0040] During specific implementation, first, the geometric model corresponding to the rail vehicle can be used to determine the external pressure value of the rail vehicle on the target operating route at the current moment. In practical applications, in order to more accurately predict the external pressure value of the rail vehicle on the corresponding target operating route at the current moment, a geometric model corresponding to the rail vehicle can be first constructed, and the geometric model corresponding to the rail vehicle can be used to numerically simulate the operating state of the rail vehicle at the current moment to determine the external pressure value of the rail vehicle on the target operating route at the current moment. In this way, the external pressure value of the rail vehicle under the current train operating conditions can be accurately simulated and predicted.

[0041] Among them, in an optional embodiment, the specific implementation method of using the geometric model corresponding to the rail vehicle to determine the external pressure value of the carriage of the rail vehicle on the target operating route at the current moment can be: establishing the geometric model corresponding to the rail vehicle; extracting the frequency spectrum characteristics of the tunnel pressure to which the rail vehicle is subjected in the target operating route; using the geometric model corresponding to the rail vehicle, based on the frequency spectrum characteristics and a set of one-dimensional flow control equations, determine the external pressure value of the carriage of the rail vehicle at the current moment, so as to accurately simulate the external pressure value to which the rail vehicle is subjected under the current train operating conditions.

[0042] Numerical simulation of train aerodynamics falls under the umbrella of computational fluid dynamics (CFD). This involves using numerical methods to solve the flow equations describing the flow field and obtain relevant flow field information. Unaffected by inherent experimental constraints (such as interference from wind tunnel walls and model supports), numerical simulations can independently consider various phenomena or conditions, providing a deeper understanding of the mechanisms of various flow phenomena and obtaining quantitative results for nonlinear problems. During the engineering design process, computational calculations can yield a wealth of flow field information, enabling the comparison of multiple alternatives. With its short research cycle and low cost, numerical simulations offer advantages over various model and vehicle tests, making them a crucial tool for train aerodynamic research.

[0043] Compressibility is a fundamental property of fluids; all fluids are compressible. However, when the effects of changes in fluid density on flow can be neglected, the incompressible flow assumption—that is, the density is constant—can be used. Generally, because trains travel at relatively low speeds, they can be treated as incompressible viscous fluids. However, when studying issues like trains passing through tunnels, the compressibility of air must be considered. Therefore, the equations required for numerical solution in this report are the fundamental governing equations for compressible flow.

[0044] After determining the external pressure value of the carriage corresponding to the current train operating condition of the rail vehicle, the internal and external pressure transmission model of the rail vehicle corresponding to the current moment is obtained, and based on the external pressure value of the carriage and the internal and external pressure transmission model of the rail vehicle corresponding to the current moment, the first internal pressure value of the rail vehicle at the current moment is determined.

[0045] The pressure transfer model inside and outside the carriage can be used to characterize the dynamic changes in pressure inside and outside the carriage and the laws governing its transfer during rail vehicle operation. The carriage is generally assumed to be a rigid, elastic, sealed container with multiple leaks (such as window and door gaps and ventilation systems). Air flow follows the law of conservation of mass and the ideal gas equation of state, and the pressure transfer process is approximately an adiabatic and isentropic process.

[0046] Moreover, in practical applications, actual vehicle tests can be conducted on the rail vehicle to determine the corresponding external and internal pressure values ​​of the carriage when the rail vehicle passes through a tunnel or other working conditions, and based on the external and internal pressure values ​​of the carriage obtained in the test, a pressure transmission model inside and outside the carriage corresponding to the rail vehicle can be constructed.

[0047] In an optional embodiment, a pressure transmission model between the inside and outside of the vehicle compartment based on the airtightness index may be used. For example, the pressure transmission model between the inside and outside of the vehicle compartment based on the airtightness index is defined as:

[0048]

[0049] Where pi and pe are the internal and external pressures of the carriage, respectively. τ is the dynamic airtightness index of the carriage, which quantifies the level of airtightness performance. Its existence establishes a mathematical and logical connection between the transfer path characteristics of rail vehicle carriages and the pressure transfer model.

[0050] Under the premise that the external pressure value pe of the car has been solved, the corresponding change characteristic result of the internal pressure value pi of the car can be obtained by solving the internal and external pressure transmission model equation (1). By specifying different values ​​for the dynamic airtightness index τ in the internal and external transmission model equation (1), the internal pressure change characteristics of the car with different sealing performance levels can be obtained. In actual application, the pressure protection valve in the rail vehicle corresponds to a variety of different states, for example, the pressure wave protection valve is in a fully open state, only the pressure wave protection valves at the two fresh air inlets are in an open state, only the pressure wave protection valves at the two exhaust outlets are in an open state, the pressure wave protection valve is in a fully closed state, only one fresh air inlet pressure wave protection valve is in an open state, and only one exhaust outlet pressure wave protection valve is in an open state. Moreover, when the pressure protection valve in the rail vehicle is in different states, the sealing performance of the car is also different, that is, when the pressure protection valve in the rail vehicle is in different states, it corresponds to different dynamic airtightness indexes.

[0051] Therefore, in an embodiment of the present application, in order to more accurately predict the internal pressure value of the carriage corresponding to the rail vehicle at the current moment, the internal and external pressure transmission model of the rail vehicle corresponding to the current moment can be determined based on the status information of the pressure wave protection valve in the rail vehicle at the current moment, and by solving the internal and external pressure transmission model of the rail vehicle corresponding to the rail vehicle, the first internal pressure value of the carriage corresponding to the rail vehicle at the current moment can be accurately calculated.

