A solenoid valve performance prediction system and method

Abstract

This application relates to the field of automotive electronics technology, and particularly to a solenoid valve performance prediction system and method. The system includes a data processing system, a digital twin intelligent computing system, and a digital twin virtual reality system. The data processing system is used to preprocess the sensing data and control data of the target vehicle respectively to obtain the target environmental data and target control data of the target vehicle. The digital twin intelligent computing system is used to convert the target control data into virtual control data recognizable by the digital twin virtual reality system; the digital twin virtual reality system performs relevant environment simulations of the solenoid valve based on the target environmental data and virtual control data to obtain virtual environmental data; the digital twin intelligent computing system predicts the relevant performance of the solenoid valve based on the virtual environmental data and / or target control data. It is possible to actively predict the relevant performance of the solenoid valve during vehicle driving, realize the prediction of solenoid valve failures, and ensure the driving safety of the vehicle.

Description

Technical Field

[0001] This application relates to the field of automotive electronics technology, and particularly to a solenoid valve performance prediction system and method. Background Art

[0002] The solenoid valve is a core technology product integrating precision machinery, materials, electromagnetism, fluid, and control technologies. The main types of solenoid valves include normally closed switch valves, normally open switch valves, normally closed linear pressure regulating valves, normally open linear pressure regulating valves, multi-stage valves, and other types of solenoid valves.

[0003] The solenoid valve is one of the core components of a vehicle. Especially in the vehicle's electronic brake system, the number and types of solenoid valves are numerous, and they undertake main core functions such as circuit opening and closing, independent pressurization, and decompression. Therefore, the reliability and performance of the solenoid valve greatly affect the operation of the vehicle system (especially the vehicle's electronic brake system).

[0004] The development of existing solenoid valves mainly exists in the research and development stage before the vehicle is launched. Specifically, first, development is carried out in stages such as simulation, bench testing, and prototype vehicles according to the vehicle development goals; then, the relevant control logic and control parameters of the solenoid valve are designed based on the vehicle development conclusions, and the relevant control logic and control parameters of the solenoid valve are solidified into the solenoid valve control system; finally, the vehicle equipped with the solenoid valve control system and the solenoid valve is launched on the market for sales and use.

[0005] In the design stage of the solenoid valve, relevant function degradation and fault diagnosis strategies of the solenoid valve are designed to prevent the functions of devices related to the solenoid valve from being affected when the solenoid valve fails. However, only when the solenoid valve has corresponding failures, the vehicle will execute the relevant function degradation and fault diagnosis strategies of the solenoid valve, that is, the vehicle does not have the ability to actively predict solenoid valve failures. During driving, it cannot timely respond to solenoid valve failures to adjust driving data, thereby affecting the driving safety of the target vehicle.

[0006] Therefore, it is necessary to provide a solenoid valve performance prediction system and method that can actively predict the performance of the solenoid valve during vehicle driving, realize the prediction of solenoid valve failures, and ensure the driving safety of the vehicle. Summary of the Invention

[0007] The embodiments of this application provide a solenoid valve performance prediction system and method, which can actively predict the performance of the solenoid valve during vehicle driving, timely respond to performance problems related to the solenoid valve, and ensure the driving safety of the vehicle.

[0008] On the one hand, the embodiments of this application provide a solenoid valve performance prediction system, and the system includes:

[0009] A data processing system, a digital twin intelligent computing system, and a digital twin virtual reality system;

[0010] The data processing system is used to obtain the sensing data and control data of the target vehicle, and preprocess the sensing data and the control data respectively to obtain the target environmental data and target control data of the target vehicle;

[0011] The digital twin intelligent computing system is used to obtain the target control data and convert the target control data into virtual control data recognizable by the digital twin virtual reality system;

[0012] The digital twin virtual reality system is used to obtain the target environmental data and the virtual control data, and perform relevant environmental simulation of the solenoid valve based on the target environmental data and the virtual control data to obtain virtual environmental data;

[0013] The digital twin intelligent computing system predicts the relevant performance of the solenoid valve based on the virtual environmental data and / or the target control data.

[0014] In some optional embodiments, the digital twin virtual reality system includes a digital twin virtual environment system and a digital twin solenoid valve simulation system; the virtual environmental data includes the external environmental data of the solenoid valve and the body environmental data of the solenoid valve;

[0015] Performing relevant environmental simulation of the solenoid valve based on the target environmental data and the virtual control data to obtain virtual environmental data includes:

[0016] The digital twin virtual environment system performs external environmental simulation of the solenoid valve based on the target environmental data to obtain the external environmental data of the solenoid valve;

[0017] The digital twin solenoid valve simulation system performs body environmental simulation of the solenoid valve based on the virtual control data to obtain the body environmental data of the solenoid valve.

[0018] In some optional embodiments, the digital twin virtual environment system includes at least one of a motion and dynamics module, an environmental vibration module, an environmental heat conduction and radiation module, and an environmental electromagnetic radiation module:

[0019] The environmental vibration module is used to simulate the installation boundary of the solenoid valve and the high and low frequency vibrations of the environment;

[0020] The environmental heat conduction and radiation module is used to simulate the heat conduction characteristics of the surrounding environment of the solenoid valve;

[0021] The environmental electromagnetic radiation module is used to simulate the electromagnetic characteristics of the vehicle environment;

[0022] The motion and dynamics module is used to simulate the motion and dynamics characteristics of the installation boundary and environment of the solenoid valve.

