A method for optimizing the design of ejector structure

Abstract

The present application belongs to the technical field of ejectors, and specifically relates to an ejector structure optimization design method, comprising the following steps: Step 1: Determine the design variables of the ejector and construct an ejector primitive model with geometric constraints; Step 2: Set the value range of each design variable and arbitrarily select a parameter within the value range to form a set of design variable matrices to construct a new ejector model; Step 3: Establish an optimization model for the design variable matrix based on performance indicators; Step 4: Repeat the process of Steps 2 and 3 until the optimal design variable matrix is ​​obtained; Step 5: Establish a parameter boundary optimization model for the design variables and determine whether the value range of the design variables needs to be updated until the determination result is that no update is required and the optimal ejector structural parameters are obtained. The present application uses a boundary-breaking algorithm to find the optimal parameter values ​​of the ejector during the assignment process, and has the beneficial effect of breaking through boundary restrictions, thereby maximizing the performance of the ejector.

Description

Technical Field

[0001] The present invention belongs to the technical field of ejectors, and in particular, relates to a method for optimizing the design of ejector structures. Background Art

[0002] The ejector is a component that fully utilizes the primary fluid to drive the system's working medium circulation. It boasts advantages such as compactness, lightweight, and zero parasitic power. In recent years, it has been widely used in fuel cell systems. Due to the high standards for operating condition control in fuel cell systems, the ejector structure must be optimally designed.

[0003] Existing ejector structure optimization methods, such as patent CN116541984A, which discloses an ejector structure optimization method based on the NSGA-II algorithm; patent CN116070369A, which discloses an ejector structure optimization method based on a particle swarm algorithm; and patent CN116186923A, which discloses an ejector structure optimization method based on a response surface algorithm, rely primarily on well-established optimization algorithms. These algorithms require optimization within given boundary parameters and cannot exceed them. Consequently, the ejector performance achieved using these methods is suboptimal. Therefore, a method for optimizing ejector structure design that can address these existing issues is needed. Summary of the Invention

[0004] In response to the defects of the existing technology, the present invention proposes an ejector structure optimization design method, which adopts a boundary-breaking algorithm to find the optimal parameter values ​​of the ejector during the assignment process, and has the beneficial effect of breaking through the boundary limitations, thereby maximizing the performance of the ejector.

[0005] In order to achieve the above technical objectives, the present invention will adopt the following technical solutions:

[0006] A method for optimizing the design of an ejector structure, comprising the following steps:

[0007] Step 1: Determine the design variables of the ejector and build an ejector primitive model with geometric constraints based on the design variables.

[0008] Step 2: Set the value range of each design variable under the original ejector model, arbitrarily select a parameter within the value range of each design variable, form the design variables of the selected parameter into a set of design variable matrices, and construct a new ejector model based on the design variable matrix;

[0009] Step 3: Analyze the performance of the ejector model constructed in step 2 and define performance indicators. Based on the performance indicators, establish the objective function and optimization model of the design variable matrix;

[0010] Step 4: Repeat the process of steps 2 and 3, and analyze the design variable matrix in step 2 through the objective function and optimization model until the optimal design variable matrix is ​​obtained;

[0011] Step 5: Obtain the optimal parameters under each design variable through the optimal design variable matrix, establish the parameter boundary optimization model of the design variables, and determine whether the value range of the design variables needs to be updated. If no update is required, the optimal design variable matrix obtained in step 4 is the optimal ejector structural parameters. If update is required, update the value range of the design variables in step 2, and loop the updated value range of the design variables through steps 3 to 5 until the result is determined to be unnecessary to update and the optimal ejector structural parameters are obtained, thus completing the ejector structural optimization.

[0012] Furthermore, step 1 specifically includes:

[0013] Step 1.1: The ejector is divided into n design variables according to the structural segment size of the original model. The multiple design variables are represented by P1, P2, P3, ... P n express;

[0014] Step 1.2: Set geometric constraints between the line segments of the ejector model to ensure that the geometric relationships between the line segments remain unchanged when the sizes of the line segments of the ejector model change.