[0052] In other words, the calculation of the pressure change characteristics inside the carriage under the action of the external pressure of the rail vehicle can be obtained by solving the pressure transmission model inside and outside the carriage based on the air tightness index.

[0053] Next, based on the current first vehicle compartment pressure value and the previous second vehicle compartment pressure value, the corresponding vehicle compartment pressure change rate is determined. The vehicle compartment pressure change rate is a key parameter in the field of rail vehicle environmental control and can be used to characterize passenger comfort and vehicle body structural performance. By collecting the corresponding vehicle compartment pressure change rate, passenger comfort and vehicle body airtightness levels can be determined at the current moment.

[0054] Among them, the pressure difference between the internal pressure value of the first compartment of the rail vehicle at the current moment and the internal pressure value of the second compartment of the rail vehicle at the previous moment can be obtained, the time difference between the current moment and the previous moment can be obtained, the ratio of the pressure difference to the time difference can be determined, and the ratio can be determined as the internal pressure change rate of the corresponding compartment of the rail vehicle.

[0055] Research has found that not only does the rate of change of internal pressure in rail vehicle compartments affect passenger comfort, but so does the carbon dioxide concentration within the vehicle. For example, to meet the requirements of operating in high-altitude continuous tunnels, the pressure surge protection valve is closed to prevent the external environment from affecting the internal pressure of the vehicle compartment. However, when entering a long continuous tunnel, keeping the pressure surge protection valve closed for a long time can cause the carbon dioxide concentration within the vehicle to rise rapidly, affecting passenger comfort. Therefore, in order to achieve coordinated control of internal pressure changes and carbon dioxide concentration in line environments such as altitude differences, steep slopes, and multiple tunnels, the opening and closing of the pressure protection valve within the rail vehicle is controlled.

[0056] Specifically, the current carbon dioxide concentration within the rail vehicle is determined based on the current state information of the pressure surge protection valve. This information can be used to collect information about the rail vehicle's operating environment, such as the carbon dioxide concentration, fresh air volume, passenger capacity, and station gate opening and closing times. Using this information, a carbon dioxide concentration prediction model is established to determine how the operating mode of the corresponding pressure surge protection valve affects the carbon dioxide concentration within the rail vehicle. Based on this carbon dioxide concentration prediction model and the current state information of the pressure surge protection valve, the current carbon dioxide concentration within the rail vehicle is determined.

[0057] Finally, based on the current internal pressure change rate of the rail vehicle and the current carbon dioxide concentration in the rail vehicle, it is determined whether the target valve opening condition of the pressure wave protection valve is met at the current moment. If so, the pressure wave protection valve corresponding to the rail vehicle is controlled to open.

[0058] The target valve opening condition can also be comprehensively determined based on factors such as the running position and running speed of the rail vehicle, the pressure changes inside and outside the car, and the carbon dioxide concentration inside the car, or can be determined directly based on the pressure changes inside and outside the car. It can be set according to actual needs. For example, in an optional embodiment, the target valve opening condition is set as follows: |ADP(t)|≤200Pa and |ADP(t)-ADP(t-1000ms)|≤200Pa. Wherein, t represents the current moment, ADP(t) represents the pressure difference between the inside and outside of the car at the current moment, and ADP(t-1000ms) represents the pressure difference between the inside and outside of the car 1000ms ago.

[0059] During specific implementation, the target valve opening conditions corresponding to the pressure wave protection valve can be set in advance. When it is judged whether the target valve opening conditions of the pressure wave protection valve are met at the current moment based on the pressure change rate inside the carriage of the rail vehicle at the current moment and the carbon dioxide concentration in the rail vehicle at the current moment, the pressure protection valve corresponding to the rail vehicle can be controlled to open.

[0060] In summary, the embodiments of the present application simulate the operating state of the rail vehicle at the current moment by numerically simulating the geometric model corresponding to the rail vehicle to determine the external pressure value of the rail vehicle on the target operating route at the current moment. This can accurately predict the external pressure value of the rail vehicle under the current train operating conditions. Furthermore, based on the external pressure value of the carriage and the internal and external pressure transmission model corresponding to the rail vehicle at the current moment, the first internal pressure value of the rail vehicle under the current train operating conditions is accurately predicted. Based on the first internal pressure value corresponding to the current moment and the second internal pressure value of the rail vehicle at the previous moment, the corresponding internal pressure change rate of the rail vehicle is determined to accurately determine the change in the vehicle's internal pressure under the current train operating conditions. In addition, based on the current pressure wave protection valve status information, the carbon dioxide concentration in the rail vehicle is predicted. Furthermore, based on the predicted changes in the vehicle's internal pressure under the current train operating conditions and the carbon dioxide concentration in the rail vehicle, it is determined whether to open the pressure wave protection valve, so as to dynamically predict the pressure change rate and carbon dioxide concentration inside the car according to the line characteristics and train operating conditions, so as to coordinately control the opening of the pressure protection valve, and then adjust the pressure changes and carbon dioxide concentration in the car to ensure the comfort of the interior environment, so as to solve the problems of insufficient adaptability and poor control effect of the existing passive pressure protection system.