[0023] In some alternative embodiments, the digital twin solenoid valve simulation system includes at least one of an electromagnetic mechanics module, a material and elasticity mechanics module, a fluid and multiphase flow module, and a multibody dynamics module;

[0024] The electromagnetic mechanics module is used to simulate the electromagnetic part of the solenoid valve;

[0025] The material and elasticity mechanics module is used to simulate the mechanical structure of the solenoid valve;

[0026] The fluid and multiphase flow module is used to simulate the internal flow field dynamics and multiphase flow characteristics of the solenoid valve;

[0027] The multibody dynamics module is used to simulate the multi-degree-of-freedom moving parts and system motion characteristics of the solenoid valve.

[0028] In some alternative embodiments, the related performance of the solenoid valve includes at least one of the life, failure, reliability, and optimization control data of the solenoid valve; the optimization control data is used for the target vehicle to control the solenoid valve.

[0029] In some alternative embodiments, the preprocessing includes at least one of parsing, format conversion, precision conversion, screening, interpolation optimization, classification, and identification assignment.

[0030] In some alternative embodiments, the solenoid valve is disposed in the electronic brake system of the target vehicle; the system further includes a solenoid valve bench test system;

[0031] The solenoid valve bench test system is used to obtain the sensing data and control data of multiple target vehicles, generate multiple test cases with diverse braking behaviors based on the sensing data and control data of multiple target vehicles, and perform a solenoid valve bench test based on the multiple test cases to obtain bench reference data;

[0032] The digital twin intelligent computing system is further used to obtain the multiple test cases and the bench reference data, input the multiple test cases into the digital twin virtual reality system to generate test environment data, and predict the related performance of the solenoid valve based on the test environment data to obtain related performance test data; wherein, the bench reference data is used to optimize the related performance test data and / or the virtual environment data.

[0033] On the other hand, an embodiment of the present application provides a method for predicting the performance of a solenoid valve, the method including:

[0034] Obtain the sensing data and control data of the target vehicle, and preprocess the sensing data and the control data respectively to obtain the target environment data and target control data of the target vehicle;

[0035] Perform relevant environment simulation of the solenoid valve of the target vehicle based on the target control data and the target environment data to obtain virtual environment data;

[0036] Predict the relevant performance of the solenoid valve based on the virtual environment data and / or the target control data.

[0037] In some optional embodiments, the virtual environment data includes the external environment data of the solenoid valve and the body environment data of the solenoid valve;

[0038] The performing relevant environment simulation of the solenoid valve of the target vehicle based on the target control data and the target environment data to obtain virtual environment data includes:

[0039] Perform external environment simulation of the solenoid valve based on the target environment data to obtain the external environment data of the solenoid valve;

[0040] Perform body environment simulation of the solenoid valve based on the target control data to obtain the body environment data of the solenoid valve.

[0041] In some optional embodiments, the above method further includes:

[0042] Construct multiple test cases with diverse braking behaviors based on the sensing data and the control data of multiple target vehicles;

[0043] Perform solenoid valve bench test based on the multiple test cases to obtain bench reference data;

[0044] Perform relevant environment simulation of the solenoid valve based on the multiple test cases to obtain test environment data;

[0045] Predict the relevant performance of the solenoid valve based on the test environment data to obtain relevant performance test data;

[0046] Optimize the relevant performance test data and / or virtual environment data based on the bench reference data.

[0047] This application obtains the sensing data and control data of the target vehicle through the data processing system, and preprocesses the sensing data and the control data respectively to obtain the target environmental data and target control data of the target vehicle; obtains the target control data through the digital twin intelligent computing system, and converts the target control data into virtual control data recognizable by the digital twin virtual reality system; obtains the target environmental data and the virtual control data through the digital twin virtual reality system, and performs relevant environmental simulation of the solenoid valve based on the target environmental data and the virtual control data to obtain virtual environmental data; predicts the relevant performance of the solenoid valve through the digital twin intelligent computing system based on the virtual environmental data and / or the target control data. In this way, the relevant performance of the solenoid valve can be actively predicted during vehicle driving, the prediction of solenoid valve failures can be achieved, and the driving safety of the vehicle can be ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0049] Figure 1 FIG. is an application scenario diagram of a solenoid valve performance prediction system provided by an embodiment of the present application;

[0050] Figure 2 FIG. is a schematic principle diagram of a solenoid valve performance prediction system provided by an embodiment of the present application;

[0051] Figure 3 FIG. is a schematic structural diagram of a solenoid valve performance prediction system provided by an embodiment of the present application;

[0052] Figure 4 FIG. is a schematic structural diagram of a digital twin virtual reality system provided by an embodiment of the present application;

[0053] Figure 5 FIG. is a schematic structural diagram of a digital twin intelligent computing system provided by an embodiment of the present application;

[0054] Figure 6 FIG. is a schematic structural diagram of a solenoid valve bench test system provided by an embodiment of the present application;

[0055] Figure 7 FIG. is a schematic flowchart of a solenoid valve performance prediction method provided by an embodiment of the present application;

[0056] Figure 8It is a schematic flowchart of another solenoid valve performance prediction method provided by an embodiment of the present application;

[0057] Figure 9 It is a hardware structure block diagram of an electronic device for implementing the solenoid valve performance prediction method provided by an embodiment of the present application. Specific embodiments

[0058] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0059] As used herein, "one embodiment" or "embodiment" refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. In the description of the present invention, it should be understood that the terms "first", "second", "third", and "fourth" in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products, or devices.

[0060] Steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products, or devices.

[0061] First, an example introduction is given to the application scenarios of the solenoid valve performance prediction system and the solenoid valve performance prediction method.