[0015] Furthermore, step 2 specifically includes:

[0016] Step 2.1: Set the value range of each design variable of the original ejector model. The value range of the i-th design variable is [Min i ,Max i ], where Min i and Max i They represent the minimum and maximum values ​​of the value range of the i-th design variable respectively;

[0017] Step 2.2: In step 2.1, select any parameters within the range of each design variable to form a set of design variable matrices, and transform [P1, P2, P3, ... P i ,...P n ]0 as the initialization matrix, where P1-P n Respectively represent any parameters selected within the value range of each design variable, P i represents the parameter selected within the value range of the i-th design variable;

[0018] Step 2.3: Based on the initialization matrix in step 2.2, construct the ejector model under the initialization matrix using 3D engineering drawing software.

[0019] Furthermore, step 3 specifically includes:

[0020] Step 3.1: Analyze the performance of the ejector model constructed in step 2.3 using mesh pre-processing software and finite element analysis software. The performance indicators include at least the ejection ratio ER. j and secondary flow mass flow rate MFR j , ER j and MFR j represent the ejection ratio and secondary flow mass flow rate of the ejector corresponding to the jth group of design variable matrices;

[0021] Step 3.2: Based on step 3.1, establish the objective function used in the optimization model of the design variable matrix. The objective function f con Determined by the following formula:

[0022] f con =ER j α1+MFR j α2

[0023] Where: ER j represents the ejection ratio; α1 represents the weight of the ejection ratio; MFR j represents the secondary flow mass flow rate; α2 represents the weight of the secondary flow mass flow rate.

[0024] Furthermore, step 4 specifically includes:

[0025] Step 4.1: Repeat the process in Step 2. Utilize the macro commands of the 3D engineering drawing software. Write macro code using the Visual Basic editor. Use a loop structure to iterate over all design variables. Each iteration generates a set of design variable matrices, and then construct the ejector model for each set of design variable matrices.

[0026] Step 4.2: Each time a set of ejector models under the design variable matrix is ​​constructed in step 4.1, the optimization model is iterated synchronously once, with the objective function f con As an evaluation index of the iterative process of the optimization algorithm, the optimization algorithm is based on the f of each iteration. con The value of the design variable matrix [P1, P2, P3, ... P i ,...P n ] j ;

[0027] Step 4.3: Based on the iterative results of the optimization model in step 4.2, determine whether it is optimal. If the judgment result is not, then re-determine the new design variable matrix [P1, P2, P3, ... P i ,...P n ] j+1 ; If the judgment result is yes, mark the current design variable matrix [P1, P2, P3, ... Pi ,...P n ] j Represents the current optimal parameter matrix

[0028] Furthermore, step 5 specifically includes:

[0029] Step 5.1: Based on step 4.3, the optimal parameters for each design variable are The parameter boundary optimization model of the i-th design variable is determined by the following formula:

[0030]

[0031] Where: is the optimal parameter of the i-th design variable in the previous cycle iteration; Min i and Max i They represent the minimum and maximum boundary parameters of the i-th design variable value range in the current loop iteration; θ min and θ max Respectively represent the tolerable interval coefficients of the algorithm breaking through the lower and upper limits of the boundary parameters;

[0032] Step 5.2: Determine whether the calculation result of the parameter boundary optimization model F of the design variable is greater than 0. If the calculation result of F is greater than 0, return to step 2 and update the value range of the i-th design variable to [Min i ,Max i ]for If the result of F is 0, no update is required, and the optimal parameter matrix That is the optimal ejector structural parameters after optimization.

[0033] Furthermore, in step 5.2 The update method is as follows:

[0034] like but otherwise like but otherwise

[0035] Where: and Respectively represent the minimum and maximum values ​​of the boundary parameters of the updated i-th design variable range; Min i and Min i They represent the minimum and maximum boundary parameters of the value range of the i-th design variable in the current loop iteration.

[0036] According to the above technical solution, compared with the prior art, the present invention has the following advantages:

[0037] The present invention employs a boundary-breaking algorithm to find optimal parameter values ​​for an ejector during the assignment process, achieving the beneficial effect of breaking through boundary limitations and maximizing ejector performance. This invention is applicable not only to ejectors; the ejector in this embodiment is merely an example. The structural design and parameter optimization methods described are equally applicable to other structural components, and the optimized object should not be limited. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 1 is a flow chart of an ejector structure optimization design method according to an embodiment of the present invention;

[0039] Figure 2 2. It is a schematic diagram of the three-dimensional structure of the ejector according to an embodiment of the present invention;

[0040] Figure 3 Schematic diagram of design variables of the ejector according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the technical solution of the present application, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0042] The terms "up", "down", "left", "right", "front", and "back" in this application are based on the positional relationships shown in the accompanying drawings. The corresponding positional relationships may vary depending on the drawings, and should not be construed as limiting the scope of protection.

