Control variable design method and device of electric control valve and computer equipment

Abstract

The invention relates to the technical field of electronic control valve control variable design or computer aided design, in particular to a control variable design method and device of an electronic control valve and a computer equipment control variable. The method comprises the steps that a finite element analysis method is adopted, a coupling model of the electric control valve is constructed, and the coupling model is used for representing the coupling relation among a temperature field, a stress field and a fluid field in the electric control valve; minimizing the angle control error of the electric control valve and maximizing the sealing performance of the electric control valve are taken as targets, the initial control variable of the electric control valve is taken as an optimization design starting point, and the optimization control variable of the electric control valve is determined; the optimized control variables of the electric control valve are input into the coupling model for verification, and performance parameters of the coupling model under the optimized control variables are obtained; and under the condition that it is determined that the performance parameters meet the set execution conditions, the optimal control variable of the electric control valve serves as the target control variable of the electric control valve.

Description

Technical Field

[0001] This application relates to the technical field of electronically controlled valve control variable design or computer-aided design, and particularly relates to a method, device, and computer equipment for designing control variables of an electronically controlled valve. Background Art

[0002] The actuator of an electronically controlled valve is an important part of the electronically controlled valve. It is mainly responsible for receiving control signals and driving the valve to open, close, or adjust according to the signals, so as to achieve precise control of parameters such as the flow rate, pressure, and temperature of fluids (such as liquids, gases, etc.). In actual applications, the actuator needs to precisely control the angle to accurately adjust parameters such as the fluid flow rate and pressure.

[0003] Traditional control algorithms may be relatively simple and unable to adapt to the complex dynamic characteristics and working condition changes of electronically controlled valves, resulting in an increase in angle control errors and difficulty in achieving precise adjustment of fluid parameters. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, and computer equipment for designing control variables of an electronically controlled valve that can improve the execution accuracy of the electronically controlled valve.

[0005] In a first aspect, this application provides a method for designing control variables of an electronically controlled valve, which is applied to a computer device. The method includes:

[0006] Adopt the finite element analysis method to construct a coupling model of the electronically controlled valve, and the coupling model is used to characterize the coupling relationship between the temperature field, stress field, and fluid field inside the electronically controlled valve;

[0007] Taking the minimization of the angle control error of the electronically controlled valve and the maximization of the sealing performance of the electronically controlled valve as the goal, and using the initial control variables of the electronically controlled valve as the starting point for optimal design, determine the optimal control variables of the electronically controlled valve;

[0008] Input the optimal control variables of the electronically controlled valve into the coupling model for verification, and obtain the performance parameters of the coupling model under the optimal control variables; the performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters, and sealing performance parameters;

[0009] When it is determined that the performance parameters meet the set execution conditions, use the optimal control variables of the electronically controlled valve as the target control variables of the electronically controlled valve.

[0010] In one of the embodiments, adopting the finite element analysis method to construct a coupling model of the electronically controlled valve includes:

[0011] Perform preliminary geometric modeling on the electronically controlled valve to obtain a three-dimensional geometric model;

[0012] An initial mesh division is performed on the three-dimensional geometric model using a uniform mesh division strategy to generate multiple finite element meshes, and an initial fixed time step corresponding to the three-dimensional geometric model is obtained;

[0013] Based on the multiple finite element meshes, the physical properties and boundary conditions of the internal temperature field, stress field, and fluid field of the electric control valve are defined;

[0014] Using a finite element analysis software, the coupled equations of the temperature field, stress field, and fluid field are solved to obtain preliminary calculation results of the multiple finite element meshes at a fixed time step;

[0015] According to the preliminary calculation results, each finite element mesh is adaptively refined to obtain each finite element mesh that meets the mesh refinement accuracy in the modeling accuracy;

[0016] According to the preliminary calculation results, the fixed time step is adjusted to obtain a fixed time step that meets the step accuracy in the modeling accuracy;

[0017] According to each finite element mesh that meets the mesh refinement accuracy in the modeling accuracy and the fixed time step that meets the step accuracy in the modeling accuracy, a coupled model of the electric control valve is constructed.

[0018] In one embodiment, according to the preliminary calculation results, each finite element mesh is adaptively refined to obtain each finite element mesh that meets the mesh refinement accuracy in the modeling accuracy, including:

[0019] For each finite element mesh, according to the preliminary calculation results, the physical quantity gradients of each physical quantity in the temperature field, stress field, and fluid field within each finite element mesh unit are calculated, and the energy error of each finite element mesh unit is estimated using the energy norm method to obtain the energy error value of each finite element mesh unit;

[0020] For each finite element mesh unit, the finite element mesh units with physical quantity gradients exceeding the corresponding gradient threshold of the physical quantity are marked as the first units to be refined;

[0021] The finite element mesh units with energy error values exceeding the energy error threshold are marked as the second units to be refined;

[0022] The finite element mesh units marked as the first units to be refined and the second units to be refined are adaptively refined to obtain finite element meshes that meet the mesh refinement accuracy in the modeling accuracy.

[0023] In one embodiment, the finite element mesh units marked as the first units to be refined and the second units to be refined are adaptively refined to obtain finite element meshes that meet the mesh refinement accuracy in the modeling accuracy, including:

[0024] For each finite element mesh cell marked as the first unit to be refined and the second unit to be refined, adaptively refine the finite element mesh cell until the element accuracy index corresponding to the refined finite element mesh cell meets the element accuracy threshold;

[0025] Among them, the element accuracy index includes the upper limit of element size, the element shape quality index, and the adjacent element size change rate;

[0026] The element accuracy index corresponding to each finite element mesh cell in the finite element mesh that meets the mesh refinement accuracy in the modeling accuracy meets the element accuracy threshold.

[0027] In one embodiment, adaptively refining the finite element mesh cell includes:

[0028] According to the element type of the finite element mesh cell, use the bisection method, the quartering method, or the octree method to adaptively refine the finite element mesh cell.

[0029] In one embodiment, adjusting the fixed time step to obtain a fixed time step that meets the step accuracy in the modeling accuracy includes:

[0030] Based on the preliminary calculation results, calculate the change rates of various physical quantities in the temperature field, stress field, and fluid field within each time step. The change rates of various physical quantities include the temperature change rate, the stress change rate, and the fluid flow velocity change rate;

[0031] Use the stability criterion in finite element analysis to evaluate the calculation stability under the fixed time step and obtain the stability evaluation result;

[0032] If there is at least one change rate of a physical quantity that does not meet the set change rate threshold, or the stability evaluation result does not meet the stability condition, then adjust the fixed time step to obtain a fixed time step that meets the step accuracy in the modeling accuracy.