[0062] Please refer to Figure 1 , Figure 1 It is an application scenario diagram of a solenoid valve performance prediction system provided by an embodiment of the present application. Figure 1 During the driving process of the target vehicle 10 shown, if a solenoid valve of the target vehicle 10 fails, the target vehicle 10 will execute a preset function degradation and fault diagnosis strategy related to the solenoid valve to avoid affecting the functions of the solenoid valve-related devices and causing driving safety problems of the target vehicle 10.

[0063] As mentioned above, since the target vehicle 10 does not have the ability to actively predict solenoid valve failures, during the driving process, it cannot timely respond to solenoid valve failures to adjust driving data, thereby affecting the driving safety of the target vehicle 10.

[0064] To solve the above problems, the present application provides a solenoid valve performance prediction system. Specifically, it includes: a data processing system, a digital twin intelligent computing system, and a digital twin virtual reality system. The data processing system is used to obtain the sensing data and control data of the target vehicle, and preprocess the sensing data and the control data respectively to obtain the target environmental data and target control data of the target vehicle. The digital twin intelligent computing system is used to obtain the target control data and convert the target control data into virtual control data recognizable by the digital twin virtual reality system. The digital twin virtual reality system is used to obtain the target environmental data and the virtual control data, and perform relevant environmental simulations of the solenoid valve based on the target environmental data and the virtual control data to obtain virtual environmental data. The digital twin intelligent computing system predicts the relevant performance of the solenoid valve based on the virtual environmental data and / or the target control data. In this way, the relevant performance of the solenoid valve can be actively predicted during vehicle driving, the prediction of solenoid valve failures can be realized, and the driving safety of the vehicle can be ensured.

[0065] The following introduces a specific embodiment of a solenoid valve performance prediction system of the present application. Figures 2 to 6 It is a schematic structural diagram of the solenoid valve performance prediction system provided by the embodiment of the present application. As Figure 2 and Figure 3 shown, the solenoid valve performance prediction system includes:

[0066] A data processing system, a digital twin intelligent computing system, and a digital twin virtual reality system.

[0067] Among them, the data processing system is used to obtain the sensing data and control data of the target vehicle, and preprocess the sensing data and the control data respectively to obtain the target environmental data and target control data of the target vehicle. The data processing system obtains the sensing data and control data of the target vehicle in real time.

[0068] The external environment of the solenoid valve in a vehicle (such as ambient temperature) and the control data of external devices (such as lane change data) usually affect the performance of the solenoid valve. To accurately predict the performance of the solenoid valve, by obtaining sensing data and / or control data outside the electronic brake system in the vehicle, the relevant environment of the solenoid valve can be more accurately simulated. In some alternative embodiments, the sensing data includes, but is not limited to, the data collected by the sensors of the electronic brake system itself, and also includes the data collected by other available sensors in the vehicle; the sensing data can optionally be data such as vehicle acceleration, vehicle speed, braking distance, ambient temperature, ambient humidity, electronic pedal displacement, etc. The control data includes, but is not limited to, the data of the controller of the electronic brake system. For example, the ambient temperature and humidity outside the electronic brake system affect the data of the internal temperature sensor and humidity sensor of the electronic brake system. Therefore, the data of the internal temperature sensor and humidity sensor of the electronic brake system can be corrected by the ambient temperature and humidity outside the electronic brake system. Another example is that the data of the controller outside the electronic brake system includes lane change controller data. In the case of a lane change, the speed usually needs to be controlled. Therefore, the lane change controller data affects the data of the internal controller of the electronic brake system, and the data of the internal controller of the electronic brake system can be corrected by the lane change controller data.

[0069] In some alternative embodiments, the preprocessing includes at least one of parsing, format conversion, precision conversion, screening, interpolation optimization, classification, and identification assignment. In this way, the readability, density, precision, etc. of the sensing data and control data are improved. For example, after classifying the sensing data of the vehicle according to the data unit, the target environment data is obtained, so that the corresponding target environment data (i.e., sensing data) can be called when the subsequent system performs simulation calculations related to the solenoid valve.

[0070] As shown, the data processing system is connected to the digital twin intelligent computing system and transmits the target control data obtained after preprocessing to the digital twin intelligent computing system.

[0071] As Figure 2 shown, the data processing system is connected to the digital twin intelligent computing system and transmits the target control data obtained after preprocessing to the digital twin intelligent computing system.

[0072] The digital twin virtual reality system usually used for simulation cannot recognize the real target control data of the target vehicle. In some alternative embodiments, the digital twin intelligent computing system is used to obtain the target control data and convert the target control data into virtual control data recognizable by the digital twin virtual reality system.

[0073] For example, if the target control data is the input current of the solenoid valve, the digital twin intelligent computing system obtains the virtual magnetic control data (i.e., recognizable virtual control data) required for magnetic simulation by the digital twin virtual reality system based on this current, as well as the virtual mechanical control data required for mechanical simulation, etc.

[0074] In some alternative embodiments, the virtual control data refers to virtual magnetic control data and virtual mechanical control data.

[0075] The digital twin intelligent computing system is connected to the digital twin virtual reality system and transmits the obtained virtual control data after conversion to the digital twin virtual reality system.

[0076] Among them, the digital twin virtual reality system is used to obtain the target environment data and the virtual control data, and perform relevant environment simulations of the solenoid valve based on the target environment data and the virtual control data to obtain virtual environment data. The relevant environment simulation of the solenoid valve includes the external environment of the solenoid valve (such as the vibration condition of the external connection components of the solenoid valve) and the internal environment of the solenoid valve, that is, the simulation of the mutual influence between the solenoid valve body structure and performance (such as the electromechanical situation of the solenoid valve). Considering the mutual influence between the external environment of the solenoid valve and the solenoid valve body structure and performance makes the simulation result of the solenoid valve closer to the solenoid valve situation of the real vehicle.