[0043] In this application, the terms "installed," "connected," "connected," "connected," "fixed," etc. should be understood in a broad sense. For example, they can refer to fixed connection, detachable connection, integral connection, mechanical connection, electrical connection, or mutual communication. They can also be directly connected or indirectly connected through an intermediate medium. They can also refer to internal communication between two components or interaction between two components. For those skilled in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0044] See the instructions attached Figure 1 The present invention records a method for optimizing the design of ejector structure, which adopts a boundary-breaking algorithm to find the optimal parameter values ​​of the ejector during the assignment process, and has the beneficial effect of breaking through the boundary limitations, thereby maximizing the performance of the ejector.

[0045] Specifically, the ejector structure optimization design method includes the following steps:

[0046] Step 1: Determine the design variables of the ejector and build an ejector primitive model with geometric constraints based on the design variables.

[0047] Step 1.1: The ejector is divided into n design variables according to the structural segment size of the original model. The multiple design variables are represented by P1, P2, P3, ... P n express.

[0048] Step 1.2: Set geometric constraints between the line segments of the ejector model to ensure that the geometric relationships between the line segments remain unchanged when the sizes of the line segments of the ejector model change.

[0049] The original model of the ejector is constructed using three-dimensional engineering drawing software, such as Solidworks software.

[0050] Instructions attached Figure 2-3 Taking the ejector of this embodiment as an example, the ejector of this embodiment is divided into 22 design variables, and the 22 design variables are defined as P1, P2, P3, ... P 22 The 22 design variables include primary inlet diameter P1, primary flow pipe length P2, secondary flow pipe center position P3, secondary flow pipe length P4, secondary flow pipe diameter P5, primary flow chamber length P6, distance from secondary flow into chamber P7, compression section length P8, nozzle position P9, nozzle length P 10 , mixing section length P 11 , Diffuser length P 12 , outlet pipe length P 13 , outlet pipe diameter P 14 , Diffuser section outlet diameter P 15 , mixing section diameter P 16 , nozzle wall thickness P 17 , nozzle diameter P 18 , secondary flow chamber length P 19 , secondary flow chamber size P 20 , secondary flow chamber wall thickness P 21 and the primary flow chamber radius P 22 .

[0051] The geometric constraints of the 22 design variables of the ejector are as follows:

[0052] The common points of line segments are constrained to coincide with each other; P1 and P2, P 13 With P 14 Apply a "vertical" constraint relationship; P5 and P 19 Apply a "parallel" constraint.

[0053] Those skilled in the art should understand that the above-mentioned constraint relationships between the ejector model structure and the 22 design variables are merely illustrative. Specifically, corresponding constraint relationships can be applied using points, lines, and surfaces based on the actual geometric topology to ensure that changes in the design variables do not affect the geometric structure relationship of the original model.

[0054] Step 2: Set the value range of each design variable under the original ejector model, arbitrarily select a parameter within the value range of each design variable, organize the design variables of the selected parameters into a set of design variable matrices, and construct a new ejector model based on the design variable matrix.

[0055] Specifically, step 2 includes the following methods:

[0056] Step 2.1: Set the value range of each design variable of the original ejector model. The value range of the i-th design variable is [Min i ,Max i ], where Min i and Max i They represent the minimum and maximum values ​​of the value range of the i-th design variable respectively.

[0057] Step 2.2: In step 2.1, select any parameters within the range of each design variable to form a set of design variable matrices, and transform [P1, P2, P3, ... P i ,...P n ]0 as the initialization matrix, where P1-P n Respectively represent any parameters selected within the value range of each design variable, P i Represents the parameters selected within the value range of the i-th design variable.

