Optimization method, device and equipment of auxiliary frame rear point structure and storage medium

Abstract

The invention discloses an optimization method, device and equipment for a rear point structure of an auxiliary frame and a storage medium, and the method comprises the steps: obtaining root section force information of the rear point structure of the auxiliary frame in a frontal collision model, and enabling the root section force information to serve as a simplified model load; extracting a bolt section force curve of a rear mounting point of the auxiliary frame, and obtaining a peak value of the bolt section force curve as a bolt section constraint value; setting falling parameters of the auxiliary frame rear point structure, and generating a plurality of groups of sample parameter sets according to the falling parameters; applying a simplified model load and a boundary to each group of sample parameter sets, generating a corresponding sample model, and obtaining a sample library; establishing a response surface model according to the sample library, wherein the response surface model takes the minimum mass of the auxiliary frame assembly as a target and takes the cross section force as a constraint condition; performing optimization analysis through the response surface model to obtain an optimal falling parameter of the rear point structure of the auxiliary frame; therefore, controllable falling of the rear point structure of the auxiliary frame is achieved, and the acceleration peak value of a vehicle body and the degree of damage to a dummy are reduced.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a method, device, equipment and storage medium for optimizing a rear point structure of a subframe. Background Art

[0002] In the prior art, the connection structure between the front subframe and the vehicle body is usually a fixed connection with high strength. When a collision occurs, the powertrain will hit the front wall structure, resulting in an increase in the peak acceleration, which will cause a large deformation of the leg area of ​​the dummy in the frontal collision model.

[0003] How to optimize the frontal collision model, reduce the degree of damage to the dummy, and even avoid deformation of the dummy's leg area has become an urgent problem that needs to be solved. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, equipment and storage medium for optimizing the rear point structure of a subframe, so as to realize the controllable shedding of the rear point structure and solve the problem of high degree of damage to the dummy in the existing frontal collision model.

[0005] An embodiment of the present invention provides a method for optimizing a rear point structure of a subframe, comprising:

[0006] Obtain the root section force information of the rear point structure of the subframe in the frontal collision model as a simplified model load;

[0007] Extracting a bolt section force curve of a rear mounting point of the subframe, and obtaining a peak value of the bolt section force curve as a bolt section constraint value;

[0008] Setting the shedding parameters of the rear point structure of the subframe, and generating a plurality of groups of sample parameter sets according to the shedding parameters;

[0009] Apply simplified model loads and boundaries to each set of sample parameter sets, generate corresponding sample models, and obtain a sample library;

[0010] Establishing a response surface model according to the sample library, wherein the response surface model takes the minimum mass of the subframe assembly as a target and the cross-sectional force as a constraint condition;

[0011] The optimal shedding parameters of the rear point structure of the subframe are obtained by performing optimization analysis using the response surface model.

[0012] Optionally, the step of setting the shedding parameters of the rear point structure of the subframe and generating a plurality of groups of sample parameter sets according to the shedding parameters comprises:

[0013] Setting the type of shedding parameters of the rear point structure of the subframe and the variation range of each shedding parameter;

[0014] Constructing a DOE experimental design according to the types of shedding parameters and their variation ranges;

[0015] In the DOE experimental design, a Latin hypercube method is used to generate several groups of sample parameter sets.

[0016] Optionally, the falling-off parameters include the weakened position and diameter of the mounting bolts, the root sheet metal thickness and material of the rear point structure of the subframe, and the depth and root cross-section of the induction ribs.

[0017] Optionally, the response surface model adopts a neural network, a standard quadratic response surface method or Kriging.

[0018] Optionally, the method further comprises:

[0019] Performing engineering optimization on the rear point structure of the subframe according to the optimal shedding parameters;

[0020] Obtain the rear point structure of the subframe after engineering optimization for vehicle simulation tests and component tests.

[0021] Optionally, the engineering optimization of the rear point structure of the subframe according to the optimal shedding parameter includes:

[0022] Regularizing the sheet metal thickness of the root portion of the rear point structure of the subframe according to a preset numerical unit;

[0023] Optimizing the boundary of the rear point structure of the subframe;

[0024] The induction ribs are adjusted according to the splicing process.

[0025] Optionally, before setting the shedding parameters of the rear point structure of the subframe, the method further includes:

[0026] The sub-frame rear point structure is intercepted to obtain a simplified sub-frame rear point structure.

