An analysis strategy for improving the accuracy of body stiffness calibration

Abstract

The application provides an analysis strategy for improving body stiffness accuracy, which can quickly and accurately improve the accuracy and precision of a CAE model in a data development stage, and comprises the following steps: building a sample body stiffness test environment and a CAE simulation model environment based on a frozen version of data; loading and sharing data information affecting the body stiffness of the sample to the CAE simulation model, performing first parameter adjustment and update on the CAE simulation model, and outputting result data; comparing sample state data with the result data to determine whether the sample meets the benchmarking condition; testing the sample meeting the benchmarking condition to obtain sample body stiffness measured data, sharing sample state data and test process information with the CAE simulation model, performing second parameter adjustment and update on the CAE simulation model, and outputting body stiffness benchmarking data; and benchmarking the sample body stiffness measured data with the body stiffness benchmarking data to verify the accuracy and precision of the data.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automobile body stiffness testing, in particular to an analysis strategy for improving the accuracy of body stiffness benchmarking. BACKGROUND

[0002] In the current automobile industry, automobiles are in the stock market, and the degree of competition has increased dramatically. In order to occupy a place in the market, the development cycle of each manufacturer's vehicle model is shortened. With the continuous development of CAE technology, the finite element method (FEM) is increasingly applied in the automobile industry. Through the CAE model, not only can the development cycle of new vehicle models be shortened, but also the vehicle body can be lightweighted. In the process of using the CAE model, especially in vehicle development, the simulation analysis of vehicle development data and the accuracy of vehicle body structure stiffness are very important. In a real scenario, the simulation analysis results of vehicle development data need to rely on the verification of experimental test results and simulation testing benchmarking to improve the accuracy of the data, so as to better reflect the value. In the prior art, for different development stages of vehicle models, simulation analysis and each experimental stage are usually carried out separately: first, the design department provides various schemes and develops test samples; then, the test samples of each scheme are analyzed and calculated by a simulation model to verify and evaluate the feasibility of each scheme; then, the schemes with poor feasibility are redesigned to develop new test samples for analysis and calculation verification; then, the above steps are repeated, and finally, the feasible scheme data is summarized and benchmarked.

[0003] Although the above scheme can achieve the final effect, the experimental test result has a long cycle and high cost. At the same time, the test samples in each stage of testing are newly developed parts, and their processing and manufacturing have not reached the standard of all tooling, which limits the consistency of the test samples, and also brings certain deviation to the accuracy and precision of the simulation analysis test results. SUMMARY

[0004] In view of the above technical problems, the present application provides an analysis strategy for improving the accuracy of body stiffness benchmarking, which combines CAE (computer aided engineering) simulation model (finite element simulation) and experimental testing to effectively improve the accuracy and precision of the CAE model, and further improve the effectiveness and consistency of simulation and experimental benchmarking. The specific technical solution is as follows:

[0005] Step S1, simultaneously building a CAE simulation model environment and a sample vehicle body stiffness test environment based on the frozen version data;

[0006] Step S2, the CAE simulation model environment analyzes the frozen version data for body stiffness, and obtains the body stiffness theoretical data of the CAE simulation model; the sample body stiffness test environment analyzes the frozen version data, collects all data information affecting the sample body stiffness and loads the shared data into the CAE simulation model, and the CAE simulation model is updated for the first time; and the updated CAE simulation model outputs the result data to the project team;

[0007] Step S3, the sample state data is collected, confirmed and summarized to the project team, the project team compares the summarized sample state data with the updated CAE simulation model output result data, judges whether the data is consistent, and if the data is consistent, the sample meets the benchmarking condition;

[0008] Step S4, the sample meeting the benchmarking condition is tested to obtain the sample body stiffness measured data; meanwhile, the sample state data and the sample test process information are shared with the CAE simulation model, and the CAE simulation model is updated for the second time; and the updated CAE simulation model outputs the body stiffness benchmarking data;

[0009] Step S5, the obtained sample body stiffness measured data is benchmarked with the body stiffness benchmarking data output by the CAE simulation model to verify the accuracy and precision of the data.