[0077] In order to accurately predict the performance of the solenoid valve, it is necessary to accurately obtain the solenoid valve body structure and performance and the external environment data. In some alternative embodiments, the virtual environment data includes the external environment data of the solenoid valve and the body environment data of the solenoid valve. For example, the external environment data includes the simulation based on the external environment of the solenoid valve (such as the temperature data of the external connection components of the solenoid valve); the body environment data includes the simulation data based on the solenoid valve body structure and performance (such as the fluid and multiphase flow inside the solenoid valve, the electromechanical situation of the solenoid valve).

[0078] Such as Figure 2 and Figure 4 As shown, the digital twin virtual reality system includes a digital twin virtual environment system and a digital twin solenoid valve simulation system; data interaction can be carried out between the two systems to realize the mutual influence between the external environment of the solenoid valve and the solenoid valve body structure and performance. For example, the digital twin virtual environment system sends the temperature data of the external connection components of the solenoid valve to the digital twin solenoid valve simulation system to optimize the simulation situation of the fluid and multiphase flow inside the solenoid valve.

[0079] The digital twin virtual environment system performs the external environment simulation of the solenoid valve based on the target environment data to obtain the external environment data of the solenoid valve; for example, based on the temperature sensing data in the target environment data, through Figure 4 The environmental heat conduction module shown simulates the temperature distribution of the external connection components of the solenoid valve. In this way, the external environment simulation of the solenoid valve is beneficial to comprehensively evaluate the performance of the solenoid valve, making the subsequent solenoid valve performance prediction (such as determining the possible circuit faults of the solenoid valve) more accurate.

[0080] The digital twin solenoid valve simulation system performs simulation of the solenoid valve's body environment based on the virtual control data to obtain the body environment data of the solenoid valve. The body environment simulation includes simulation of the structure and performance of the solenoid valve body, such as simulation of the electromagnetic and mechanical performance of the solenoid valve body. Among them, as Figure 2 shown, the digital twin solenoid valve simulation system obtains virtual control data from the digital twin intelligent computing system.

[0081] In some alternative embodiments, the correct operation of the digital twin virtual environment system also depends on the target environment data from the data processing system and the data from the digital twin solenoid valve simulation system. The correct operation of the digital twin solenoid valve simulation system also depends on the data from the digital twin intelligent computing system and the virtual control data of the digital twin intelligent computing system. In this way, the simulation data between the digital twin virtual environment system and the digital twin solenoid valve simulation system are interacted, thereby optimizing the simulation data of the two systems and making the simulation data of the two systems more accurate.

[0082] In some alternative embodiments, the digital twin virtual environment system includes Figure 4 shown, including at least one of an environmental vibration module, an environmental heat conduction and radiation module, an environmental electromagnetic radiation module, and a motion and dynamics module;

[0083] The environmental vibration module is used to simulate the high and low frequency vibrations of the installation boundary of the solenoid valve and the environment;

[0084] The environmental heat conduction and radiation module is used to simulate the heat conduction characteristics of the surrounding environment of the solenoid valve;

[0085] The environmental electromagnetic radiation module is used to simulate the electromagnetic characteristics of the vehicle environment;

[0086] The motion and dynamics module is used to simulate the motion and dynamics characteristics of the installation boundary of the solenoid valve and the environment.

[0087] For example, the environmental vibration module performs environmental vibration simulation based on the installation boundaries of the solenoid valves and the high- and low-frequency vibration data of the environment in the sensing data, and obtains the vibration conditions of each solenoid valve device. The environmental heat conduction and radiation module determines the heat conduction and heat distribution conditions between the solenoid valve devices based on the temperature data of each solenoid valve device in the sensing data. The environmental electromagnetic radiation module performs simulation based on the electromagnetic data of the vehicle environment in the sensing data, and obtains the electromagnetic characteristic distribution of the vehicle environment. The motion and dynamics module simulates the installation boundaries of the solenoid valves and the motion and dynamics of the environment based on the installation boundaries of the solenoid valves and the motion and dynamics data of the environment in the sensing data, and the motion and dynamics conditions of the installation boundaries of the solenoid valves and the environment.

[0088] The digital twin virtual environment system obtains the external environment data of the solenoid valve based on the vibration conditions, heat conduction and heat distribution conditions, electromagnetic characteristic distribution conditions of the external structure of each solenoid valve, and the motion and dynamics conditions of the installation boundaries of the solenoid valves and the environment (such as analyzing and fusing the data obtained from the simulation of each module).

[0089] In some alternative embodiments, the digital twin solenoid valve simulation system Figure 4 as shown, includes at least one of an electromagnetic mechanics module, a materials and elasticity mechanics module, a fluid and multiphase flow module, and a multibody dynamics module;

[0090] The electromagnetic mechanics module is used to simulate the electromagnetic part of the solenoid valve;

[0091] The materials and elasticity mechanics module is used to simulate the mechanical structure of the solenoid valve;

[0092] The fluid and multiphase flow module is used to simulate the internal flow field dynamics and multiphase flow characteristics of the solenoid valve;

[0093] The multibody dynamics module is used to simulate the multi-degree-of-freedom moving parts and system motion characteristics of the solenoid valve.

[0094] For example, the electromagnetic mechanics module simulates the electromagnetic part of the solenoid valve based on the relevant current data inside the solenoid valve in the sensing data, and obtains the electromagnetic state of the solenoid valve. The materials and elasticity mechanics module simulates the mechanical structure of the solenoid valve based on the relevant mechanics data inside the solenoid valve in the sensing data, and obtains the internal spring state of the solenoid valve. The fluid and multiphase flow module obtains the internal flow field dynamics and multiphase flow characteristics of the solenoid valve based on the relevant pressure and flow rate inside the solenoid valve.