[0061] The above embodiment describes that the corresponding internal pressure change rate of the rail vehicle at each moment during the operation of the rail vehicle and the carbon dioxide concentration in the rail vehicle can be predicted for each operating route, and based on the corresponding internal pressure change rate and carbon dioxide concentration of the rail vehicle at each moment on each operating route, whether to open the pressure wave protection valve in the rail vehicle is dynamically controlled, so as to realize the coordinated control of the valve opening operation of the pressure wave protection valve by utilizing the internal pressure change rate and carbon dioxide concentration of the rail vehicle. However, in actual applications, it is also necessary to close the pressure protection valve in the rail vehicle in a timely manner according to the actual working conditions to ensure that the rail vehicle can always ensure the comfort of passengers during operation. The specific implementation process of controlling the closure of the pressure protection valve in the rail vehicle is described in detail in conjunction with the following embodiments.

[0062] Figure 2 A flow chart of another method for controlling pressure waves of a rail vehicle provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, based on the above embodiment, the method may further include the following steps:

[0063] 201. Based on the pressure change rate and carbon dioxide concentration inside the vehicle compartment, determine whether the closing conditions of the pressure wave protection valve are met at the current moment.

[0064] 202. If the conditions are met, control the closing of the pressure wave protection valve corresponding to the rail vehicle.

[0065] During specific implementation, the preset valve closing condition corresponding to the pressure protection valve can be preset.

[0066] For example, in an optional embodiment, four preset valve closing conditions are pre-set. Valve closing condition 1: |ADP(t)| > 500 Pa. Valve closing condition 2: |ADP(t) - ADP(t-50 ms)| > 80 Pa. Valve closing condition 3: |ADP(t) - ADP(t-200 ms)| > 90 Pa. Valve closing condition 4: |ADP(t) - ADP(t-200 ms)| > 50 Pa and |ADP(t-200 ms) - ADP(t-400 ms)| > 50 Pa and |ADP(t-400 ms) - ADP(t-600 ms)| > 50 Pa.

[0067] Where t represents the current moment, ADP(t) represents the pressure difference between the interior and exterior of the vehicle at the current moment, and ADP(t-50ms), ADP(t-200ms), ADP(t-400ms), and ADP(t-600ms) represent the pressure differences between the interior and exterior of the vehicle 50ms, 200ms, 400ms, and 600ms ago, respectively.

[0068] However, in actual applications, in order to coordinately control the closing of the pressure wave protection valve in combination with the corresponding internal pressure change rate of the rail vehicle and the carbon dioxide concentration in the rail vehicle, the preset valve closing conditions corresponding to the pressure wave protection valve can be set according to the internal pressure change rate of the rail vehicle and the carbon dioxide concentration in the rail vehicle.

[0069] The preset valve closing conditions can be optimized to achieve coordinated control of the closing of the pressure wave protection valve by combining the rate of change of the internal pressure of the rail vehicle compartment and the carbon dioxide concentration within the rail vehicle. Specifically, in an optional embodiment, a particle swarm algorithm can be used to optimize the pressure wave control parameters in the preset valve closing conditions corresponding to the rail vehicle to obtain optimized pressure wave control parameters. Based on the optimized pressure wave control parameters and the preset valve closing conditions, a target valve closing condition for the pressure wave protection valve within the rail vehicle is determined, and the target valve closing condition is used to control the closing of the pressure wave protection valve within the rail vehicle.

[0070] Continuing with the above example, the 500 Pa in the above valve closing condition 1 can be used as the pressure wave control parameter, and the particle swarm algorithm can be used to optimize the pressure wave control parameters in multiple preset valve closing conditions corresponding to the rail vehicle to determine the limit values ​​corresponding to the pressure wave control parameters, so that the carbon dioxide concentration in the car and the pressure change rate inside the car meet the requirements at the same time, and the optimal solution corresponding to each pressure wave control parameter is obtained, and the optimal solution corresponding to each pressure wave control parameter is determined as the limit value corresponding to each pressure wave control parameter.

[0071] Next, based on the current internal pressure change rate of the car and the current carbon dioxide concentration in the car, determine whether the closing conditions of the pressure wave protection valve are met at the current moment. If it is determined that the closing conditions of the pressure wave protection valve are not met at the current moment, continue to maintain the state corresponding to the original pressure wave protection valve. If it is determined that the closing conditions of the pressure wave protection valve are met at the current moment, control the closing of the pressure wave protection valve corresponding to the rail vehicle.

[0072] In an embodiment of the present application, whether the closing conditions of the pressure wave protection valve are met at the current moment is determined based on the current internal pressure change rate of the car and the CO2 concentration in the car, so as to control the closing operation of the pressure wave protection valve corresponding to the rail vehicle. This realizes the coordinated control of the closing of the pressure protection valve by combining the current internal pressure change rate of the car and the CO2 concentration in the car, so as to dynamically adjust the pressure change and carbon dioxide concentration in the car, ensure the comfort of the interior environment, and solve the problems of insufficient adaptability and poor control effect of the existing passive pressure protection system.

[0073] The above embodiment describes how, when controlling the pressure protection valve within a rail vehicle, it is necessary to determine the first internal pressure value of the rail vehicle at the current moment based on the internal and external pressure transmission model corresponding to the rail vehicle at the current moment. Different states of the pressure wave protection valve correspond to different dynamic airtightness indices, i.e., different internal and external pressure transmission models. Therefore, before determining the first internal pressure value of the rail vehicle at the current moment, the internal and external pressure transmission model corresponding to the rail vehicle at the current moment can be determined. The following provides an exemplary description of determining the internal and external pressure transmission model corresponding to the rail vehicle at the current moment.