[0058] In one embodiment, taking the i-th design variable as an example, the method for initializing the matrix value can be to take the median value of the boundary parameter within the value range of the i-th variable, that is, You can also find it in [Min i ,Max i ], the random values ​​can be selected from the default values ​​of the design variables when the original model of the ejector is constructed by the 3D engineering drawing software, or the design variable parameters can be randomly generated by third-party software such as Excel and imported with the help of macro commands or imported into the 3D engineering drawing software through the configuration manager function.

[0059] Step 2.3: Based on the initialization matrix in step 2.2, construct the ejector model under the initialization matrix using 3D engineering drawing software.

[0060] Step 3: Analyze the performance of the ejector model constructed in step 2 and define performance indicators. Based on the performance indicators, establish an optimization model for the design variable matrix.

[0061] Specifically, step 3 includes the following methods:

[0062] Step 3.1: Analyze the performance of the ejector model constructed in step 2.3 using mesh pre-processing software and finite element analysis software. The performance indicators include at least the ejection ratio ER. j and secondary flow mass flow rate MFR j , ER j and MFR j They represent the ejection ratio and secondary flow mass flow rate of the ejector corresponding to the jth group of design variable matrices.

[0063] The mesh pre-processing software is used to establish the mesh model of the ejector. In this embodiment, ICEM or Hypermesh is used as the mesh pre-processing software. The finite element analysis software is used to analyze the performance index of the established mesh model. In this embodiment, Fluent or Starccm is used as the finite element analysis software.

[0064] Step 3.2: Based on step 3.1, the objective function formula used in the optimization model of the design variable matrix is ​​established. The objective function f of the optimization model of the design variable matrix is con Determined by the following formula:

[0065] f con =ER j α1+MFR j α2

[0066] Where: ER j represents the ejection ratio; α1 represents the weight of the ejection ratio; MFR j represents the secondary flow mass flow rate; α2 represents the weight of the secondary flow mass flow rate.

[0067] Preferably, during the ejector structure optimization process, α1+α2=1.

[0068] It should be noted that the performance indicators and objective functions in the optimization model of the design variable matrix are not limited to the ejection ratio ER. j and secondary flow mass flow rate MFR j , and other performance parameters can also be included. Therefore, the objective function formula of the design variable matrix can add other performance parameters to participate in the calculation based on step 3.2.

[0069] Step 4: Repeat the process of steps 2 and 3, and analyze the design variable matrix in step 2 through the optimization model until the optimal design variable matrix is ​​obtained.

[0070] Specifically, step 4 includes the following methods:

[0071] Step 4.1: Repeat the process of step 2, using the macro commands of the 3D engineering drawing software. By using the Visual Basic editor to write macro code, use a loop structure to traverse all design variables, generate a set of design variable matrices each time, and then construct the ejector model under each set of design variable matrices.

[0072] In other embodiments, the following method may be used to construct the ejector model under each set of design variable matrices:

[0073] Method 1: Use the "Configuration Table" function in the 3D engineering drawing software to perform batch modification and assignment, such as entering the "Configuration Manager" in the feature tree in Solidworks, and configuring properties for all design variables to achieve assignment; Method 2: Integrate other software with batch operation functions, such as using the Solidworks module in the iSight software to integrate the sketch file of the ejector, and import the design variable matrix in iSight; Method 3: Directly enter the 3D drawing software manually, modify each design variable one by one, or use programming language instead of manual drive to complete it.

[0074] Step 4.2: Each time a set of ejector models under the design variable matrix is ​​constructed in step 4.1, the optimization model is iterated synchronously once, with the objective function f con As an evaluation index of the iterative process of the optimization algorithm, the optimization algorithm is based on the f of each iteration. con The value of the design variable matrix [P1, P2, P3, ... P i ,...P n ] j .

[0075] The method for determining the specific value of the design variable matrix for the next iteration depends on the optimization algorithm used by the optimization model. Taking the ant colony optimization algorithm as an example, in the optimization process, the method for determining the design variable matrix for the next iteration is no longer based on the heuristic function and heuristic factor, but on the objective function f in this embodiment. con As the heuristic function at each iteration to update the pheromone.

[0076] The optimization algorithm for the design variable matrix adopted in this embodiment uses the objective function proposed in the present invention to judge the results in each iteration process. Those skilled in the art should understand that the optimization algorithm for the design variable matrix can adopt any algorithm with optimization capabilities, such as gradient descent, ant colony algorithm, particle swarm algorithm and dragonfly algorithm, and can also adopt other mathematical methods or manual observation and judgment.