[0095] The multi-body dynamics module simulates the motion characteristics of the multi-degree-of-freedom moving components and systems inside the solenoid valve based on the relevant mechanical data of the multi-degree-of-freedom moving components and systems inside the solenoid valve in the sensing data. The digital twin solenoid valve simulation system realizes the simulation of various performances of the solenoid valve through the above-mentioned modules, and obtains the body environment data of the solenoid valve.

[0096] The digital twin virtual reality system is connected to the digital twin intelligent computing system, and transmits the simulated virtual environment data to the digital twin intelligent computing system.

[0097] Among them, the digital twin intelligent computing system predicts the relevant performances of the solenoid valve based on the virtual environment data and / or the target control data. The digital twin intelligent computing system predicts the relevant performances of the solenoid valve in real time based on the sensing data and control data of the target vehicle obtained by the data processing system in real time.

[0098] In some optional embodiments, the relevant performances of the solenoid valve include at least one of the life, failure, reliability, and optimized control data of the solenoid valve; the optimized control data is used for the target vehicle to control the solenoid valve. In this way, a comprehensive prediction of the relevant performances of the solenoid valve can be realized, so as to timely discover the performance problems related to the solenoid valve, and timely adjust the control data to improve the safety of vehicle driving.

[0099] Through this embodiment, during the driving process of the vehicle, the sensing data and control data of the vehicle are obtained in real time, and the performance of the solenoid valve of the vehicle is predicted in real time, so as to predict the performance of the solenoid valve in time, cope with the solenoid valve failure, and realize the safe driving of the vehicle. Among them, the target vehicle transmits the sensing data and control data to the data processing system through the in-vehicle communication terminal and by means of 4G / 5G / other wireless communication technologies. The data processing system preprocesses the sensing data and control data uploaded by the in-vehicle communication terminal to meet the requirements of the digital twin virtual reality system, the digital twin intelligent computing system, and the solenoid valve bench test system for the data interaction format. The digital twin intelligent computing system converts the preprocessed target control data into virtual control data acceptable to the digital twin virtual reality system, and realizes the real-time matching and correspondence of the virtual control data and the target environment data input into the digital twin virtual reality system (for example, the digital twin virtual reality system matches and marks the target environment data and the virtual control data with the same matching identifier in real time, and this matching identifier can be obtained through the data processing system, where the matching identifier can be used to represent the data obtained by the data processing system from the target vehicle at the same moment), completing the synchronous data input of the digital twin virtual reality system, the digital twin intelligent computing system and the target vehicle, and ensuring the consistency of the digital twin virtual reality system, the digital twin intelligent computing system and the target vehicle.

[0100] In some alternative embodiments, such as Figure 5 shown, the digital twin intelligent computing system includes a data processing module, a reliability calculation module, a performance optimization module, a life prediction module, and an intelligent optimization module.

[0101] Among them, the data processing module is used to convert the target control data into virtual control data acceptable to the digital twin virtual reality system. The reliability calculation module is used to perform solenoid valve reliability deduction calculation according to the virtual environment data from the digital twin virtual reality system. The performance optimization module is used to perform performance optimization calculation based on the current and historical driving behavior data of the single vehicle driver (i.e., the target control data) to obtain optimized control data. The digital twin intelligent computing system transmits the optimized control data to the controller of the electronic brake system of the target vehicle through the on-vehicle communication terminal of the target vehicle for algorithm update, so as to complete the real-time optimization of the solenoid valve control performance; at the same time, important information such as the reliability deduction calculation result and the life expectancy result is distributed to the driver interaction interface of the target vehicle and the background database of the target vehicle, so as to complete the predictive monitoring and intervention of the electronic brake solenoid valve of the vehicle.

[0102] In some alternative embodiments, the solenoid valve is arranged in the electronic brake system of the target vehicle; as Figure 6 shown, the system further includes a solenoid valve bench test system;

[0103] The solenoid valve bench test system is used to obtain the sensing data and the control data of multiple target vehicles, generate multiple test cases of diverse braking behaviors based on the sensing data and the control data of multiple target vehicles, and perform solenoid valve bench tests based on the multiple test cases to obtain bench reference data; wherein the bench reference data is used to represent the solenoid valve bench test results of multiple test cases based on a large amount of real vehicle data, and its test results are more accurate, which has good reference significance for the vehicle to determine the control data of the braking behavior.

[0104] The digital twin intelligent computing system is also used to obtain the multiple test cases and the bench reference data, input the multiple test cases into the digital twin virtual reality system to generate test environment data, and predict the relevant performance of the solenoid valve based on the test environment data to obtain relevant performance test data; wherein, the bench reference data is used to optimize the relevant performance test data and / or virtual environment data. For example, the bench reference data includes bench test data of multiple target vehicles of multiple scenarios and multiple types (such as the first reliability calculation result including the solenoid valve performance), and the relevant performance test data includes the second reliability result of the solenoid valve performance of a single target vehicle obtained by the reliability calculation module. The first reliability calculation results of multiple target vehicles are compared with the second reliability results to obtain a comparison result, and the second reliability results are optimized (corrected) based on the comparison result.

[0105] In some alternative embodiments, such as Figure 6 shown, the intelligent optimization module of the digital twin intelligent computing system is used to optimize the data processing module, the reliability calculation module, the performance optimization module, and the life prediction module based on the bench reference data (i.e., optimize the relevant performance test data). For example, by comparing the bench reference data with the data from the digital twin virtual reality system, the data processing module, the reliability calculation module, the performance optimization module, and the life prediction module can be calibrated and corrected.