[0033] In one embodiment, adjusting the fixed time step includes:

[0034] If there is at least one change rate of a physical quantity that exceeds the set change rate threshold, or the stability evaluation result does not meet the stability condition, then determine to reduce the fixed time step;

[0035] If it is determined that the change rates of all physical quantities are less than the set change rate threshold and the stability evaluation result meets the stability condition, then increase the fixed time step by the set step increment.

[0036] In one embodiment, the initial control variables include the PWM duty cycle, the motor speed, and the worm and worm gear transmission ratio;

[0037] Correspondingly, aiming to minimize the angle control error of the electro-control valve and maximize the sealing performance of the electro-control valve, starting from the initial control variables of the electro-control valve as the starting point of the optimization design, the optimized control variables of the electro-control valve are determined, including:

[0038] Aiming to minimize the angle control error of the electro-control valve and maximize the sealing performance of the electro-control valve, under the energy consumption constraint and response time constraint of the electro-control valve, starting from the initial control variables of the electro-control valve as the starting point of the optimization design, the optimized control variables of the electro-control valve are determined.

[0039] In one embodiment, aiming to minimize the angle control error of the electro-control valve and maximize the sealing performance of the electro-control valve, under the energy consumption constraint and response time constraint of the electro-control valve, starting from the initial control variables of the electro-control valve as the starting point of the optimization design, the optimized control variables of the electro-control valve are determined, including:

[0040] Aiming to minimize the angle control error of the electro-control valve and maximize the sealing performance of the electro-control valve, the penalty function method is used to handle the energy consumption constraint and response time constraint, and a penalty term proportional to the degree of constraint violation is added; and,

[0041] Starting from the initial control variables of the electro-control valve as the starting point of the optimization design, the optimized control variables of the electro-control valve are determined.

[0042] In one embodiment, the initial control variables of the electro-control valve are determined according to the design specifications and historical operation data of the electro-control valve.

[0043] In a second aspect, the present application also provides a control variable design device for an electro-control valve, configured in a computer device, and the device includes:

[0044] A model construction module, which is used to construct a coupling model of the electro-control valve by using the finite element analysis method, and the coupling model is used to characterize the coupling relationship between the temperature field, stress field and fluid field inside the electro-control valve;

[0045] An optimization module, which is used to determine the optimized control variables of the electro-control valve with the goal of minimizing the angle control error of the electro-control valve and maximizing the sealing performance of the electro-control valve, starting from the initial control variables of the electro-control valve as the starting point of the optimization design;

[0046] A verification module, which is used to input the optimized control variables of the electro-control valve into the coupling model for verification to obtain the performance parameters of the coupling model under the optimized control variables; the performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters and sealing performance parameters;

[0047] A variable design module, which is used to use the optimized control variables of the electro-control valve as the target control variables of the electro-control valve when it is determined that the performance parameters meet the set execution conditions.

[0048] In a third aspect, the present application also provides an electro-control valve, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0049] Adopt the finite element analysis method to construct a coupling model of the electro-control valve, and the coupling model is used to characterize the coupling relationship between the temperature field, stress field and fluid field inside the electro-control valve;

[0050] Taking minimizing the angle control error of the electro-control valve and maximizing the sealing performance of the electro-control valve as the goal, and taking the initial control variables of the electro-control valve as the starting point of the optimization design, determine the optimized control variables of the electro-control valve;

[0051] Input the optimized control variables of the electro-control valve into the coupling model for verification to obtain the performance parameters of the coupling model under the optimized control variables; the performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters and sealing performance parameters;

[0052] When it is determined that the performance parameters meet the set execution conditions, take the optimized control variables of the electro-control valve as the target control variables of the electro-control valve.

[0053] In a fourth aspect of model construction, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0054] Adopt the finite element analysis method to construct a coupling model of the electro-control valve, and the coupling model is used to characterize the coupling relationship between the temperature field, stress field and fluid field inside the electro-control valve;

[0055] Taking minimizing the angle control error of the electro-control valve and maximizing the sealing performance of the electro-control valve as the goal, and taking the initial control variables of the electro-control valve as the starting point of the optimization design, determine the optimized control variables of the electro-control valve;

[0056] Input the optimized control variables of the electro-control valve into the coupling model for verification to obtain the performance parameters of the coupling model under the optimized control variables; the performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters and sealing performance parameters;

[0057] When it is determined that the performance parameters meet the set execution conditions, take the optimized control variables of the electro-control valve as the target control variables of the electro-control valve.

[0058] In a fifth aspect of model construction, the present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the following steps are implemented:

[0059] Adopt the finite element analysis method to construct a coupling model of the electro-control valve, which is used to characterize the coupling relationship between the temperature field, stress field and fluid field inside the electro-control valve;

[0060] Taking minimizing the angle control error of the electro-control valve and maximizing the sealing performance of the electro-control valve as the goal, and taking the initial control variables of the electro-control valve as the starting point of the optimization design, determine the optimized control variables of the electro-control valve;

[0061] Input the optimized control variables of the electro-control valve into the coupling model for verification, and obtain the performance parameters of the coupling model under the optimized control variables; the performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters and sealing performance parameters;

[0062] When it is determined that the performance parameters meet the set execution conditions, take the optimized control variables of the electro-control valve as the target control variables of the electro-control valve.