[0077] Step 4.3: Based on the iterative results of the optimization model in step 4.2, determine whether it is optimal. If the judgment result is not, then re-determine the new design variable matrix [P1, P2, P3, ... P i ,...P n ] j+1 ; If the judgment result is yes, mark the current design variable matrix [P1, P2, P3, ... P i ,...P n ] j Represents the current optimal parameter matrix

[0078] The criterion for the optimization model is the objective function f con The higher the value of f, the better the result. con Lower values ​​result in worse results.

[0079] Step 5: Obtain the optimal parameters under each design variable through the optimal design variable matrix, establish the parameter boundary optimization model of the design variables, and determine whether the value range of the design variables needs to be updated. If no update is required, the optimal design variable matrix obtained in step 4 is the optimal ejector structural parameters. If update is required, update the value range of the design variables in step 2, and loop the updated value range of the design variables through steps 3 to 5 until the result is determined to be unnecessary to update and the optimal ejector structural parameters are obtained, thus completing the ejector structural optimization.

[0080] Specifically, step 5 includes the following methods:

[0081] Step 5.1: Based on step 4.3, the optimal parameters for each design variable are The parameter boundary optimization model of the i-th design variable is determined by the following formula:

[0082]

[0083] Where: is the optimal parameter of the i-th design variable in the previous cycle iteration; Min i and Max i They represent the minimum and maximum boundary parameters of the i-th design variable value range in the current loop iteration; θ min and θ max Respectively represent the tolerable interval coefficients of the algorithm breaking through the lower and upper limits of the boundary parameters. Preferably, θ min =0.1,θ max =0.2.

[0084] The parameter boundary optimization model of the design variables in this embodiment adopts a coupled optimization tool. Those skilled in the art should understand that the coupled optimization tool can be any algorithm with optimization capability, or other mathematical methods or human observation and judgment.

[0085] Step 5.2: Determine whether the calculation result of the parameter boundary optimization model F of the design variable is greater than 0. If the calculation result of F is greater than 0, return to step 2 and update the value range of the i-th design variable to [Min i ,Max i ]for If the result of F is 0, no update is required, and the optimal parameter matrix That is the optimal ejector structural parameters after optimization.

[0086] Specifically, The update method is as follows:

[0087] like but otherwise like but otherwise

[0088] Where: and Respectively represent the minimum and maximum values ​​of the boundary parameters of the updated i-th design variable range; Min i and Min i They represent the minimum and maximum boundary parameters of the value range of the i-th design variable in the current loop iteration.

[0089] The present invention is not only applicable to ejectors. The ejector in this embodiment is only an example. The structural design method and parameter optimization method described are also applicable to other structural parts, and the optimized objects should not be limited.

[0090] The above is only an embodiment of the present invention, and common sense such as the specific structure and characteristics of the scheme are not described in detail here. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claim involved.

Claims

1. A method for optimizing the design of ejector structure, characterized in that: The ejector structure optimization design method includes the following steps: Step 1: Determine the design variables of the ejector and build an ejector primitive model with geometric constraints based on the design variables. Step 2: Set the value range of each design variable under the original ejector model, arbitrarily select a parameter within the value range of each design variable, form the design variables of the selected parameter into a set of design variable matrices, and construct a new ejector model based on the design variable matrix; Step 3: Analyze the performance of the ejector model constructed in step 2 and define performance indicators. Based on the performance indicators, establish an optimization model for the design variable matrix. Step 3 specifically includes: Step 3.1: Analyze the performance of the ejector model constructed in step 2.3 using mesh pre-processing software and finite element analysis software. The performance indicators include at least the ejection ratio ER. j and secondary flow mass flow rate MFR j , ER j and MFR j represent the ejection ratio and secondary flow mass flow rate of the ejector corresponding to the jth group of design variable matrices; Step 3.2: Based on step 3.1, establish the objective function used in the optimization model of the design variable matrix. The objective function f con Determined by the following formula: f con =ER j ·α1+MFR j ·a2 Where: ER j represents the ejection ratio; α1 represents the weight of the ejection ratio; MFR j represents the secondary flow mass flow rate; α2 represents the weight of the secondary flow mass flow rate; Step 4: Repeat the process of steps 2 and 3, and analyze the design variable matrix in step 2 through the objective function and optimization model until the optimal design variable matrix is ​​obtained; Step 5: Obtain the optimal parameters under each design variable through the optimal design variable matrix, establish the parameter boundary optimization model of the design variables, and determine whether the value range of the design variables needs to be updated. If no update is required, the optimal design variable matrix obtained in step 4 is the optimal ejector structural parameters. If update is required, update the value range of the design variables in step 2, and loop the updated value range of the design variables through steps 3 to 5 until the result is determined to be unnecessary to update and the optimal ejector structural parameters are obtained, thus completing the ejector structural optimization.