[0106] In some alternative embodiments, such as Figure 6 shown, the solenoid valve bench test system includes a data recombination module, a bench environment simulation module, a solenoid valve bench module, and a sensing module. The data recombination module is used to perform processing such as screening, deduplication, and recombination on the data from the data processing system (such as target environment data and target control data) to form effective diverse braking behavior big data, and form big data test cases accordingly. The big data test cases and the bench reference data output by the solenoid valve bench test system are also input into the digital twin intelligent computing system. At the same time, the digital twin intelligent computing system also uses the big data test cases to perform virtual tests through the digital twin virtual reality system, and compares the performance optimization calculation results, reliability calculation results, and life prediction deduction results obtained from the tests in the digital twin intelligent computing system with the bench reference data, and corrects and optimizes the data processing module, the reliability calculation module, the performance optimization module, and the life prediction module in the digital twin intelligent computing system through the intelligent optimization module.

[0107] To solve the above problems, the present application provides a solenoid valve performance prediction method based on the above system. Specifically, by obtaining the sensing data and control data of the target vehicle, and respectively preprocessing the sensing data and the control data, the target environmental data and target control data of the target vehicle are correspondingly obtained; based on the target control data and the target environmental data, relevant environment simulation of the solenoid valve of the target vehicle is performed to obtain virtual environmental data; based on the virtual environmental data and / or the target control data, the relevant performance of the solenoid valve is predicted. In this way, the relevant performance of the solenoid valve can be actively predicted during vehicle driving, the prediction of solenoid valve faults can be realized, and the driving safety of the vehicle can be ensured.

[0108] The following introduces a specific embodiment of a solenoid valve performance prediction method of the present application. Figure 7 FIG. is a schematic flow chart of a solenoid valve performance prediction method provided by an embodiment of the present application. This specification provides method operation steps such as in the embodiment or flow chart, but based on routine or non-creative labor, there may be more or fewer operation steps. The step order listed in the embodiment is only one way among the execution orders of numerous steps, and does not represent the only execution order. When the actual system or server product executes, it can be executed in the order of the embodiment or as shown in the accompanying drawings, or executed in parallel (for example, in an environment of parallel processors or multi-threaded processing). Specifically, as Figure 7 shown, the method may include:

[0109] S201: Obtain the sensing data and control data of the target vehicle, and respectively preprocess the sensing data and the control data to correspondingly obtain the target environmental data and target control data of the target vehicle. For example, the data processing system obtains and preprocesses the sensing data and control data of the target vehicle.

[0110] In some alternative embodiments, the sensing data includes but is not limited to data collected by sensors of the by-wire braking system itself,

[0111] and also includes data collected by other available sensors of the vehicle; the sensing data is optionally vehicle acceleration, vehicle speed,

[0112] braking distance, ambient temperature, ambient humidity, electronic pedal displacement and other data. The control data includes but is not limited to data of the controller of the by-wire braking system.

[0113] In some alternative embodiments, the preprocessing includes at least one of parsing, format conversion, precision conversion, screening, interpolation optimization, classification, and identification assignment. In this way, the readability, density, precision, etc. of the sensing data and control data are improved.

[0114] S203: Perform relevant environmental simulation of the solenoid valve of the target vehicle based on the target control data and the target environmental data to obtain virtual environmental data. For example, the digital twin virtual reality system performs relevant environmental simulation of the solenoid valve of the target vehicle based on the target control data and the target environmental data. Among them, the target control data is converted into virtual control data recognizable by the digital twin virtual reality system through the digital twin intelligent computing system.

[0115] In some alternative embodiments, the virtual environmental data includes the external environmental data of the solenoid valve and the body environmental data of the solenoid valve;

[0116] Performing the relevant environmental simulation of the solenoid valve of the target vehicle based on the target control data and the target environmental data to obtain virtual environmental data includes:

[0117] Perform external environmental simulation of the solenoid valve based on the target environmental data to obtain the external environmental data of the solenoid valve;

[0118] Perform body environmental simulation of the solenoid valve based on the target control data to obtain the body environmental data of the solenoid valve.

[0119] For example, the digital twin virtual reality system includes a digital twin virtual environment system and a digital twin solenoid valve simulation system;

[0120] The digital twin virtual environment system performs external environmental simulation of the solenoid valve based on the target environmental data to obtain the external environmental data of the solenoid valve;

[0121] The digital twin solenoid valve simulation system performs body environmental simulation of the solenoid valve based on the virtual control data to obtain the body environmental data of the solenoid valve.

[0122] In some alternative embodiments, performing the external environmental simulation of the solenoid valve based on the target environmental data includes at least one of the following simulations:

[0123] Simulate the high and low frequency vibrations of the installation boundary and environment of the solenoid valve;

[0124] Simulate the heat conduction characteristics of the surrounding environment of the solenoid valve;

[0125] Simulate the electromagnetic characteristics of the vehicle environment;

[0126] Simulate the movement and dynamic characteristics of the installation boundary and environment of the solenoid valve.

[0127] In some alternative embodiments, performing the body environmental simulation of the solenoid valve based on the target control data includes at least one of the following simulations:

[0128] Simulate the electromagnetic part of the solenoid valve;

[0129] Simulate the mechanical structure of the solenoid valve;

[0130] Simulate the internal flow field dynamics and multiphase flow characteristics of the solenoid valve;

[0131] Simulate the multi-degree-of-freedom moving parts and system motion characteristics of the solenoid valve.

[0132] S205: Predict the relevant performance of the solenoid valve based on the virtual environment data and / or target control data.