[0063] For the above control variable design method, device and computer equipment of the electro-control valve, the present application adopts the finite element analysis method to construct a coupling model of the electro-control valve, which can accurately characterize the coupling relationship between the temperature field, stress field and fluid field inside the electro-control valve. Traditional methods often have difficulty in comprehensively considering these complex interactions, while the coupling model helps to more deeply understand the dynamic characteristics of the electro-control valve under different working conditions. Different temperature, stress and fluid conditions will cause changes in the response and performance of the electro-control valve, and the coupling model can simulate these complex change situations. Taking minimizing the angle control error of the electro-control valve as the goal, optimize the initial control variables. Traditional control algorithms are simple and cannot adapt to complex working condition changes, resulting in an increase in the angle control error. The target control variables determined through verification in the present application can better adapt to the actual working conditions and dynamic characteristics of the electro-control valve. In practical applications, the electro-control valve faces various complex working environments and working condition changes. Adopting the optimized and verified control variables can ensure the stable and reliable operation of the electro-control valve. Description of the Drawings

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0065] Figure 1 It is a schematic flowchart of the control variable design method of the electro-control valve in an embodiment;

[0066] Figure 2 It is a schematic flowchart of the steps for constructing the coupling model of the electro-control valve in an embodiment;

[0067] Figure 3 It is a schematic flow chart of a fixed time step procedure for meeting the step size accuracy in the modeling accuracy in one embodiment;

[0068] Figure 4 It is a structural block diagram of a control variable design device for an electronically controlled valve in one embodiment. Specific embodiments

[0069] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0070] In an exemplary embodiment, as Figure 1 shown, a method for designing a control variable of an electronically controlled valve is provided, which is applied to a computer device. The method includes:

[0071] S101, constructing a coupling model of the electronically controlled valve by using the finite element analysis method.

[0072] Among them, the coupling model is a mathematical model used to describe the interaction and coupling relationship between multiple physical fields (such as temperature field, stress field, fluid field). Through this model, the mutual influence between different physical fields can be analyzed. Specifically: the coupling model is used to characterize the coupling relationship between the temperature field, stress field and fluid field inside the electronically controlled valve.

[0073] Optionally, a geometric model of the electronically controlled valve is created using 3D modeling software, including each component and internal channel of the electronically controlled valve. The geometric model is imported into the finite element analysis software, and the model is meshed and discretized into a finite number of elements. The quality and density of the mesh will affect the accuracy and efficiency of the calculation results. The material properties of each component of the electronically controlled valve are defined, including thermal conductivity, elastic modulus, Poisson's ratio, etc. These properties will be used to calculate the temperature field and stress field. According to the actual situation, the boundary conditions of the electronically controlled valve are defined, including temperature boundary conditions, stress boundary conditions and fluid boundary conditions. For example, the operating temperature of the electronically controlled valve, the applied external force and the inlet and outlet flow rates of the fluid are specified. In the finite element analysis software, the coupling relationship between the temperature field, stress field and fluid field is set. For example, considering the influence of thermal stress, the calculation result of the temperature field is used as the input of the stress field.

[0074] Solving the model: Run the finite element analysis software to solve the coupling model, and obtain the temperature field, stress field and fluid field distributions inside the electronically controlled valve.

[0075] S102. With the goal of minimizing the angle control error of the electro-control valve and maximizing its sealing performance, and taking the initial control variables of the electro-control valve as the starting point of the optimization design, determine the optimized control variables of the electro-control valve.

[0076] Among them, the angle control error refers to the deviation between the actually output angle of the electro-control valve and the desired angle. Minimizing the angle control error can improve the control accuracy of the electro-control valve. The sealing performance refers to the ability of the electro-control valve to prevent internal fluid leakage. Maximizing the sealing performance can ensure the normal operation and reliability of the electro-control valve.

[0077] Among them, the initial control variables refer to the control variables used by the electro-control valve before the start of optimization and serve as the starting point of the optimization process. The optimized control variables refer to a set of control variables obtained through an optimization algorithm, aiming to optimize the performance of the electro-control valve.

[0078] Optionally, with the goal of minimizing the angle control error of the electro-control valve and maximizing its sealing performance, define the objective function. For example, the weighted sum of the angle control error and the sealing performance can be used as the objective function.

[0079] Furthermore, select the initial control variables of the electro-control valve as the optimization variables, such as control voltage, control current, etc. According to the characteristics and requirements of the problem, select a suitable optimization algorithm, such as genetic algorithm, particle swarm algorithm, etc. Set the parameters of the optimization algorithm, such as population size, number of iterations, etc.

[0080] Finally, input the objective function, optimization variables, and optimization algorithm parameters into the optimization software, run the optimization algorithm, and obtain the optimized control variables of the electro-control valve.

[0081] S103. Input the optimized control variables of the electro-control valve into the coupling model for verification, and obtain the performance parameters of the coupling model under the optimized control variables.

[0082] Among them, the performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters, and sealing performance parameters.

[0083] Optionally, take the optimized control variables as new boundary conditions, initial conditions, or material properties, etc., and input them into the coupling model. Use finite element analysis software to solve the updated coupling model to obtain the distribution of each physical field. Extract and calculate the temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters, and sealing performance parameters from the solution results.

[0084] Specifically, the temperature field performance parameters are obtained in the following manner: In the temperature field distribution data obtained by solving, find the maximum value among the temperature values of all nodes or elements. Find the minimum value among the temperature values of all nodes or elements. Sum up the temperature values of all nodes or elements, and then divide by the total number of nodes or elements.

[0085] Specifically, the stress field performance parameters are obtained in the following manner: In the stress field distribution data, find the maximum value of the equivalent stress (such as Von-Mises stress). Find the minimum value of the equivalent stress. The ratio of the maximum stress in a specific area to the nominal stress, and the nominal stress can be calculated according to simple mechanical formulas.

[0086] Specifically, the fluid field distribution performance parameters are obtained in the following manner: In the fluid field velocity distribution data, find the maximum value of the velocity magnitude. Find the minimum value of the velocity magnitude. Sum up the flow velocity values of all nodes or elements, and then divide by the total number of nodes or elements to obtain the average flow velocity.

[0087] Specifically, the angle control accuracy parameter is obtained in the following manner: The angle control error is obtained by subtracting the actual output angle of the electric control valve from the desired angle. The actual output angle can be obtained from the rotation angle data at a specific position in the model, and the desired angle is a pre-set target value.

[0088] Specifically, the temperature field performance parameters are obtained in the following manner: Calculate the pressure difference between both sides of the seal, the pressure data can be extracted from the solution results, and / or the leakage rate, and the leakage rate can be estimated by simulating the fluid flow rate on the leakage path, or calculated according to a specific seal theoretical model.

[0089] S104, when it is determined that the performance parameters meet the set execution conditions, use the optimized control variable of the electric control valve as the target control variable of the electric control valve.

[0090] Optionally, input the optimized control variable of the electric control valve into the previously constructed coupling model. Run the coupling model to simulate the performance of the electric control valve under actual working conditions, and obtain a series of performance parameters, including temperature field parameters (such as temperature distribution, temperature change rate), stress field parameters (such as stress distribution, maximum stress value), fluid field distribution parameters (such as flow velocity, pressure distribution), angle control accuracy (such as the deviation between the actual angle and the desired angle), and sealing performance (such as leakage rate, contact pressure of the sealing surface).