[0010] Further, in steps S1-S5, the body stiffness includes body torsional stiffness and body bending stiffness.

[0011] In step S1, the frozen version data refers to the data recorded in the design stage and the parameter change in the manufacturing process in the past real vehicle manufacturing process.

[0012] In step S2, the CAE simulation model analyzes the frozen version data for body stiffness, which refers to all information recorded in the frozen version data. These information may affect the body stiffness analysis, or may not affect it, so first the recorded data should be collected completely.

[0013] Further, the sample body stiffness test environment analyzes the frozen version data, and the analysis process includes set variable data information, one car one single data information and trial production process data information; specifically, the set variable data information includes material, thickness, connection and structure data information; the one car one single data information includes glue and welding point data information; and the trial production process data information includes cycle compression, mold, process, version quantity of production site, parts mounting, structure change, welding position, quantity and length data information.

[0014] Further, in the process of analyzing the frozen version data, all data information affecting the body stiffness of the sample part is collected and loaded onto the CAE simulation model. The CAE simulation model is based on the frozen version data, obtains shared information, and after the information affecting the body stiffness of the sample part is extracted and compared, the first parameter adjustment and update are performed. The output result data of the updated CAE simulation model is output to the project team.

[0015] In step S3, the sample part state data includes the actual manufacturers, grades and parameters of the glass glue and structural glue, the nearest weld point inspection information of the sample part, the visual door hinge and welding quality of the sample part, and the difference parts providing the data.

[0016] Further, in step S3, if the compared data is inconsistent, the sample part does not meet the benchmarking conditions, and the benchmarking fails. For the sample part that fails to benchmark, the welding inspection, glue curing requirements, etc. need to be organized to confirm, report and review. When the benchmarking conditions are not met, the sample part can be replaced to continue to determine whether the sample part state meets the benchmarking conditions, or the benchmarking work can be cancelled.

[0017] In step S4, the sample part test process information includes clamping, loading, instrument and test process information. The test process information includes actual loading and constraint point position information.

[0018] Further, when the sample part state data and the sample part test process information are shared with the CAE simulation model, it should be ensured that the clamping, loading, test process and instrument are working properly.

[0019] Further, the CAE simulation model performs a second parameter adjustment and update, mainly reconfirms the sample part, and adjusts the CAE simulation model again with the data information affecting the body stiffness to ensure the accuracy of the final output data.

[0020] In step S5, the accuracy and precision of the verification data specifically include the following steps:

[0021] Step S501, calculate the benchmarking deviation rate by the sample part body stiffness measured data and the body stiffness benchmarking data.

[0022] Step S502, set a threshold range for the calculated benchmarking deviation rate. If the benchmarking deviation rate is within the threshold range, the accuracy and precision of the data are qualified. If the benchmarking deviation rate is not within the threshold range, the accuracy and precision of the data are unqualified.

[0023] Further, in step S501, the benchmarking deviation rate is calculated as follows:

[0024]

[0025] Further, in the step S502, the threshold range is preferably -10% < threshold < 10%.

[0026] The beneficial effects brought by the present application are: through the combination of CAE simulation model and experimental test, i.e., CAE simulation model experimental test and real experimental test are simultaneously performed, the data factors involved in real experimental test affecting the test effect are synchronized in real time to CAE simulation model test, the effectiveness and consistency of experimental results are improved, and the precision effect and value of CAE simulation model in the data development stage are effectively improved.

[0027] Further, due to the simultaneous performance of CAE simulation model experimental test and real experimental test, the cycle of experimental test results is shortened, data is synchronized in real time in the experimental test process, and the error rate and experimental test cost in the test process are reduced. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0029] Figure 1 is a flowchart of an analysis strategy for improving body stiffness benchmarking accuracy according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] The technical solutions of the present application will be described clearly and completely below in combination with specific embodiments and the drawings of the specification. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments.