[0027] An embodiment of the present invention provides a device for optimizing a rear point structure of a subframe, comprising:

[0028] An acquisition module is used to obtain the root section force information of the rear point structure of the subframe in the frontal collision model as a simplified model load;

[0029] An extraction module, used to extract a bolt section force curve of a rear mounting point of a subframe, and obtain a peak value of the bolt section force curve as a bolt section constraint value;

[0030] A sample parameter generation module, used to set the shedding parameters of the rear point structure of the subframe, and generate a plurality of sample parameter sets according to the shedding parameters;

[0031] A sample model generation module is used to apply simplified model loads and boundaries to each set of sample parameter sets, generate corresponding sample models, and obtain a sample library;

[0032] An establishment module is used to establish a response surface model according to the sample library, wherein the response surface model takes the minimum mass of the subframe assembly as a target and the cross-sectional force as a constraint condition;

[0033] The optimization module is used to perform optimization analysis through the response surface model to obtain the optimal shedding parameters of the rear point structure of the subframe.

[0034] An embodiment of the present invention provides a terminal device, including a memory, a controller, and a computer program stored in the memory and executable on the controller, wherein the controller implements the above-mentioned method for optimizing the rear point structure of the sub-frame when executing the computer program.

[0035] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing the rear point structure of a subframe as described in any one of the above items is implemented.

[0036] The above-mentioned optimization method, device, equipment and storage medium for the rear point structure of the subframe obtain the root section force information of the rear point structure of the subframe in the frontal collision model as a simplified model load; extract the bolt section force curve of the rear mounting point of the subframe, and obtain the peak value of the bolt section force curve as the bolt section constraint value; set the shedding parameters of the rear point structure of the subframe, and generate several groups of sample parameter sets according to the shedding parameters; apply the simplified model load and boundary to each group of sample parameter sets to generate the corresponding sample model and obtain a sample library; establish a response surface model according to the sample library, and the response surface model takes the minimum mass of the subframe assembly as the target and the section force as the constraint condition; perform optimization analysis through the response surface model to obtain the optimal shedding parameters of the rear point structure of the subframe. In this way, the controllable shedding of the rear point structure of the subframe is realized, the conduction path of the collision force is improved, the energy absorption space at the rear of the vehicle is fully utilized, and the acceleration peak of the vehicle body and the degree of damage to the dummy are effectively reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0038] Figure 1 is a flow chart of a method for optimizing a rear point structure of a subframe in one embodiment of the present invention;

[0039] Figure 2 It is a flow chart of a method for optimizing the rear point structure of a subframe in another embodiment of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] The optimization method of the rear point structure of the subframe provided by the embodiment of the present invention obtains the optimal drop-off parameter of the rear point structure of the subframe through the optimization analysis of the response surface, improves the conduction path of the collision force, and can realize the drop-off of the subframe with relatively small changes, making full use of the energy absorption space at the rear of the vehicle, improving the deformation problem of the leg area of ​​the dummy in the frontal collision model, playing an important role in reducing the peak acceleration of the vehicle body and the degree of injury to the dummy, and improving the collision safety of the vehicle body. The method is applicable to the field of passive safety body and chassis structure design of automobiles, including but not limited to passenger cars and commercial vehicles.

[0042] In one embodiment, if Figure 1 As shown, a method for optimizing the rear point structure of a subframe is provided, the method comprising the following steps:

[0043] S101: obtaining root section force information of the rear point structure of the subframe in the frontal collision model as a simplified model load;

[0044] S102: extracting a bolt cross-sectional force curve of a rear mounting point of the subframe, and obtaining a peak value of the bolt cross-sectional force curve as a bolt cross-sectional constraint value;

[0045] S103: setting the shedding parameters of the rear point structure of the subframe, and generating a plurality of sample parameter sets according to the shedding parameters;

[0046] S104: applying simplified model loads and boundaries to each set of sample parameter sets, generating corresponding sample models, and obtaining a sample library;

[0047] S105: establishing a response surface model according to the sample library, wherein the response surface model takes minimizing the mass of the subframe assembly as a target and the cross-sectional force as a constraint condition;

[0048] S106: Performing optimization analysis through the response surface model to obtain optimal shedding parameters of the rear point structure of the subframe.

[0049] Among them, load refers to the external force that a part or a structure is subjected to when it is working. Simplified model load refers to the external force that a simplified model is subjected to when it is working.