[0074] Figure 3 This is a flow chart of an embodiment of the present application for determining the pressure transmission model inside and outside the vehicle compartment corresponding to the current moment of the rail vehicle. Figure 3 As shown, the method may specifically include the following steps:

[0075] 301. Obtain status information corresponding to the pressure wave protection valve at the current moment.

[0076] 302. Determine a dynamic air tightness index corresponding to the rail vehicle at the current moment based on the state information.

[0077] 303. Based on the dynamic air tightness index corresponding to the rail vehicle at the current moment, determine the internal and external pressure transmission model corresponding to the rail vehicle at the current moment.

[0078] First, the state information corresponding to the pressure wave protection valve at the current moment is obtained, and based on the state information corresponding to the pressure wave protection valve at the current moment, the dynamic airtightness index corresponding to the rail vehicle at the current moment is determined.

[0079] In an optional embodiment, the process of determining the dynamic airtightness index can be determined according to a method for calculating the dynamic airtightness index of a vehicle compartment having a structure of "Euler method-Euclidean distance (ED index)-three-part search algorithm". Among them, the Euler method is an ODE numerical solution algorithm, which can be used to discretize the differential equation corresponding to the pressure transmission model inside and outside the vehicle compartment, and calculate the internal pressure curve of the internal pressure changing with time. The ED index is used to quantify the difference between the internal pressure curve calculated by the Euler method and the measured curve. The three-part search algorithm is used to quickly find the dynamic airtightness index that minimizes the ED index within the known interval corresponding to the dynamic airtightness index.

[0080] Among them, the optimal dynamic airtightness index is found by using the Euler method (Euler method for short) and the ternary search algorithm (TernarySearch Algorithm) combined with the Euclidean distance (ED) indicator, so that the similarity between the calculated internal pressure curve and the measured internal pressure curve is maximized.

[0081] Specifically, a target interval for the dynamic airtightness index is obtained, and based on the target interval, a first search point and a second search point in the current search interval are determined. A first internal pressure curve corresponding to the first search point and a second internal pressure curve corresponding to the second search point are determined. A first similarity metric corresponding to the first search point is determined based on the first internal pressure curve corresponding to the first search point and the measured internal pressure curve, where the measured internal pressure curve is an internal pressure curve obtained by conducting experimental tests on a rail vehicle. A second similarity metric corresponding to the second search point is determined based on the second internal pressure curve corresponding to the second search point and the measured internal pressure curve. The search interval is updated based on the magnitude relationship between the first similarity metric and the second similarity metric. If the current calculation accuracy does not meet the set calculation accuracy, the first and second search points are re-determined using the updated search interval, and another search is performed, where the current calculation accuracy is determined based on the length of the current search interval. When the current calculation accuracy meets the required dynamic airtightness index calculation accuracy, the optimal calculation result for the current dynamic airtightness index is output. The optimal calculation result is determined as the dynamic airtightness index corresponding to the rail vehicle at the current moment.

[0082] An optional method for determining the first internal pressure curve corresponding to the search point is to obtain a preset internal / external pressure transmission model, where the dynamic airtightness index in the preset internal / external pressure transmission model is an undetermined constant. The preset internal / external pressure transmission model is numerically solved to obtain a preset internal pressure function. Based on the dynamic airtightness index corresponding to the first search point and the preset internal pressure function, the first internal pressure curve corresponding to the first search point is determined.

[0083] The similarity metric (ED index) corresponding to 50 different values ​​of the dynamic airtightness index τ in the range of 0 to 200 seconds was evaluated and calculated, and the final result of the τ calculation result for the car compartment in the current working condition example was determined to be 8.4 seconds. At the same time, compared with the calculated internal pressure curves corresponding to adjacent τ values, the calculated internal pressure time history curve corresponding to 8.4 seconds has a better similarity with the measured curve, so the Euclidean distance difference of the overall data is the smallest. For example, Figure 4 As shown, from Figure 4 It can be seen that the final value of τ determined, 8.4s, has a high degree of similarity with the measured internal pressure curve.

[0084] After the dynamic airtightness index corresponding to the current rail vehicle is determined, the dynamic airtightness index corresponding to the current rail vehicle is substituted into the preset internal and external pressure transmission model of the vehicle to obtain the internal and external pressure transmission model corresponding to the current rail vehicle.

[0085] In an embodiment of the present application, the dynamic air tightness index corresponding to the rail vehicle at the current moment is determined based on the status information corresponding to the pressure wave protection valve at the current moment, and the inside and outside pressure transmission model of the rail vehicle at the current moment is determined based on the dynamic air tightness index corresponding to the rail vehicle at the current moment. In this way, the inside and outside pressure transmission model of the rail vehicle at the current moment can be determined more accurately, and the real inside and outside pressure transmission relationship of the rail vehicle can be simulated more accurately, and then the first internal pressure value of the rail vehicle at the current moment can be calculated more accurately to provide a control effect.

[0086] An optional specific implementation method is described below for the implementation process of determining the carbon dioxide concentration in the rail vehicle at the current moment in the above embodiment.

[0087] Specifically, the number of passengers in the rail vehicle at the current moment and the corresponding air flow rate of the rail vehicle at the current moment can be obtained to construct a carbon dioxide concentration prediction model. Based on the current pressure wave protection valve status information, the number of passengers, the air flow rate, and the carbon dioxide concentration prediction model, the carbon dioxide concentration in the rail vehicle at the current moment is determined.