[0031] In an embodiment, referring to Figure 1 The present application provides an analysis strategy for improving body stiffness benchmarking accuracy, specifically comprising:

[0032] Step S1: simultaneously building a CAE simulation model environment and a sample body stiffness test environment on the basis of the frozen version data;

[0033] Step S2: the CAE simulation model environment performs body stiffness analysis on the frozen version data to obtain the theoretical data of body stiffness of the CAE simulation model; the sample body stiffness test environment performs analysis on the frozen version data, collects all data information affecting the sample body stiffness and loads the shared data to the CAE simulation model, the CAE simulation model performs first parameter adjustment and update, and the updated CAE simulation model outputs result data to the project team;

[0034] Step S3, the sample state data is collected, confirmed and summarized to the project team, the project team compares the summarized sample state data with the updated CAE simulation model output result data, judges whether the data is consistent, and the sample meets the benchmarking conditions if the data is consistent;

[0035] Step S4, the sample that meets the benchmarking conditions is tested to obtain the sample body stiffness measured data; meanwhile, the sample state data and the sample test process information are shared with the CAE simulation model, and the CAE simulation model is updated for the second time, and the updated CAE simulation model outputs the body stiffness benchmarking data;

[0036] Step S5, the sample body stiffness measured data obtained is benchmarked with the body stiffness benchmarking data output by the CAE simulation model to verify the accuracy and precision of the data.

[0037] Further, in steps S1-S5, the body stiffness includes body torsional stiffness and body bending stiffness.

[0038] In step S1, the frozen version data refers to the data recorded in the design stage and the parameter change in the manufacturing process in the past real vehicle manufacturing process.

[0039] In step S2, the CAE simulation model analysis is based on the frozen version data for body stiffness analysis, which refers to all information recorded in the frozen version data, which may or may not affect the body stiffness analysis. Therefore, the recorded data must be collected first. After the analysis is completed, the CAE simulation model will output a body stiffness theoretical data based on the frozen version data, which will be sent to the project team (not marked in the figure).

[0040] Further, in the sample body stiffness test environment, the sample body stiffness test environment analyzes the frozen version data, and the analysis process includes set variable data information, one car one single data information and trial production process data information; specifically, the set variable data information includes material, thickness, connection, structure data information; the one car one single data information includes glue, welding point data information; the trial production process data information includes period compression, mold, process, production site version quantity, parts mounting, structure change, welding position, quantity, length data information.

[0041] Further, in the process of analyzing the frozen version data, when collecting all data information affecting the body stiffness of the sample and loading the shared information to the CAE simulation model, the CAE simulation model is based on the frozen version data, obtains the shared information, and after the information affecting the body stiffness of the sample is extracted and compared, the first parameter adjustment and update are performed, and the output result data of the updated CAE simulation model is output to the project team.

[0042] In step S3, the sample state data includes: actual manufacturers, grades and parameters of glass glue and structural glue, welding point section inspection information closest to the sample, sample visual door hinge, welding quality and difference pieces providing data.

[0043] Further, in step S3, if the compared data is inconsistent, the sample does not meet the benchmarking condition, and the benchmarking fails. For the sample that fails to benchmark, welding section inspection, glue curing requirements and the like need to be organized to confirm, report and review. When the benchmarking condition is not met, the sample can be replaced to continue to judge whether the sample state meets the benchmarking condition, or the benchmarking work can be cancelled.

[0044] In step S4, the sample test process information includes: clamping, loading, instrument and test flow information; the test flow information includes actual loading and constraint point position information.

[0045] Further, when the sample state data and the sample test process information are shared with the CAE simulation model, it should be ensured that the clamping, loading, test flow and instrument work normally.

[0046] Further, the CAE simulation model performs second parameter adjustment and update, mainly reconfirms the sample, and adjusts the data information affecting the body stiffness of the sample to the CAE simulation model again to ensure the accuracy of the finally output data.

[0047] In step S5, the accuracy and precision of the verification data specifically include the following steps:

[0048] Step S501, calculating the benchmarking deviation rate by the sample body stiffness measured data and the body stiffness benchmarking data;

[0049] Step S502, setting a threshold range for the calculated benchmarking deviation rate, if the benchmarking deviation rate is within the threshold range, the accuracy and precision of the data are qualified; if the benchmarking deviation rate is not within the threshold range, the accuracy and precision of the data are unqualified.