[0133] For example, the digital twin intelligent computing system predicts the relevant performance of the solenoid valve based on the virtual environment data and / or target control data.

[0134] In some alternative embodiments, the relevant performance of the solenoid valve includes at least one of the life, failure, reliability, and optimized control data of the solenoid valve; the optimized control data is used for the target vehicle to control the solenoid valve. In this way, a comprehensive prediction of the relevant performance of the solenoid valve can be achieved, the performance problems related to the solenoid valve can be discovered in time, and the control data can be adjusted in time to improve the driving safety of the vehicle.

[0135] In the above embodiments, by acquiring the sensing data and control data of the vehicle in real time, the relevant performance of the solenoid valve can be predicted in real time.

[0136] Figure 8 It is a schematic flowchart of another method for predicting the performance of a solenoid valve provided by an embodiment of the present application. As Figure 8 shown, the method includes Figure 7 the steps shown, that is, steps S201 - S205, which will not be elaborated here Figure 7 for the step content. The specific steps of the method further include:

[0137] S207: Based on the sensing data and control data of multiple target vehicles, construct multiple test cases with diverse braking behaviors.

[0138] S209: Conduct a bench test on the solenoid valve based on multiple test cases to obtain bench reference data.

[0139] For example, a solenoid valve bench test system implements the above steps S207 - S209 to obtain bench reference data.

[0140] S211: Conduct relevant environment simulation of the solenoid valve based on multiple test cases to obtain test environment data.

[0141] For example, the digital twin virtual reality system performs relevant environment simulation of the solenoid valve based on multiple test cases to obtain test environment data.

[0142] S213: Based on the test environment data, predict the relevant performance of the solenoid valve to obtain relevant performance test data.

[0143] S215: Optimize the relevant performance test data and / or the relevant performance test data based on the bench reference data.

[0144] For example, the digital twin intelligent computing system obtains the multiple test cases and the bench reference data, inputs the multiple test cases into the digital twin virtual reality system to generate test environment data, and predicts the relevant performance of the solenoid valve based on the test environment data to obtain relevant performance test data; the bench reference data is used to optimize the relevant performance test data and / or the virtual environment data.

[0145] Through this embodiment, based on test cases composed of a large amount of real vehicle data (i.e., sensing data and control data), the relevant performance of the solenoid valve is optimized, and the optimized control data obtained by the optimization is sent to the vehicle through the data processing system, further improving the driving safety of the vehicle.

[0146] In this way, through the solenoid valve performance prediction system based on the above digital twin technology, the above solenoid valve performance prediction method is realized.

[0147] Figure 9 It is a hardware structure block diagram of an electronic device provided by an embodiment of the present application for implementing a solenoid valve performance prediction method. This electronic device can be a server or a terminal device, and its internal structure diagram can be as Figure 9 shown. As Figure 9As shown, the electronic device 800 can vary significantly due to different configurations or performances. It may include one or more central processing units (CPUs) 810 (the processor 810 may include, but is not limited to, processing devices such as a microprocessor MCU or a field-programmable gate array FPGA), a memory 830 for storing data, and one or more storage media 820 (such as one or more mass storage devices) for storing application programs 823 or data 822. Among them, the memory 830 and the storage media 820 can be transient storage or persistent storage. The program stored in the storage media 820 may include one or more modules, and each module may include a series of instruction operations on the server. Further, the central processor 810 can be set to communicate with the storage media 820 and execute a series of instruction operations in the storage media 820 on the electronic device 800. The electronic device 800 may also include one or more power supplies 860, one or more wired or wireless network interfaces 850, one or more input / output interfaces 840, and / or one or more operating systems 821,

[0148] such as Windows, Mac OS, Unix, Linux, FreeBSD, and so on.

[0149] The input / output interface 840 can be used to receive or send data via a network. Specific examples of the above network may include a wireless network provided by the communication provider of the electronic device 800. In one instance, the input / output interface 840 includes a network interface controller (NIC), which can be connected to other network devices through a base station and thus communicate with the Internet. In one instance, the input / output interface 840 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0150] The power supply 860 can be logically connected to the processor 810 through a power management system, so as to implement functions such as management of charging, discharging, and power consumption management through the power management system.

[0151] Those of ordinary skill in the art can understand that, Figure 9 the structure shown is only schematic and does not limit the structure of the above electronic device. For example, the electronic device 800 may also include more or fewer components than those shown in Figure 9 or have a different configuration from that shown in Figure 9 shown.

[0152] An embodiment of the present application further provides a computer storage medium, in which at least one instruction or at least one program segment is stored, and the at least one instruction or at least one program segment is loaded and executed by a processor to implement the above-mentioned solenoid valve performance prediction method.

[0153] Optionally, in this embodiment, the above storage medium may be located in at least one of multiple network servers in a computer network. Optionally, in this embodiment, the above storage medium may include, but is not limited to: various media that can store program codes such as USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks, or optical discs.

[0154] An embodiment of the present application further provides an electronic device, which at least includes a processor 810 and a memory 830. At least one instruction or at least one program segment is stored in the memory 830, and the at least one instruction or at least one program segment is loaded and executed by the processor 810 to implement the above-mentioned solenoid valve performance prediction method.

[0155] As can be seen from the above embodiments of the solenoid valve performance prediction method and system provided by the present application, by obtaining the sensing data and control data of the target vehicle, and respectively preprocessing the sensing data and the control data, the target environmental data and target control data of the target vehicle are correspondingly obtained; based on the target control data and the target environmental data, relevant environmental simulation of the solenoid valve of the target vehicle is performed to obtain virtual environmental data; based on the virtual environmental data and / or the target control data, relevant performance of the solenoid valve is predicted. It is possible to actively predict the relevant performance of the solenoid valve during vehicle driving, realize the prediction of solenoid valve faults, and ensure the driving safety of the vehicle.

