Section parameter optimization method for sealing strip

Abstract

The invention relates to the technical field of part manufacturing, and particularly discloses a section parameter optimization method for a sealing strip, which comprises the following steps of: S1, determining a section design concept of the sealing strip according to a preset requirement, and finishing a primary section outer contour; s2, parameterizing the wall thickness of each part of the section, and establishing a compression load analysis model; s3, establishing a DOE matrix by taking the wall thickness of each part of the section as an input parameter and the compression load of different contact positions as an output parameter, generating permutation and combination of a plurality of input parameters in a numerical value setting range of the parameters, and calculating a result of each combination to obtain a complete DOE matrix; s4, performing response surface analysis by using the established DOE matrix; s5, according to a response surface analysis result, performing optimization by using a multi-optimization target genetic algorithm; and S6, deriving an optimal design point, and completing optimization analysis. By means of the technical scheme, the design efficiency of the sealing strip section parameters can be improved, and meanwhile it is ensured that the product performance is close to the design target value to the maximum extent.

Description

Technical Field

[0001] The invention relates to the technical field of component manufacturing, and in particular to a method for optimizing cross-section parameters of a sealing strip. Background Art

[0002] Sealing strip products are widely used in automobiles to ensure the sealing performance of the car body. When developing new products, the design concept of the sealing strip must be determined first. Since the matching relationship between the sealing strips in different positions (such as door locks and hinge positions) is different, the design requirements of each position (such as compression load) must be met at the same time. The current routine workflow is that the product engineer designs the initial section, which is then handed over to the finite element analysis (FEA) engineer for calculation, and the section is modified according to the analysis results, and the process is repeated. This process often leads to a lot of time waste when faced with strict compression load requirements or insufficient experience of product engineers, especially in the process of communicating results and modifying sections.

[0003] Therefore, an optimization method is urgently needed to improve the design efficiency of the sealing strip cross-sectional parameters while ensuring that the product performance is as close to the design target value as possible. Summary of the invention

[0004] The present invention provides a method for optimizing cross-sectional parameters of a sealing strip, which can improve the design efficiency of the cross-sectional parameters of the sealing strip and ensure that product performance is close to the design target value to the greatest extent.

[0005] In order to solve the above technical problems, this application provides the following technical solutions:

[0006] The cross-section parameter optimization method for sealing strips includes the following contents:

[0007] S1. Determine the design concept of the sealing strip section according to the preset requirements and complete the initial section outline;

[0008] S2. Parameterize the wall thickness at each location of the section, establish a compression load analysis model, complete the compression load analysis of different contact positions between the sheet metal and the sealing strip of the initial section, and set the results as parameters;

[0009] S3. Using the wall thickness at each location of the cross section as the input parameter and the compressive load at different contact positions as the output parameter, the DOE matrix is ​​established using the central composite design method in the preset software, and several permutations and combinations of input parameters are generated within the numerical setting range of the parameters, and the results of each combination are calculated to obtain a complete DOE matrix;

[0010] S4. Use the established DOE matrix to perform response surface analysis;

[0011] S5. Based on the response surface analysis results, a multi-optimization objective genetic algorithm is used for optimization;

[0012] S6. Export the best design point and complete the optimization analysis.

[0013] Furthermore, in step S2, the compression load analysis of each contact position specifically includes:

[0014] S201, inputting material parameters of the constitutive model of the sealing strip material; the sealing strip material is dense rubber and foam rubber;

[0015] S202, establishing a contact relationship between the sheet metal contact position and the sealing strip;

[0016] S203, establishing boundary conditions for the fixing of the bottom of the sealing strip and the displacement of the sheet metal;

[0017] S204, generating a quadrilateral mesh;

[0018] S205. Complete the compression load calculation.

[0019] Further, the contact position includes a door lock and a hinge.