[0088] When constructing a carbon dioxide concentration prediction model, an original carbon dioxide concentration prediction model can be first obtained and then optimized to obtain a carbon dioxide concentration prediction model corresponding to the rail vehicle. Because the original carbon dioxide concentration prediction model does not take into account vehicle leakage, it causes carbon dioxide to increase too quickly after the pressure wave protection valve (fresh air) is closed. Therefore, in the embodiment of the present application, the original carbon dioxide concentration prediction model can be modified based on the actual vehicle test results to obtain a carbon dioxide concentration prediction model corresponding to the rail vehicle.

[0089] Among them, the CO2 concentration prediction model corresponding to the rail vehicle obtained after correction can be:

[0090]

[0091] Where QF = Qf_n + Qf_l, where Qfl is the train's CO2 leakage [m³ / h], Qfn is the fresh air flow rate [m³ / h]. Cint(t) is the CO2 concentration in the rail vehicle at time t [ppm]. Cext is the CO2 concentration in the fresh air [ppm]. V is the free volume inside the rail vehicle, i.e., the volume of air not occupied by passengers [m³]. Qf is the fresh air flow rate [m³ / h]. N is the number of passengers, and QPers is the amount of CO2 generated by one passenger [l / h].

[0092] In this way, by using the carbon dioxide concentration prediction model corresponding to the rail vehicle determined above, the carbon dioxide concentration in the rail vehicle compartment under various train operating conditions can be more accurately predicted dynamically, so as to accurately control the opening and closing of the rail vehicle pressure protection valve.

[0093] To facilitate understanding of the process of determining the target valve opening condition of the pressure wave protection valve in the rail vehicle in the above embodiment, a feasible method for determining the target valve opening condition of the pressure wave protection valve in the rail vehicle is introduced below.

[0094] Specifically, a preset valve opening condition corresponding to a pressure wave protection valve in a rail vehicle is determined, and a pressure wave control parameter in the preset valve opening condition is optimized to obtain an optimized pressure wave control parameter. Based on the optimized pressure wave control parameter and the preset valve opening condition, a target valve opening condition for the pressure wave protection valve in the rail vehicle is determined.

[0095] Among them, in an optional embodiment, the specific implementation process of optimizing the pressure wave control parameters in the preset valve opening conditions and obtaining the optimized pressure wave control parameters can be: randomly generating a group of particles, the position of each particle represents a group of pressure wave control parameters; calculating the fitness value of each particle according to the objective function; updating the individual optimum and the global optimum, recording the historical optimal position of each particle and the global optimal position of the entire group; updating the speed and position of each particle according to the particle swarm optimization formula; when the termination condition is met, outputting the optimal calculation result of the pressure wave control parameters in the current preset valve opening conditions; and determining the optimal calculation result of the pressure wave control parameters as the optimized pressure wave control parameters.

[0096] In order to facilitate understanding of the above implementation process, an example is now given to illustrate the implementation process.

[0097] The definition of valve closing and opening conditions in the train control logic involves two key parameters: time span combination and internal / external pressure differential. Mandatory conditions, on the other hand, simply define the extreme boundary states of the pressure protection valve's opening and closing actions. Therefore, the key parameters that can be optimized in the pressure surge protection valve control logic are: time span combination and internal / external pressure differential.

[0098] Considering the efficiency and complexity of parameter optimization, this study decoupled the two major parameters, time span combination and internal and external pressure difference index, during the parameter optimization of the pressure wave protection valve control logic. This formed two parameter optimization angles and optimized the control logic parameters separately, thus forming the following three control logic parameter optimization schemes:

[0099] The original basic design scheme for valve closing and opening conditions was retained, and only the internal and external pressure differential parameters involved in each operating condition were optimized to obtain the internal and external pressure differential index value combination for each operating condition that best protected the vehicle's internal pressure. The original basic design scheme for valve closing and opening conditions was retained, and only the time span parameters involved in each operating condition were optimized to obtain the time span index value combination for each operating condition that best protected the vehicle's internal pressure. These two optimization approaches were coupled to perform coupled optimization.

[0100] The optimization design of the control logic parameters for a train's pressure surge protection valve aims to determine the optimal combination of control parameters to achieve the optimal pressure variation within the carriage. This is essentially a multi-parameter optimization problem. Therefore, this problem can be solved using a typical optimization algorithm. Taking into account various optimization factors, including programming complexity, optimization accuracy, convergence performance, and optimization effectiveness, this study selected the particle swarm optimization algorithm.

[0101] The particle swarm optimization (PSO) algorithm is used to optimize the switch action limits of the pressure wave protection valve. The goal is to ensure that the CO2 concentration and pressure change rate in the train meet the requirements at the same time and obtain the optimal solution.

[0102] Set the limits for valve opening and closing as optimized parameters. The opening and closing of the pressure wave valve consists of six conditions, each with a corresponding pressure limit. These limits are set as optimized parameters. Assume the control pressure limits of the protection valve are [k1, k2, …, k6], where ki represents the i-th control parameter, representing the pressure limit under the valve closing or opening conditions.

[0103] Optimize the vehicle's airtightness index under different valve opening and closing conditions. Assume that the airtightness index under different states is [τ1, τ2, τ3, τ4, τ5, τ6], with different values ​​corresponding to different pressure surge protection valve states. τ1: indicates the pressure surge protection valve is fully open; τ2: indicates the pressure surge protection valve is fully closed; τ3: The pressure surge protection valve is only open at the two fresh air inlets; τ4: The pressure surge protection valve is only open at the two exhaust outlets; τ5: The pressure surge protection valve is only open at one fresh air inlet; τ6: The pressure surge protection valve is only open at one exhaust outlet.