2. The ejector structure optimization design method according to claim 1, characterized in that: Step 1 specifically includes: Step 1.1: The ejector is divided into n design variables according to the structural segment size of the original model. The multiple design variables are represented by P1, P2, P3, ... P n express; Step 1.2: Set geometric constraints between the line segments of the ejector model to ensure that the geometric relationships between the line segments remain unchanged when the sizes of the line segments of the ejector model change.

3. The ejector structure optimization design method according to claim 1, characterized in that: Step 2 specifically includes: Step 2.1: Set the value range of each design variable of the original ejector model. The value range of the i-th design variable is [Min i ,Max i ], where Min i and Max i They represent the minimum and maximum values ​​of the value range of the i-th design variable respectively; Step 2.2: In step 2.1, select any parameters within the range of each design variable to form a set of design variable matrices, and transform [P1, P2, P3, ... P i ,...P n ]0 as the initialization matrix, where P1-P n Respectively represent any parameters selected within the value range of each design variable, P i represents the parameter selected within the value range of the i-th design variable; Step 2.3: Based on the initialization matrix in step 2.2, construct the ejector model under the initialization matrix using 3D engineering drawing software.

4. The ejector structure optimization design method according to claim 1, characterized in that: Step 4 specifically includes: Step 4.1: Repeat the process in Step 2. Utilize the macro commands of the 3D engineering drawing software. Write macro code using the Visual Basic editor. Use a loop structure to iterate over all design variables. Each iteration generates a set of design variable matrices, and then construct the ejector model for each set of design variable matrices. Step 4.2: Each time a set of ejector models under the design variable matrix is ​​constructed in step 4.1, the optimization model is iterated synchronously once, with the objective function f con As an evaluation index of the iterative process of the optimization algorithm, the optimization algorithm is based on the f of each iteration. con The value of the design variable matrix [P1, P2, P3, ... P i ,...P n ] j ; Step 4.3: Based on the iterative results of the optimization model in step 4.2, determine whether it is optimal. If the judgment result is not, then re-determine the new design variable matrix [P1, P2, P3, ... P i ,...P n ] j+1 ; If the judgment result is yes, mark the current design variable matrix [P1, P2, P3, ... P i ,...P n ] j Represents the current optimal parameter matrix 5. The ejector structure optimization design method according to claim 1, characterized in that: Step 5 specifically includes: Step 5.1: Based on step 4.3, the optimal parameters for each design variable are The parameter boundary optimization model of the i-th design variable is determined by the following formula: Where: is the optimal parameter of the i-th design variable in the previous cycle iteration; Min i and Max i They represent the minimum and maximum boundary parameters of the i-th design variable value range in the current loop iteration; θ min and θ max Respectively represent the tolerable interval coefficients of the algorithm breaking through the lower and upper limits of the boundary parameters; Step 5.2: Determine whether the calculation result of the parameter boundary optimization model F of the design variable is greater than 0. If the calculation result of F is greater than 0, return to step 2 and update the value range of the i-th design variable to [Min i ,Max i ]for If the result of F is 0, no update is required, and the optimal parameter matrix That is the optimal ejector structural parameters after optimization.

6. The ejector structure optimization design method according to claim 5, characterized in that: Step 5.2 The update method is as follows: like but otherwise like but otherwise Where: and Respectively represent the minimum and maximum values ​​of the boundary parameters of the updated i-th design variable range; Min i and Min i They represent the minimum and maximum values ​​of the boundary parameters of the i-th design variable value range in the current loop iteration.

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