[0020] Further, the step S4 specifically includes:

[0021] S401, select the response surface type as genetic aggregation model;

[0022] S402, select to automatically generate three verification points;

[0023] S403, start response surface analysis;

[0024] S404, observe the compliance index curve. If the scattered points are concentrated on the 45° line, the response surface analysis result is obtained, and jump to step S5; if there are scattered points deviating from the 45° line, set the three generated verification points as optimization points, jump to S403, and re-perform the response surface analysis.

[0025] Further, the step S5 specifically includes:

[0026] S501, select MOGA algorithm;

[0027] S502, specifying optimization objectives and constraints;

[0028] S503, automatically solving using preset software;

[0029] S504, check the optimization results;

[0030] S505. Obtain the optimal design point.

[0031] Further, the specified optimization target is the compression load at the door lock and hinge position.

[0032] This solution uses preset software internal iterations in the cross-section optimization process, which significantly reduces the communication and feedback time between product engineers and finite element analysis (FEA) engineers, thereby improving overall development efficiency. Through a systematic and automated analysis process, the best design solution that meets the compression load requirements of different locations (such as door locks and hinges) can be quickly identified. This not only reduces the time wasted due to lack of experience or design iterations, but also ensures the optimal performance of the sealing strip in a variety of application scenarios, so that the final product better meets customer needs and market standards. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flow chart of an embodiment of a method for optimizing cross-section parameters of a sealing strip;

[0034] Figure 2 A schematic diagram of section parameterization in an embodiment of a section parameter optimization method for a sealing strip;

[0035] Figure 3 A schematic diagram of the assembly relationship of door locks and hinges at different positions in an embodiment of a method for optimizing cross-section parameters of a sealing strip;

[0036] Figure 4 A schematic diagram of a door lock position iteration process in an embodiment of a method for optimizing cross-section parameters of a sealing strip;

[0037] Figure 5 A schematic diagram of a hinge position iteration process in an embodiment of a cross-section parameter optimization method for a sealing strip;

[0038] Figure 6 It is a schematic diagram before and after optimization in an embodiment of a cross-section parameter optimization method for a sealing strip. DETAILED DESCRIPTION

[0039] The following is further described in detail through specific implementation methods:

[0040] Example

[0041] like Figure 1 As shown, the cross-section parameter optimization method for the sealing strip of this embodiment includes the following contents:

[0042] S1. Determine the design concept of the sealing strip section according to the preset requirements and complete the initial section outline; the preset requirements are the customer's product requirements;

[0043] S2, such as Figure 2 As shown in the figure, the wall thickness of each section is parameterized, and a compression load analysis model is established. The compression load analysis of different contact positions between the sheet metal and the sealing strip of the first version section is completed respectively, and the results are set as parameters. Among them, the contact positions include door locks and hinges, such as Figure 3As shown, the left picture shows the matching relationship between the sealing strip and the sheet metal at the door lock position; the right picture shows the matching relationship between the sealing strip and the sheet metal at the hinge position.

[0044] The compression load analysis at each contact location specifically includes:

[0045] S201, inputting material parameters of the constitutive model of the sealing strip material; the sealing strip material is dense rubber and foam rubber;

[0046] S202, establishing a contact relationship between the sheet metal contact position and the sealing strip;

[0047] S203, establishing boundary conditions for the fixing of the bottom of the sealing strip and the displacement of the sheet metal;

[0048] S204, generating quadrilateral meshes for all components involved in the analysis, namely, sheet metal and sealing strips;

[0049] S205. Submit technical tasks and complete compression load calculation;

[0050] S3. Take the wall thickness at each location of the cross section as the input parameter, and the compressive load at the door lock and hinge as the output parameter. Use the central composite design method in the preset software to establish a DOE matrix. Generate a large number of permutations and combinations of input parameters within the numerical setting range of the parameters, and calculate the results of each combination to obtain a complete DOE matrix. The numerical setting range of the parameters is determined according to the actual situation, such as the initial wall thickness ±0.3mm.