[0104] The optimization goal is to optimize these parameters so that the protection valve has the fastest response speed and the highest stability when dealing with pressure fluctuations. The optimization objective function can be expressed as:

[0105] f(x) = w1*q1+w2*q2+w3*q3+w4*q4+w5*q5. q1: If the pressure change rate within the vehicle cabin over a period of 1 second meets the requirement, the value is 0; if it does not, the value is 1. q2: If the pressure change rate within the vehicle cabin over a period of 3 seconds meets the requirement, the value is 0; if it does not, the value is 1. q3: If the pressure change rate within the vehicle cabin over a period of 10 seconds meets the requirement, the value is 0; if it does not, the value is 1. q4: If the pressure change rate within the vehicle cabin over a period of 60 seconds meets the requirement, the value is 0; if it does not, the value is 1. q5: If the maximum CO2 concentration within the vehicle cabin is no more than 5000 ppm, the value is 0; if it is greater than 5000 ppm, the value is 1. w1-w5 represent the weight coefficients corresponding to the respective q values.

[0106] Through particle swarm optimization, the objective function value is minimized to obtain the optimal pressure wave control parameters.

[0107] The particle swarm optimization process is as follows: Step 1. Initialize the particle swarm: Randomly generate a group of particles. The position of each particle represents a set of control parameters, and the velocity is initialized to zero. Step 2. Calculate the fitness: Calculate the fitness value of each particle based on the objective function. Step 3. Update the individual optimal and global optimal: Record the historical optimal position of each particle and the global optimal position of the entire swarm. Step 4. Update the velocity and position: Update the velocity and position of each particle according to the PSO formula. Step 5. Iterate the optimization: Repeat steps 2-4 until the termination condition is met (such as reaching the maximum number of iterations or the fitness value converges).

[0108] Through the intelligent optimization algorithm of the particle swarm optimization (PSO) and machine learning, the objective function value was minimized, the control logic of the pressure surge protection valve was optimized, and the multi-parameter coordinated logic optimization of the pressure protection device was achieved. After the logic optimization, the CO2 clear line was lowered and the rate of change of the vehicle pressure met the requirements.

[0109] The following describes in detail one or more embodiments of the rail vehicle pressure wave control device of the present application. Those skilled in the art will appreciate that these devices can be configured using commercially available hardware components through the steps taught in this solution.

[0110] Figure 5 The present application provides a pressure wave control device for a rail vehicle, such as Figure 5 As shown, the device includes: a first determining module 11 , a second determining module 12 , a third determining module 13 , a fourth determining module 14 , and a control module 15 .

[0111] The first determining module 11 is configured to determine the external pressure value of the carriage of the rail vehicle on the target running route at a current moment by using a geometric model corresponding to the rail vehicle.

[0112] The second determining module 12 is configured to determine a first compartment internal pressure value of the rail vehicle at a current moment based on the compartment external pressure value and a compartment internal and external pressure transmission model corresponding to the rail vehicle at a current moment.

[0113] The third determining module 13 is configured to determine a corresponding carriage internal pressure change rate of the rail vehicle based on the first carriage internal pressure value and a second carriage internal pressure value of the rail vehicle at a previous moment.

[0114] The fourth determining module 14 is configured to determine the carbon dioxide concentration in the rail vehicle at the current moment based on the state information of the pressure wave protection valve at the current moment.

[0115] The control module 15 is used to determine whether the target valve opening condition of the pressure wave protection valve is met at the current moment based on the pressure change rate inside the carriage and the carbon dioxide concentration. If so, control the opening of the pressure wave protection valve corresponding to the rail vehicle.

[0116] Optionally, the device may further include a judgment module, which is specifically used to: judge whether the closing condition of the pressure wave protection valve is met at the current moment based on the pressure change rate inside the car and the carbon dioxide concentration; if met, control the closing of the pressure wave protection valve corresponding to the rail vehicle.

[0117] Optionally, the first determination module 11 is specifically used to: establish a geometric model corresponding to the rail vehicle; extract the frequency spectrum characteristics of the tunnel pressure exerted on the rail vehicle in the target operating route; use the geometric model corresponding to the rail vehicle, based on the frequency spectrum characteristics and the one-dimensional flow control equation group, to determine the external pressure value of the rail vehicle at the current moment.

[0118] Optionally, before determining the first compartment internal pressure value of the rail vehicle at the current moment based on the compartment external pressure value and the compartment internal and external pressure transmission model corresponding to the rail vehicle at the current moment, the device also includes a model determination module, and the model determination module is specifically used to: obtain the status information corresponding to the pressure wave protection valve at the current moment; determine the dynamic air tightness index corresponding to the rail vehicle at the current moment based on the status information; determine the compartment internal and external pressure transmission model corresponding to the rail vehicle at the current moment based on the dynamic air tightness index corresponding to the rail vehicle at the current moment.

[0119] Optionally, the model determination module is specifically used to: obtain a target interval in which the dynamic airtightness index is located; determine a first search point and a second search point in the current search interval based on the target interval; determine a first internal pressure curve corresponding to the first search point and a second internal pressure curve corresponding to the second search point; determine a first similarity measurement index corresponding to the first search point based on the first internal pressure curve corresponding to the first search point and a measured internal pressure curve, wherein the measured internal pressure curve is an internal pressure curve obtained by testing the rail vehicle; determine a second similarity measurement index corresponding to the second search point based on the second internal pressure curve corresponding to the second search point and the measured internal pressure curve; update the search interval according to the magnitude relationship between the first similarity measurement index and the second similarity measurement index; if the current calculation accuracy does not reach the set calculation accuracy, re-determine the first search point and the second search point with the updated search interval, and perform another search, wherein the current calculation accuracy is determined according to the length of the current search interval; when the current calculation accuracy reaches the required dynamic sealing index calculation accuracy, output the optimal calculation result of the current dynamic airtightness index; and determine the optimal calculation result as the dynamic airtightness index corresponding to the rail vehicle at the current moment.