[0091] Furthermore, according to the design requirements and working conditions of the electric control valve, set a series of set execution conditions. These conditions may include temperature upper limit, stress upper limit, fluid flow stability requirements, angle control accuracy threshold, and sealing performance standards, etc. These set execution conditions should ensure that the electric control valve can work safely and reliably in actual applications and meet the expected performance requirements.

[0092] Subsequently, compare the obtained performance parameters with the set execution conditions, and evaluate whether each performance parameter meets the corresponding set execution conditions one by one. If a certain performance parameter does not meet the set execution conditions, it is necessary to re-optimize or adjust the coupling model until all performance parameters meet the set execution conditions.

[0093] After confirming that all performance parameters meet the set execution conditions, use the optimized control variables of the electromagnetic valve as the target control variables. These target control variables will be used for the control and operation of the actual electromagnetic valve to ensure that the electromagnetic valve can meet the expected performance requirements under actual working conditions.

[0094] In an exemplary embodiment, as Figure 2 shown, use the finite element analysis method to construct a coupling model of the electromagnetic valve, including:

[0095] S201, perform preliminary geometric modeling on the electromagnetic valve to obtain a three-dimensional geometric model.

[0096] S202, use a uniform mesh division strategy to perform initial mesh division on the three-dimensional geometric model, generate multiple finite element meshes, and obtain the initial fixed time step corresponding to the three-dimensional geometric model.

[0097] Optionally, in the finite element analysis software, select the uniform mesh division strategy to divide the three-dimensional geometric model into multiple finite element meshes. Set the size and shape of the mesh according to the geometric dimensions and modeling accuracy requirements of the electromagnetic valve. Execute the mesh division operation to generate multiple finite element meshes. Determine an initial fixed time step according to the working conditions and modeling accuracy requirements of the electromagnetic valve for subsequent finite element analysis.

[0098] S203, based on multiple finite element meshes, define the physical properties and boundary conditions of the internal temperature field, stress field, and fluid field of the electromagnetic valve.

[0099] Optionally, define the physical properties of the temperature field, stress field, and fluid field for each finite element mesh, such as thermal conductivity, elastic modulus, density, viscosity, etc. According to the working conditions and actual environment of the electromagnetic valve, set the corresponding boundary conditions for each finite element mesh, such as temperature boundary conditions (such as constant temperature, convective heat transfer, etc.), stress boundary conditions (such as fixed, free, stressed, etc.), and fluid boundary conditions (such as inlet flow rate, outlet pressure, etc.).

[0100] S204, use the finite element analysis software to solve the coupled equations of the temperature field, stress field, and fluid field to obtain the preliminary calculation results of multiple finite element meshes at the fixed time step.

[0101] Optionally, in the finite element analysis software, establish the coupled equations of the temperature field, stress field, and fluid field according to the physical properties and boundary conditions. Use the solver of the finite element analysis software to solve the coupled equations to obtain the preliminary calculation results of multiple finite element meshes at a fixed time step.

[0102] S205. According to the preliminary calculation results, adaptively refine each finite element mesh to obtain each finite element mesh that meets the mesh refinement accuracy in the modeling accuracy.

[0103] Optionally, create an initial finite element mesh, which can be structured or unstructured. Perform finite element solution on the initial mesh to obtain preliminary results (such as displacement, stress, temperature field, etc.).

[0104] Select an error estimation method. Common methods include: residual-based error estimation: calculate the residual of each element. Gradient-based error estimation: calculate the gradient of physical quantities (such as stress, strain). Energy-based error estimation: calculate the energy error of the element. Calculate the local error: for each element i, calculate its error Ei.

[0105] Set the error tolerance: define the global error tolerance ∈ and the local error tolerance ∈ local .

[0106] If Ei > ∈ local , mark the element as needing refinement. If Ei ≤ ∈ local , retain the element.

[0107] Refinement strategies include: h-refinement: divide the marked element into smaller elements (such as dividing a quadrilateral element into 4 sub-elements and a triangular element into 4 sub-triangles). p-refinement: increase the interpolation order of the element (such as increasing from linear interpolation to quadratic interpolation).

[0108] Refine the marked elements while ensuring that the refined mesh satisfies geometric and topological consistency. Generate a new refined mesh. Perform finite element solution on the new mesh. Recalculate the error and check whether the global error tolerance ∈ is satisfied. Repeat the above process until the error Ei of all elements ≤ ∈ local and the global error meets the requirements. When the global error E global ≤ ∈, stop the iteration. Output the final refined mesh and the solution results.

[0109] S206. According to the preliminary calculation results, adjust the fixed time step to obtain a fixed time step that meets the step accuracy in the modeling accuracy.

[0110] Optionally, based on experience or a preliminary estimate, select an initial time step Δt0. Use Δt0 for a preliminary simulation and record the results. Define an error metric E, such as the local truncation error or the global error. Calculate the error E0 of the preliminary simulation.

[0111] Set the error tolerance ∈. If E0 > ∈, decrease the time step Δt;

[0112] If E0 < ∈, increase the time step Δt.

[0113]

[0114] where p is the order of the method.

[0115] Repeat the simulation: Use the new Δt new to perform the simulation and calculate the new error E new .

[0116] Judge convergence: If E new ≤ ∈, stop adjusting; otherwise, continue to adjust the time step Δt final .

[0117] Determine the time step: When the error meets the requirements, determine the final fixed time step Δt final . Use Δt final to perform the final simulation to ensure that the results meet the accuracy requirements.

[0118] S207. Based on each finite element mesh that meets the mesh refinement accuracy in the modeling accuracy and the fixed time step that meets the time step accuracy in the modeling accuracy, construct a coupled model of the electro-control valve.

[0119] Optionally, when constructing the coupled model of the electro-control valve, it is necessary to combine the finite element mesh that meets the modeling accuracy and the fixed time step to ensure that the model achieves the required accuracy in both the spatial and temporal dimensions.