[0156] It should be noted that: the above sequence of embodiments of the present application is only for description and does not represent the advantages or disadvantages of the embodiments. And the above description of specific embodiments of this specification is made. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0157] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and for the relevant parts, reference can be made to the partial description of the method embodiments.

[0158] Those of ordinary skill in the art can understand that all or part of the steps for implementing the above embodiments can be completed by hardware or by a program instructing relevant hardware. The program can be stored in a computer-readable storage medium, and the above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disk, or the like.

[0159] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A solenoid valve performance prediction system, characterized in that, It includes a data processing system, a digital twin intelligent computing system, and a digital twin virtual reality system; the digital twin virtual reality system includes a digital twin virtual environment system and a digital twin solenoid valve simulation system; The data processing system is used to obtain the sensing data and control data of the target vehicle, and preprocess the sensing data and the control data respectively to obtain the target environment data and target control data of the target vehicle; The digital twin intelligent computing system is used to obtain the target control data and convert the target control data into virtual control data recognizable by the digital twin virtual reality system; The digital twin virtual reality system is used to obtain the target environment data and the virtual control data; the digital twin virtual environment system simulates the external environment of the solenoid valve based on the target environment data to obtain the external environment data of the solenoid valve; the digital twin solenoid valve simulation system simulates the body environment of the solenoid valve based on the virtual control data to obtain the body environment data of the solenoid valve; wherein, the body environment data includes simulation data based on the structure and performance of the solenoid valve body; The digital twin intelligent computing system predicts the relevant performance of the solenoid valve based on the virtual environment data and / or the target control data; the virtual environment data includes the external environment data and the body environment data.

2. The system according to claim 1, wherein The digital twin virtual environment system includes at least one of a motion and dynamics module, an environmental vibration module, an environmental heat conduction and radiation module, and an environmental electromagnetic radiation module: The environmental vibration module is used to simulate the installation boundary of the solenoid valve and the high and low frequency vibrations of the environment; The environmental heat conduction and radiation module is used to simulate the heat conduction characteristics of the surrounding environment of the solenoid valve; The environmental electromagnetic radiation module is used to simulate the electromagnetic characteristics of the vehicle environment; The motion and dynamics module is used to simulate the motion and dynamics characteristics of the installation boundary and environment of the solenoid valve.

3. The system according to claim 1, wherein The digital twin solenoid valve simulation system includes at least one of an electromagnetic mechanics module, a material and elastic mechanics module, a fluid and multiphase flow module, and a multibody dynamics module; The electromagnetic mechanics module is used to simulate the electromagnetic part of the solenoid valve; The material and elastic mechanics module is used to simulate the mechanical structure of the solenoid valve; The fluid and multiphase flow module is used to simulate the internal flow field dynamics and multiphase flow characteristics of the solenoid valve; The multibody dynamics module is used to simulate the multi-degree-of-freedom moving parts and system motion characteristics of the solenoid valve.

4. The system according to claim 1, wherein The relevant performance of the solenoid valve includes at least one of the life, failure, reliability, and optimized control data of the solenoid valve; the optimized control data is used for the target vehicle to control the solenoid valve.

5. The system according to claim 1, wherein The preprocessing includes at least one of parsing, format conversion, precision conversion, screening, interpolation optimization, classification, and identification assignment.

6. The system according to any one of claims 1 to 5, characterized in that, The solenoid valve is arranged in the electronic brake system of the target vehicle; the system also includes a solenoid valve bench test system; The solenoid valve bench test system is used to obtain the sensing data and control data of multiple target vehicles, generate multiple test cases of diverse braking behaviors based on the sensing data and control data of the multiple target vehicles, and perform solenoid valve bench tests based on the multiple test cases to obtain bench reference data; The digital twin intelligent computing system is further used to obtain the multiple test cases and the bench reference data, input the multiple test cases into the digital twin virtual reality system to generate test environment data, and predict the relevant performance of the solenoid valve based on the test environment data to obtain relevant performance test data; wherein, the bench reference data is used to optimize the relevant performance test data and / or the virtual environment data.

7. A method for predicting the performance of a solenoid valve, characterized in that, The method includes: Obtain the sensing data and control data of the target vehicle, and preprocess the sensing data and the control data respectively to obtain the target environment data and target control data of the target vehicle; Perform relevant environment simulation of the solenoid valve of the target vehicle based on the target control data and the target environment data to obtain virtual environment data; Predict the relevant performance of the solenoid valve based on the virtual environment data and / or the target control data; Wherein, the virtual environment data includes the external environment data of the solenoid valve and the body environment data of the solenoid valve; the performing relevant environment simulation of the solenoid valve of the target vehicle based on the target control data and the target environment data to obtain virtual environment data includes: Perform external environment simulation of the solenoid valve based on the target environment data to obtain the external environment data of the solenoid valve; Perform body environment simulation of the solenoid valve based on the target control data to obtain the body environment data of the solenoid valve; wherein, the body environment data includes simulation data based on the structure and performance of the solenoid valve body.

8. The method according to claim 7, characterized in that The method further includes: Construct multiple test cases of diverse braking behaviors based on the sensing data and control data of multiple target vehicles; Perform solenoid valve bench tests based on the multiple test cases to obtain bench reference data; Perform relevant environment simulation of the solenoid valve based on the multiple test cases to obtain test environment data; Predict the relevant performance of the solenoid valve based on the test environment data to obtain relevant performance test data; Optimize the relevant performance test data and / or the virtual environment data based on the bench reference data.

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