[0050] Further, in step S501, the benchmarking deviation rate is calculated as follows:

[0051]

[0052] Further, in the step S502, the threshold range is preferably -10% < threshold < 10%.

[0053] Finally, the results are summarized and experience is accumulated by iteration of data, which are applied to actual production.

[0054] Through the technical scheme provided by the application, the accuracy and precision of the CAE simulation model can be effectively improved, and the effectiveness and consistency of the experimental results are improved.

[0055] The above description is merely a specific implementation of the present application, enabling those skilled in the art to understand or implement the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the application. Therefore, the present application will not be limited to the embodiments shown herein, but will be consistent with the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An analysis strategy for improving the accuracy of body stiffness benchmarking, characterized by: building a CAE simulation model environment and a sample body stiffness test environment simultaneously based on the frozen version data; analyzing the frozen version data in the CAE simulation model environment to obtain the theoretical data of the body stiffness of the CAE simulation model; analyzing the frozen version data in the sample body stiffness test environment, collecting all data information affecting the body stiffness of the sample, and loading the shared data into the CAE simulation model, and updating the CAE simulation model for the first time, and outputting the updated CAE simulation model result data to the project team; collecting, confirming and summarizing the sample state data to the project team, and comparing the summarized sample state data with the updated CAE simulation model output result data to determine whether the data is consistent, and if the data is consistent, the sample meets the benchmarking conditions; testing the sample that meets the benchmarking conditions to obtain the measured data of the body stiffness of the sample; at the same time, sharing the sample state data and sample test process information with the CAE simulation model, and updating the CAE simulation model for the second time, and outputting the updated CAE simulation model to the body stiffness benchmarking data; comparing the measured data of the body stiffness of the sample with the body stiffness benchmarking data output by the CAE simulation model to verify the accuracy and precision of the data. wherein, the accuracy and precision of the data are calculated by comparing the measured data of the body stiffness of the sample with the body stiffness benchmarking data, and a threshold range is set for the calculated benchmarking deviation rate; if the benchmarking deviation rate is within the threshold range, the accuracy and precision of the data are qualified; if the benchmarking deviation rate is not within the threshold range, the accuracy and precision of the data are unqualified; the calculation method of the benchmarking deviation rate is: ； the threshold range is: -10% < threshold < 10%. 2.The analysis strategy for improving the accuracy of body stiffness benchmarking according to claim 1, characterized by: the frozen version data is based on the data recorded in the parameter change in the previous real vehicle design stage and the manufacturing process. 3.The analysis strategy for improving the accuracy of body stiffness benchmarking according to claim 1, characterized by: the analysis of the frozen version data in the sample body stiffness test environment includes set variable data information, one car one single data information and trial production process data information. 4.The analysis strategy for improving the accuracy of body stiffness benchmarking according to claim 3, characterized by: the set variable data information includes material, thickness, connection and structure data information; the one car one single data information includes glue and welding point data information; the trial production process data information includes cycle compression, mold, process, version quantity of production site, parts mounting, structure change, welding position, quantity and length data information. 5.The analysis strategy for improving the accuracy of body stiffness benchmarking according to claim 1, characterized by: the sample state data includes the actual manufacturer, model and parameters of glass glue and structural glue, the nearest welding point profile inspection information of the sample, the visual door hinge and welding quality of the sample, and the difference pieces providing data. The sample test process information includes clamping, loading, instrument, and test flow information.

6. The analysis strategy for improving the accuracy of body stiffness benchmarking according to claim 5, characterized in that: The test flow information includes actual loading and constraint point position information.

7. The analysis strategy for improving the accuracy of body stiffness benchmarking according to claim 5, characterized in that: When the sample state data and sample test process information are shared with the CAE simulation model, the clamping, loading, test flow, and instrument should be ensured to work normally.

8. The analysis strategy for improving the body rigidity to target accuracy of any one of claims 1-7, wherein: The body stiffness includes body torsional stiffness and body bending stiffness.

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