[0120] In an exemplary embodiment, based on the preliminary calculation results, adaptively refine each finite element mesh to obtain each finite element mesh that meets the mesh refinement accuracy in the modeling accuracy, including:

[0121] (1) For each finite element mesh, according to the preliminary calculation results, calculate the physical quantity gradients of the physical quantities in the temperature field, stress field, and fluid field in each finite element mesh unit, and use the energy norm method to estimate the energy error of each finite element mesh unit to obtain the energy error value of each finite element mesh unit.

[0122] It is understandable that in finite element analysis, temperature fields, stress fields, and fluid fields are common physical fields. The gradient of a physical quantity reflects the rate of change of the physical quantity in space. For example, the temperature gradient indicates how fast the temperature changes in space, and the stress gradient indicates the variation of stress in space. By calculating the gradients of these physical quantities, the degree of variation of the physical quantities within the finite element mesh elements can be understood.

[0123] It is understandable that the energy norm is a method for measuring error, which evaluates the difference between the finite element solution and the exact solution based on the concept of energy. In finite element analysis, due to the use of the discretization method, the obtained solution is an approximate solution and there is a certain error. Energy error estimation can understand the error magnitude of each element, thereby determining which elements need to be refined.

[0124] (2) For each finite element mesh element, mark the finite element mesh elements whose physical quantity gradient exceeds the gradient threshold corresponding to the physical quantity as the first elements to be refined, and mark the finite element mesh elements whose energy error value exceeds the energy error threshold as the second elements to be refined.

[0125] Optionally, for each finite element mesh element, mark the finite element mesh elements whose physical quantity gradient exceeds the gradient threshold corresponding to the physical quantity as the first elements to be refined. The gradient threshold is a preset standard value used to determine whether the change of the physical quantity within the element is too drastic. If the physical quantity gradient within a certain finite element mesh element exceeds the corresponding gradient threshold, it indicates that the change of the physical quantity within this element is very fast, and the finite element mesh may not be able to accurately describe this change, so this element needs to be refined to improve the calculation accuracy.

[0126] Among them, mark the finite element mesh elements whose energy error value exceeds the energy error threshold as the second elements to be refined. The energy error threshold is also a preset standard value used to determine whether the error of the finite element solution within this element is too large. If the energy error value of a certain finite element mesh element exceeds the energy error threshold, it indicates that the difference between the finite element solution and the exact solution of this element is relatively large, and this element needs to be refined to reduce the error.

[0127] (3) Adaptively refine the finite element mesh elements that are marked as the first elements to be refined and are also marked as the second elements to be refined to obtain a finite element mesh that meets the mesh refinement accuracy in the modeling accuracy.

[0128] Optionally, only those finite element mesh elements that satisfy both the physical quantity gradient exceeding the threshold and the energy error value exceeding the threshold will be refined. The purpose of this is to ensure that only those elements that really need to be refined are operated, avoiding unnecessary refinement and improving computational efficiency. By refining these elements, the finite element mesh can better adapt to changes in the physical field, thereby meeting the mesh refinement accuracy requirements in modeling accuracy.

[0129] Adaptive refinement usually involves splitting a large finite element mesh unit into multiple small finite element mesh units, such as splitting a quadrilateral unit into four smaller quadrilateral units. This can increase the density of the mesh and improve the accuracy of the description of the physical field.

[0130] In an exemplary embodiment, the finite element mesh units marked as the first unit to be refined and the second unit to be refined are adaptively refined to obtain a finite element mesh that satisfies the mesh refinement accuracy in the modeling accuracy, including: for each finite element mesh unit marked as the first unit to be refined and the second unit to be refined, the finite element mesh unit is adaptively refined until the unit accuracy index corresponding to the refined finite element mesh unit meets the unit accuracy threshold.

[0131] Among them, the unit accuracy indicators include the upper limit of unit size, unit shape quality index and the change rate of adjacent unit sizes.

[0132] Optionally, each finite element mesh unit marked as both the first unit to be refined and the second unit to be refined is to be adaptively refined. Adaptive refinement means selecting an appropriate refinement method and degree according to the characteristics of the finite element mesh unit itself and the actual situation, rather than adopting a uniform fixed method.

[0133] It is understandable that the refinement operation will continue until the unit accuracy index corresponding to the refined finite element mesh unit meets the unit accuracy threshold. Unit accuracy index is a quantitative index to measure the quality and applicability of finite element mesh units. When these indexes reach the preset threshold, it means that the refinement level of the unit has been able to meet the modeling accuracy requirements and no further refinement is required.

[0134] Among them, the upper limit of the unit size stipulates the maximum allowable size of the finite element mesh unit. If the unit size is too large, it may not be able to accurately describe the changes in the physical field in that area, resulting in inaccurate calculation results. By limiting the upper limit of the unit size, it can be ensured that the finite element mesh unit is small enough to improve the resolution of the physical field. For example, in a heat conduction problem, if the temperature in a certain area changes very drastically, then the unit size in that area needs to be small enough to accurately capture the temperature changes.

[0135] Among them, the element shape quality index is used to measure whether the shape of the finite element mesh elements is reasonable. Finite element mesh elements of different shapes may vary greatly in calculation accuracy and stability. For example, in the two-dimensional case, an ideal quadrilateral element should be close to a square, and in the three-dimensional case, an ideal hexahedral element should be close to a cube. If the element shape is too distorted or irregular, it may lead to an increase in calculation errors and even numerical instability problems. The element shape quality index can be defined by some geometric parameters, such as the side length ratio and interior angle size of the element.

[0136] Among them, the adjacent element size change rate reflects the degree of difference in size between adjacent finite element mesh elements. If the sizes of adjacent elements change too much, large errors may occur at the element junctions, affecting the accuracy of the calculation results. Therefore, it is necessary to control the adjacent element size change rate within a reasonable range. For example, it is stipulated that the adjacent element size change rate cannot exceed a certain percentage to ensure a smooth transition of the mesh.

[0137] Optionally, adaptive refinement of the finite element mesh elements includes: according to the element type of the finite element mesh elements, using the bisection method, quartering method or octree method to perform adaptive refinement on the finite element mesh elements.

[0138] It can be understood that for each finite element mesh element in the finite element mesh that meets the mesh refinement accuracy in the modeling accuracy, the corresponding element accuracy index meets the element accuracy threshold.

[0139] After the above adaptive refinement process, for each finite element mesh element in the finite element mesh that meets the mesh refinement accuracy requirements in the modeling accuracy, the corresponding element accuracy index will meet the element accuracy threshold. Such a mesh can more accurately describe the distribution of the physical field and improve the calculation accuracy and reliability of the finite element analysis.