[0051] S4. Use the established DOE matrix to perform response surface analysis, including:

[0052] S401, select the response surface type as genetic aggregation model;

[0053] S402, select to automatically generate three verification points;

[0054] S403, start response surface analysis;

[0055] S404, observe the compliance index curve, if the scattered points are concentrated on the 45° line, obtain the response surface analysis results, and jump to step S5; if there are scattered points deviating from the 45° line, set the three generated verification points as optimization points, jump to S403, and re-perform the response surface analysis;

[0056] S5. Based on the response surface analysis results, MOGA (multi-optimization objective genetic algorithm) is used for optimization, including:

[0057] S501, select MOGA algorithm;

[0058] S502, specifying optimization targets and constraints; in this embodiment, the optimization target is specified as the compression load at the door lock and hinge position, and the constraint condition has a value range of the compression load force requirement of ±0.2N;

[0059] S503, automatically solving using preset software;

[0060] S504, check the optimization results, such as Figure 4 and Figure 5 The iterative process shown in the figure, the dotted line is the constraint range, and the optimization finally reaches the constraint range;

[0061] S505, obtaining the best design point, that is, the wall thickness value at each location on the cross section;

[0062] In this embodiment, Ansys software is used to analyze and solve.

[0063] S6. Export the best design point and complete the optimization analysis. The comparison before and after optimization is as follows: Figure 6 shown.

[0064] The above are only embodiments of the present invention. The invention is not limited to the fields involved in this implementation case. The common sense such as the known specific structures and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field to which the invention belongs before the application date or the priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to explain the content of the claims.

Claims

1. A method for optimizing cross-sectional parameters of a sealing strip, characterized in that: It includes the following: S1. Determine the design concept of the sealing strip section according to the preset requirements and complete the initial section outline; S2. Parameterize the wall thickness at each location of the section, establish a compression load analysis model, complete the compression load analysis of different contact positions between the sheet metal and the sealing strip of the initial section, and set the results as parameters; S3. Using the wall thickness at each location of the cross section as the input parameter and the compressive load at different contact positions as the output parameter, the DOE matrix is ​​established using the central composite design method in the preset software, and several permutations and combinations of input parameters are generated within the numerical setting range of the parameters, and the results of each combination are calculated to obtain a complete DOE matrix; S4. Use the established DOE matrix to perform response surface analysis; S5. Based on the response surface analysis results, a multi-optimization objective genetic algorithm is used for optimization; S6. Export the best design point and complete the optimization analysis.

2. The cross-sectional parameter optimization method for a sealing strip according to claim 1, characterized in that: In step S2, the compression load analysis of each contact position specifically includes: S201, inputting material parameters of the constitutive model of the sealing strip material; the sealing strip material is dense rubber and foam rubber; S202, establishing a contact relationship between the sheet metal contact position and the sealing strip; S203, establishing boundary conditions for the fixing of the bottom of the sealing strip and the displacement of the sheet metal; S204, generating a quadrilateral mesh; S205. Complete the compression load calculation.

3. The cross-sectional parameter optimization method for a sealing strip according to claim 2, characterized in that: The contact locations include door locks and hinges.

4. The cross-sectional parameter optimization method for a sealing strip according to claim 3, characterized in that: The step S4 specifically includes: S401, select the response surface type as genetic aggregation model; S402, select to automatically generate three verification points; S403, start response surface analysis; S404, observe the compliance index curve. If the scattered points are concentrated on the 45° line, the response surface analysis result is obtained, and jump to step S5; if there are scattered points deviating from the 45° line, set the three generated verification points as optimization points, jump to S403, and re-perform the response surface analysis.

5. The cross-sectional parameter optimization method for a sealing strip according to claim 4, characterized in that: The step S5 specifically includes: S501, select MOGA algorithm; S502, specifying optimization objectives and constraints; S503, automatically solving using preset software; S504, check the optimization results; S505. Obtain the optimal design point.

6. The cross-sectional parameter optimization method for a sealing strip according to claim 5, characterized in that: The specified optimization targets are the compressive loads at the door lock and hinge locations.

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