[0120] Optionally, the model determination module is specifically used to: obtain a preset pressure transmission model inside and outside the vehicle compartment; numerically solve the preset pressure transmission model inside and outside the vehicle compartment to obtain the preset internal pressure function; and determine the first internal pressure curve corresponding to the first search point based on the dynamic airtightness index corresponding to the first search point and the preset internal pressure function.

[0121] Optionally, the fourth determination module 14 is specifically used to: obtain the number of passengers in the rail vehicle at the current moment and the air flow corresponding to the rail vehicle at the current moment; construct a carbon dioxide concentration prediction model; and determine the carbon dioxide concentration in the rail vehicle at the current moment based on the pressure wave protection valve status information at the current moment, the number of passengers, the air flow and the carbon dioxide concentration prediction model.

[0122] Optionally, the device also includes an optimization module, which is specifically used to: determine the preset valve opening conditions corresponding to the pressure wave protection valve in the rail vehicle; optimize the pressure wave control parameters in the preset valve opening conditions to obtain optimized pressure wave control parameters; based on the optimized pressure wave control parameters and the preset valve opening conditions, determine the target valve opening conditions of the pressure wave protection valve in the rail vehicle.

[0123] Optionally, the optimization module is specifically used to: randomly generate a group of particles, where the position of each particle represents a set of pressure wave control parameters; calculate the fitness value of each particle according to the objective function; update the individual optimum and the global optimum, and record the historical optimal position of each particle and the global optimal position of the entire group; update the speed and position of each particle according to the particle swarm optimization formula; when the termination condition is met, output the optimal calculation result of the pressure wave control parameter in the current preset valve opening condition; and determine the optimal calculation result of the pressure wave control parameter as the optimized pressure wave control parameter.

[0124] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 6 As shown, in practice, the electronic device includes: a memory 21 and a processor 22.

[0125] The memory 21 is used to store computer programs and can be configured to store various other data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on the electronic device, data structures, contact data, phone book data, messages, images, videos, etc.

[0126] The processor 22 is coupled to the memory 21 and is used to execute the computer program in the memory 21 to implement the pressure wave control method for the rail vehicle provided in the above embodiment.

[0127] Further, if Figure 6 As shown, the electronic device also includes: a communication component 23, a display 24, a power component 25, an audio component 26 and other components. Figure 6 Only some components are shown schematically, which does not mean that the electronic device only includes Figure 6 The electronic device of this embodiment can be implemented as a terminal device such as a desktop computer, a laptop computer, a smart phone or an IOT device, or a server device such as a conventional server, a cloud server or a server array.

[0128] The above-mentioned memory can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random-access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0129] The communication component is configured to facilitate wired or wireless communication between the device in which the communication component resides and other devices. The device in which the communication component resides can access a wireless network based on a communication standard, such as a 2G, 3G, 4G / LTE, 5G, or other mobile communication network, or a combination thereof. In an exemplary embodiment, the communication component receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel.

[0130] The above-mentioned display includes a screen, which may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor can not only sense the boundary of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

[0131] The power supply assembly provides power to various components of the device in which the power supply assembly is located. The power supply assembly may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device in which the power supply assembly is located.

[0132] The above-mentioned audio component can be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC), and when the device where the audio component is located is in an operating mode, such as call mode, recording mode, and voice recognition mode, the microphone is configured to receive external audio signals. The received audio signal can be further stored in a memory or sent via a communication component. In some embodiments, the audio component also includes a speaker for outputting audio signals.

[0133] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor is enabled to implement each step in the above method embodiment.

[0134] The computer-readable storage medium may be volatile or non-volatile, or a combination thereof, and may be removable or non-removable. Examples of computer-readable storage media include, but are not limited to, phase-change random access 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), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, disk storage or other magnetic storage devices, or any other non-transmission medium.

[0135] Accordingly, an embodiment of the present application further provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by a processor, the processor is enabled to implement the steps in the above method embodiment.

[0136] Those skilled in the art will appreciate that the embodiments of the present application may be provided as a pressure wave control method, system, or computer program product for a rail vehicle. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented 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. The solutions in the embodiments of the present application may be implemented in various computer languages, such as C language, VHDL language, Verilog language, object-oriented programming language Java, and interpreted scripting language JavaScript.

[0137] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0138] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0139] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0140] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0141] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the features. Throughout the description of this application, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0142] In this application, unless otherwise expressly specified or limited, terms such as "mounted," "connected," "connect," and "fixed" should be understood broadly. For example, they may refer to fixed connections, detachable connections, or integration; mechanical connections, electrical connections, or communication; direct connections or indirect connections through an intermediate medium; and internal communication between two components or interaction between two components. Those skilled in the art will understand the specific meanings of these terms in this application based on specific circumstances.