[0140] In an exemplary embodiment, as Figure 3 shown, adjusting the fixed time step to obtain a fixed time step that meets the step accuracy in the modeling accuracy includes:

[0141] S301, based on the preliminary calculation results, calculate the change rates of various physical quantities in the temperature field, stress field and fluid field within each time step. The change rates of various physical quantities include the temperature change rate, stress change rate and fluid flow velocity change rate.

[0142] Optionally, the temperature field describes the temperature distribution within an object, the stress field reflects the stress state inside the object, and the fluid field depicts the flow characteristics of the fluid. By calculating the change rates of these physical quantities within each time step, the rate of change of the physical system in the time dimension can be understood.

[0143] In S302, the stability criterion in finite element analysis is adopted to evaluate the computational stability at a fixed time step, and a stability evaluation result is obtained.

[0144] Optionally, in finite element analysis, the computational stability is a key issue. If the time step is not properly selected, it may lead to unstable computational results, such as numerical oscillations, divergence, etc., making the simulation results meaningless.

[0145] Among them, the stability criterion is a series of rules or conditions established based on the theory of the finite element method and the characteristics of physical problems, used to judge whether the calculation is stable at a given time step. By applying these criteria to evaluate the calculation at the current fixed time step, it can be determined whether the calculation can proceed stably.

[0146] In S303, if the change rate of at least one physical quantity does not meet the set change rate threshold, or the stability evaluation result does not meet the stability condition, then the fixed time step is adjusted to obtain a fixed time step that meets the step accuracy in the modeling accuracy.

[0147] Among them, the change rate threshold is a set of pre-set standard values used to measure the reasonable range of physical quantity changes. If the change rate of a certain physical quantity exceeds the corresponding threshold, it means that the physical quantity changes too violently within the current time step, which may be due to too large a time step setting, resulting in the inability to accurately capture the changes in the physical quantity. For example, if the temperature change rate threshold is set to, and the calculated temperature change rate at a certain point is, exceeding the threshold, the time step needs to be adjusted.

[0148] Determined by the stability criterion, it is the standard for judging whether the calculation is stable. If the stability evaluation result does not meet these conditions, it means that the calculation at the current time step is unstable and may produce incorrect results, and the time step also needs to be adjusted.

[0149] By continuously adjusting the time step, the change rate of the physical quantity meets the change rate threshold, and the calculation meets the stability condition. Finally, the obtained fixed time step can meet the step accuracy requirements in the modeling accuracy, thus ensuring the accuracy and reliability of the finite element simulation results.

[0150] Optionally, adjusting the fixed time step includes: if the change rate of at least one physical quantity exceeds the set change rate threshold, or the stability evaluation result does not meet the stability condition, then it is determined that the fixed time step is to be reduced.

[0151] Optionally, when the rate of change of a physical quantity (such as temperature, stress, fluid flow rate, etc.) within a time step exceeds a pre-set threshold, it means that the physical quantity changes too violently within the current time step. This may be because the time step size is set too large, making it impossible for the finite element analysis to accurately capture the rapid changes of the physical quantity, resulting in inaccurate calculation results. For example, in a heat conduction problem, if the temperature change rate exceeds the threshold, it may cause a large deviation in the simulation of the temperature distribution.

[0152] In finite element analysis, the stability of the calculation is crucial. If the stability evaluation result shows that the calculation under the current time step size is unstable, problems such as numerical oscillation and divergence may occur, making the simulation result meaningless. For example, in a fluid dynamics simulation, unstable calculation may cause unreasonable fluctuations in the flow pattern of the fluid.

[0153] In the above two cases, by reducing the fixed time step size, the calculation can more carefully track the changes of the physical quantity, improving the accuracy and stability of the calculation.

[0154] If it is determined that the rate of change of each physical quantity is less than the set rate of change threshold, and the stability evaluation result meets the stability condition, then the fixed time step size is increased by the set step increment.

[0155] Optionally, when the rate of change of all physical quantities within a time step is less than the pre-set threshold, it indicates that the changes of the physical quantities are relatively slow within the current time step. This means that the current time step size may be set too conservatively, resulting in low calculation efficiency. For example, in a relatively stable heat conduction process, the temperature changes very slowly. If the time step size is too small, it will increase unnecessary calculation amount.

[0156] If the stability evaluation shows that the calculation under the current time step size is stable, then on the premise of ensuring the calculation stability, the time step size can be appropriately increased. In this case, increasing the fixed time step size by the set step increment can reduce the number of time steps required for the calculation without affecting the calculation accuracy and stability, thereby improving the calculation efficiency.

[0157] In an exemplary embodiment, the initial control variables include the PWM duty cycle, the motor speed, and the worm and worm gear transmission ratio.

[0158] Correspondingly, with the goal of minimizing the angle control error of the electro-control valve and maximizing the sealing performance of the electro-control valve, taking the initial control variables of the electro-control valve as the starting point of the optimization design, the optimized control variables of the electro-control valve are determined, including:

[0159] Aiming to minimize the angle control error of the electro-control valve and maximize its sealing performance, under the energy consumption constraint and response time constraint of the electro-control valve, starting from the initial control variables of the electro-control valve as the optimization design starting point, the optimized control variables of the electro-control valve are determined.

[0160] Optionally, aiming to minimize the angle control error of the electro-control valve and maximize its sealing performance, the penalty function method is used to handle the energy consumption constraint and response time constraint, and a penalty term proportional to the degree of constraint violation is added; and, starting from the initial control variables of the electro-control valve as the optimization design starting point, the optimized control variables of the electro-control valve are determined.

[0161] Among them, the PWM duty cycle: Pulse Width Modulation (PWM) is a commonly used control technique, and the duty cycle represents the ratio of the high-level duration in the pulse signal to the entire cycle. In the control of the electro-control valve, by adjusting the PWM duty cycle, the average power supplied to the electro-control valve can be changed, thereby controlling its motion state.

[0162] Motor speed: The motor is the power source of the electro-control valve, and the motor speed directly affects the motion speed of the electro-control valve. Different application scenarios may require different motor speeds to achieve precise control.

[0163] The transmission ratio of the worm and worm gear: The worm and worm gear transmission is a common mechanical transmission method, and the transmission ratio represents the ratio of the rotational speeds of the worm gear and the worm. A reasonable transmission ratio can achieve force amplification or speed adjustment to meet the working requirements of the electro-control valve.

[0164] Among them, the initial control variables of the electro-control valve are determined according to the design specifications and historical operation data of the electro-control valve. The initial control variables of the electro-control valve are determined according to the design specifications and historical operation data of the electro-control valve. The design specifications stipulate the basic performance and working range of the electro-control valve, such as the rated power of the motor, the transmission efficiency of the worm and worm gear, etc. The historical operation data reflects the performance of the electro-control valve in actual work. By analyzing these data, the optimal control variable range of the electro-control valve under different working conditions can be understood, thereby determining the initial control variables.

[0165] Optionally, aiming to minimize the angle control error of the electro-control valve and maximize its sealing performance. The angle control error refers to the difference between the actual rotation angle of the electro-control valve and the desired angle. The smaller the error, the higher the control accuracy of the electro-control valve. The sealing performance is crucial for some electro-control valves that need to prevent medium leakage. Good sealing performance can ensure the reliability and safety of the electro-control valve.

[0166] Among them, the energy consumption constraint: The electric control valve consumes energy during operation. To improve energy utilization efficiency, it is necessary to limit the energy consumption. For example, the maximum energy consumption of the electric control valve when completing a specific task is specified to avoid unnecessary energy waste. Response time constraint: The response time refers to the time required for the electric control valve to reach the desired state from receiving the control signal. In some applications with high real-time requirements, it is necessary to constrain the response time of the electric control valve to ensure that it can respond to control instructions in a timely and accurate manner.

[0167] Optionally, the penalty function method is used to handle the energy consumption constraint and the response time constraint. The penalty function method is a commonly used optimization algorithm that adds a penalty term proportional to the degree of constraint violation to the objective function. When the control variable does not satisfy the constraint condition, the penalty term will increase the value of the objective function, thereby guiding the optimization process towards the direction of satisfying the constraint condition.

[0168] Taking the initial control variable of the electric control valve as the starting point of the optimization design, by continuously adjusting the control variable, the optimal control variable that satisfies the optimization objective and constraint conditions is gradually found, that is, the optimized control variable of the electric control valve. This optimization method starting from the initial control variable can utilize existing design and operation experience to accelerate the convergence speed of the optimization process.

[0169] It should be understood that although the steps in the flowcharts involved in the above embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps in other steps.

[0170] Based on the same inventive concept, the embodiments of the present application also provide an electric control valve control variable design device for implementing the above-mentioned electric control valve control variable design method. The implementation solutions provided by this device to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the electric control valve control variable design device provided below can refer to the limitations on the electric control valve control variable design method in the above text, and will not be repeated here.

[0171] In an exemplary embodiment, as Figure 4 shown, an electric control valve control variable design device is provided, including:

[0172] The model construction module 41 is used to construct a coupling model of the electronic control valve by using the finite element analysis method. The coupling model is used to characterize the coupling relationship between the temperature field, stress field and fluid field inside the electronic control valve;

[0173] The parameter optimization module 42 is used to determine the optimized control variables of the electronic control valve with the goal of minimizing the angle control error of the electronic control valve and maximizing the sealing performance of the electronic control valve, starting from the initial control variables of the electronic control valve as the starting point of the optimization design;

[0174] The verification module 43 is used to input the optimized control variables of the electronic control valve into the coupling model for verification to obtain the performance parameters of the coupling model under the optimized control variables. The performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters and sealing performance parameters;

[0175] The variable design module 44 is used to, when it is determined that the performance parameters meet the set execution conditions, use the optimized control variables of the electronic control valve as the target control variables of the electronic control valve.

[0176] Each module in the above control variable design device of the electronic control valve can be implemented in whole or in part by software, hardware and their combination. The above modules can be embedded in or independent of the processor in the electronic control valve in the form of hardware, or stored in the memory in the electronic control valve in the form of software, so as to facilitate the processor to call and execute the operations corresponding to the above modules.

[0177] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0178] Use the finite element analysis method to construct a coupling model of the electronic control valve. The coupling model is used to characterize the coupling relationship between the temperature field, stress field and fluid field inside the electronic control valve;

[0179] With the goal of minimizing the angle control error of the electronic control valve and maximizing the sealing performance of the electronic control valve, starting from the initial control variables of the electronic control valve as the starting point of the optimization design, determine the optimized control variables of the electronic control valve;

[0180] Input the optimized control variables of the electronic control valve into the coupling model for verification to obtain the performance parameters of the coupling model under the optimized control variables. The performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters and sealing performance parameters;

[0181] When it is determined that the performance parameters meet the set execution conditions, use the optimized control variables of the electronic control valve as the target control variables of the electronic control valve.

[0182] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0183] Adopt the finite element analysis method to construct a coupling model of the electronic control valve. The coupling model is used to characterize the coupling relationship between the temperature field, stress field and fluid field inside the electronic control valve;

[0184] Taking the minimization of the angle control error of the electronic control valve and the maximization of the sealing performance of the electronic control valve as the goal, and taking the initial control variables of the electronic control valve as the starting point of the optimization design, determine the optimized control variables of the electronic control valve;

[0185] Input the optimized control variables of the electronic control valve into the coupling model for verification, and obtain the performance parameters of the coupling model under the optimized control variables; the performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters and sealing performance parameters;

[0186] When it is determined that the performance parameters meet the set execution conditions, take the optimized control variables of the electronic control valve as the target control variables of the electronic control valve.

[0187] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the following steps are implemented:

[0188] Adopt the finite element analysis method to construct a coupling model of the electronic control valve. The coupling model is used to characterize the coupling relationship between the temperature field, stress field and fluid field inside the electronic control valve;

[0189] Taking the minimization of the angle control error of the electronic control valve and the maximization of the sealing performance of the electronic control valve as the goal, and taking the initial control variables of the electronic control valve as the starting point of the optimization design, determine the optimized control variables of the electronic control valve;

[0190] Input the optimized control variables of the electronic control valve into the coupling model for verification, and obtain the performance parameters of the coupling model under the optimized control variables; the performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters and sealing performance parameters;

[0191] When it is determined that the performance parameters meet the set execution conditions, take the optimized control variables of the electronic control valve as the target control variables of the electronic control valve.

[0192] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0193] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in the present application.