[0143] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0144] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A pressure wave control method for a rail vehicle, characterized in that: include: Determine, using a geometric model corresponding to the rail vehicle, a current external pressure value of the rail vehicle on the target operating route; Determining a first compartment internal pressure value of the rail vehicle at a current moment based on the compartment external pressure value and a compartment internal and external pressure transmission model corresponding to the rail vehicle at a current moment; Determining a pressure change rate of the compartment corresponding to the rail vehicle based on the first compartment internal pressure value and a second compartment internal pressure value of the rail vehicle at a previous moment; determining a carbon dioxide concentration in the rail vehicle at a current moment based on the pressure wave protection valve state information at a current moment; Based on the pressure change rate inside the carriage and the carbon dioxide concentration, it is determined whether the target valve opening condition of the pressure wave protection valve is met at the current moment. If so, the pressure wave protection valve corresponding to the rail vehicle is controlled to open.

2. The method according to claim 1, characterized in that The method further comprises: determining whether a closing condition of a pressure wave protection valve is satisfied at a current moment based on the cabin internal pressure change rate and the carbon dioxide concentration; If the conditions are met, the pressure wave protection valve corresponding to the rail vehicle is controlled to close.

3. The method according to claim 1, characterized in that The method of using a geometric model corresponding to the rail vehicle to determine a current external pressure value of the rail vehicle on the target running route includes: Establish the geometric model corresponding to the rail vehicle; extracting frequency spectrum characteristics of tunnel pressure experienced by the rail vehicle in a target operating route; The geometric model corresponding to the rail vehicle is used to determine the external pressure value of the rail vehicle at a current moment based on the frequency spectrum characteristics and the one-dimensional flow control equations.

4. The method according to claim 1, wherein Before determining the first compartment internal pressure value of the rail vehicle at the current moment based on the compartment external pressure value and the compartment internal and external pressure transmission model corresponding to the rail vehicle at the current moment, the method further includes: Obtaining status information corresponding to the pressure wave protection valve at the current moment; Determining a dynamic airtightness index corresponding to the rail vehicle at a current moment based on the state information; Based on the dynamic air tightness index corresponding to the rail vehicle at the current moment, a pressure transmission model inside and outside the compartment corresponding to the rail vehicle at the current moment is determined.

5. The method according to claim 4, characterized in that The determining, based on the state information, a dynamic airtightness index corresponding to the rail vehicle at a current moment includes: Obtaining a target range in which the dynamic airtightness index is located; Determining a first search point and a second search point in a current search interval based on the target interval; determining a first internal pressure curve corresponding to the first search point and a second internal pressure curve corresponding to the second search point; determining a first similarity metric corresponding to the first search point based on a first internal pressure curve corresponding to the first search point and a measured internal pressure curve, wherein the measured internal pressure curve is an internal pressure curve obtained by performing an experimental test on the rail vehicle; determining a second similarity measurement index corresponding to the second search point based on a second internal pressure curve corresponding to the second search point and a measured internal pressure curve; Updating the search interval according to the magnitude relationship between the first similarity measurement index and the second similarity measurement index; If the current calculation accuracy does not reach the set calculation accuracy, re-determine the first search point and the second search point using the updated search interval and perform another search, wherein the current calculation accuracy is determined according to the length of the current search interval; When the current calculation accuracy reaches the required dynamic sealing index calculation accuracy, the optimal calculation result of the current dynamic airtight index is output; The optimal calculation result is determined as the dynamic air tightness index corresponding to the rail vehicle at the current moment.

6. The method according to claim 5, characterized in that The determining a first internal pressure curve corresponding to the first search point includes: Obtaining a preset pressure transmission model inside and outside the vehicle compartment; Numerically solving the preset pressure transmission model inside and outside the vehicle compartment to obtain the preset internal pressure function; A first internal pressure curve corresponding to the first search point is determined based on the dynamic airtightness index corresponding to the first search point and the preset internal pressure function.

7. The method according to claim 1, characterized in that The determining of the carbon dioxide concentration in the rail vehicle at a current moment based on the pressure wave protection valve state information includes: Obtaining the number of passengers in the rail vehicle at a current moment and the air flow rate corresponding to the rail vehicle at a current moment; Build a carbon dioxide concentration prediction model; The carbon dioxide concentration in the rail vehicle at the current moment is determined based on the current state information of the pressure wave protection valve, the number of passengers, the air flow, and the carbon dioxide concentration prediction model.

8. The method according to claim 1, characterized in that The method further comprises: determining a preset valve opening condition corresponding to a pressure wave protection valve in the rail vehicle; Optimizing the pressure wave control parameters in the preset valve opening conditions to obtain optimized pressure wave control parameters; Based on the optimized pressure wave control parameters and the preset valve opening conditions, a target valve opening condition of the pressure wave protection valve in the rail vehicle is determined.

9. The method according to claim 8, characterized in that The optimizing the pressure wave control parameters in the preset valve opening conditions to obtain optimized pressure wave control parameters includes: randomly generating a set of particles, wherein the position of each particle represents a set of pressure wave control parameters; Calculate the fitness value of each particle according to the objective function; Update individual optimal and global optimal positions, record the historical optimal position of each particle and the global optimal position of the entire group; Update the speed and position of each particle according to the particle swarm optimization formula; When the termination condition is met, the optimal calculation result of the pressure wave control parameter in the current preset valve opening condition is output; The optimal calculation result of the pressure wave control parameter is determined as the optimized pressure wave control parameter.

10. A pressure wave control device, characterized in that: include: Memory; processor; as well as computer programs; The computer program is stored in the memory and configured to be executed by the processor to implement the method according to any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that A computer program is stored thereon; the computer program is executed by a processor to implement the method according to any one of claims 1 to 9.

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