[0194] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A control variable design method for an electric control valve, characterized in that: Applied to a computer device, the method comprises: A finite element analysis method is used to construct a coupling model of the electric control valve, wherein the coupling model is used to characterize the coupling relationship between the temperature field, the stress field and the fluid field inside the electric control valve; With the goal of minimizing the angle control error of the electric control valve and maximizing the sealing performance of the electric control valve, the initial control variables of the electric control valve are used as the starting point of the optimization design to determine the optimized control variables of the electric control valve; Inputting the optimized control variables of the electric control valve into the coupling model for verification, and obtaining the performance parameters of the coupling model under the optimized control variables; the performance parameters include temperature field performance parameters, stress field performance parameters, fluid field distribution performance parameters, angle control accuracy parameters and sealing performance parameters; When it is determined that the performance parameter satisfies the set execution condition, the optimized control variable of the electric control valve is used as the target control variable of the electric control valve.

2. The method according to claim 1, characterized in that The finite element analysis method is used to construct the coupling model of the electric control valve, including: Performing preliminary geometric modeling on the electric control valve to obtain a three-dimensional geometric model; Performing initial meshing of the three-dimensional geometric model using a uniform meshing strategy to generate a plurality of finite element meshes, and obtaining an initial fixed time step corresponding to the three-dimensional geometric model; Based on the multiple finite element grids, defining the physical properties and boundary conditions of the temperature field, stress field and fluid field inside the electric control valve; Using finite element analysis software, solving the coupled equations of the temperature field, stress field and fluid field, and obtaining preliminary calculation results of multiple finite element grids at the fixed time step; According to the preliminary calculation results, each finite element mesh is adaptively refined to obtain each finite element mesh that satisfies the mesh refinement accuracy in the modeling accuracy; According to the preliminary calculation result, the fixed time step is adjusted to obtain a fixed time step that satisfies the step accuracy in the modeling accuracy; The coupling model of the electric control valve is constructed according to each finite element grid that meets the grid refinement accuracy in the modeling accuracy and the fixed time step that meets the step accuracy in the modeling accuracy.

3. The method according to claim 2, characterized in that The method of adaptively refining each finite element mesh according to the preliminary calculation results to obtain each finite element mesh that satisfies the mesh refinement accuracy in the modeling accuracy includes: For each finite element grid, according to the preliminary calculation results, the physical quantity gradients of each physical quantity in the temperature field, stress field and fluid field in each finite element grid unit in the finite element grid are calculated, and the energy error of each finite element grid unit is estimated by using the energy norm method to obtain the energy error value of each finite element grid unit; For each finite element mesh unit, marking the finite element mesh unit whose physical quantity gradient exceeds the gradient threshold corresponding to the physical quantity as the first unit to be refined; Marking the finite element mesh unit whose energy error value exceeds the energy error threshold as the second unit to be refined; The finite element mesh units marked as the first units to be refined and the second units to be refined are adaptively refined to obtain the finite element mesh that satisfies the mesh refinement accuracy in the modeling accuracy.

4. The method according to claim 3, characterized in that The step of adaptively refining the finite element mesh units marked as the first unit to be refined and the second unit to be refined to obtain the finite element mesh that satisfies the mesh refinement accuracy in the modeling accuracy includes: For each finite element mesh unit marked as the first unit to be refined and marked as the second unit to be refined, the finite element mesh unit is adaptively refined until a unit accuracy index corresponding to the refined finite element mesh unit meets a unit accuracy threshold; The unit accuracy index includes the upper limit of unit size, unit shape quality index and adjacent unit size change rate; The unit accuracy index corresponding to each finite element mesh unit in the finite element mesh that meets the mesh refinement accuracy in the modeling accuracy meets the unit accuracy threshold.

5. The method according to claim 4, characterized in that The adaptively refining the finite element mesh unit comprises: According to the unit type of the finite element mesh unit, the finite element mesh unit is adaptively refined by using a bisection method, a quartering method or an octave method.

6. The method according to claim 2, characterized in that The step of adjusting the fixed time step to obtain a fixed time step that satisfies the step accuracy in the modeling accuracy includes: Based on the preliminary calculation results, calculating the change rate of each physical quantity in the temperature field, stress field and fluid field in each time step, wherein the change rate of each physical quantity includes the temperature change rate, stress change rate and fluid flow rate change rate; Using the stability criterion in the finite element analysis, the calculation stability under the fixed time step is evaluated to obtain a stability evaluation result; If there is at least one physical quantity whose rate of change does not meet the set rate of change threshold, or the stability evaluation result does not meet the stability condition, the fixed time step is adjusted to obtain a fixed time step that meets the step accuracy in the modeling accuracy.

7. The method according to claim 6, characterized in that The adjusting the fixed time step comprises: If there is a change rate of at least one physical quantity that exceeds the set change rate threshold, or the stability evaluation result does not meet the stability condition, then determining to reduce the fixed time step; If it is determined that the change rates of each physical quantity are less than the set change rate threshold, and the stability evaluation result satisfies the stability condition, the fixed time step is increased by the set step increment.

8. The method according to claim 1, characterized in that The initial control variables include PWM duty cycle, motor speed and worm gear ratio; Accordingly, the method aims to minimize the angle control error of the electric control valve and maximize the sealing performance of the electric control valve, takes the initial control variables of the electric control valve as the starting point of the optimization design, and determines the optimized control variables of the electric control valve, including: The goal is to minimize the angle control error of the electric control valve and maximize the sealing performance of the electric control valve. Under the energy consumption constraints and response time constraints of the electric control valve, the initial control variables of the electric control valve are used as the starting point of the optimization design to determine the optimized control variables of the electric control valve.

9. The method according to claim 8, characterized in that The method aims to minimize the angle control error of the electric control valve and maximize the sealing performance of the electric control valve, and under the energy consumption constraint and response time constraint of the electric control valve, takes the initial control variables of the electric control valve as the starting point of the optimization design, and determines the optimized control variables of the electric control valve, including: With the goal of minimizing the angle control error of the electric control valve and maximizing the sealing performance of the electric control valve, a penalty function method is used to process energy consumption constraints and response time constraints, and a penalty term proportional to the degree of constraint violation is added; and, The initial control variables of the electric control valve are used as the starting point of the optimization design to determine the optimized control variables of the electric control valve.

10. The method according to claim 8, characterized in that The initial control variable of the electric control valve is determined according to the design specification and historical operation data of the electric control valve.

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