[0050] As an example, in step S101, the rear point structure of the subframe can fall off by two ways: sheet metal failure or installation bolt failure. The sheet metal failure is limited by factors such as sheet metal thinning rate and material properties and cannot achieve a stable falling design. The latter can cause the bolts to be sheared by the bending force of the rear point structure of the subframe. Therefore, this embodiment adopts the method of installation bolt failure. This embodiment intercepts and simplifies the rear point structure of the subframe, characterizes the stress state of the rear point bolts of the subframe of the whole vehicle model, and then obtains the root section force information of the rear point structure of the subframe in the frontal collision model as the simplified model load.

[0051] The bolt section constraint value refers to the maximum force on the bolt section.

[0052] As an example, in step S102, the present embodiment first extracts the corresponding bolt section force curve for the rear mounting point of the subframe as a subframe rear point dropout assessment, and then searches and obtains the maximum value of the bolt section force curve, i.e., the peak value, and uses the peak value of the bolt section force curve as the bolt section constraint value.

[0053] The falling-off parameter refers to the factor causing the falling-off of the rear point structure of the sub-frame. The sample parameter set refers to a set consisting of different values ​​of the falling-off factor of the rear point structure of the sub-frame.

[0054] As an example, in step S103, this embodiment first sets the shedding parameters of the rear point structure of the subframe, that is, determines which shedding factors are. Optionally, as a preferred example of the present invention, the shedding parameters include but are not limited to the weakened position and diameter of the mounting bolts, the root sheet metal thickness and material of the rear point structure of the subframe, the depth and root section of the induction ribs. Then, several groups of sample parameter sets are generated according to the shedding parameters.

[0055] As an example, before setting the shedding parameters of the rear point structure of the sub-frame in step S103, this embodiment also includes intercepting the rear point structure of the sub-frame to obtain a simplified rear point structure of the sub-frame, applying a fixed support constraint to the sheet metal edge of the sub-frame mounting box, loading the simplified model according to the root section force of the rear point structure of the sub-frame, and obtaining a basic model in the sample library, so as to facilitate subsequent test analysis and improve calculation efficiency.

[0056] Among them, a set of sample parameter sets corresponds to generating a sample model.

[0057] As an example, in step S104, this embodiment applies simplified model loads and boundaries to each set of sample parameter sets, conducts tests, and generates corresponding sample models according to the test results; and traverses the plurality of sets of sample parameter sets to obtain a sample library.

[0058] The response surface model, namely the response surface function, reflects the response relationship between the independent variable cross-sectional force and the dependent variable subframe assembly mass.

[0059] As an example, in step S105, this embodiment constructs a response surface model based on the above test scheme and sample model. Optionally, there are multiple methods for constructing a response surface function, including but not limited to neural network, standard quadratic response surface method or Kriging. The response surface model takes the minimum mass of the subframe assembly as the target and the cross-sectional force as the constraint condition.

[0060] As an example, in step S106, with the goal of minimizing the mass of the subframe assembly and the cross-sectional force as a constraint condition, the response surface model is used to perform an optimization analysis on the response surface to determine the optimal result, that is, the optimal shedding parameter of the rear point structure of the subframe.

[0061] The optimization method for the rear point structure of the subframe provided in this embodiment obtains the optimal shedding parameters through the optimization analysis of the response surface, realizes the controllable shedding of the rear point structure of the subframe, improves the conduction path of the collision force, makes full use of the energy absorption space at the rear of the vehicle, reduces the peak acceleration of the vehicle body and the degree of injury to the dummy, and has a high degree of automation, which provides a new idea for the optimization of the frontal collision model and has important guiding significance for automobile design.

[0062] In one embodiment, step S103, i.e. setting the shedding parameters of the rear point structure of the subframe, and generating a plurality of sample parameter sets according to the shedding parameters, includes:

[0063] Step S1031, setting the type of shedding parameters of the rear point structure of the sub-frame and the variation range of each shedding parameter;

[0064] Step S1032, constructing a DOE experimental design according to the types of shedding parameters and their variation ranges;

[0065] Step S1033, in the DOE experimental design, a Latin hypercube method is used to generate several groups of sample parameter sets.

[0066] The falling off parameters include but are not limited to the weakened position and diameter of the mounting bolts, the root sheet metal thickness and material of the rear point structure of the subframe, and the depth and root cross-section of the induction ribs.

[0067] As an example, DOE (Design of Experiment, referred to as DOE) is a mathematical statistics method for arranging experiments and analyzing experimental data. In this embodiment, the variation range of each falling-off parameter is defined, and the variation range is selected and defined for the weakened position and diameter of the mounting bolt, the root sheet metal thickness and material of the rear point structure of the subframe, and the depth and root section of the induction rib. Then, the DOE experimental design is constructed according to the type of falling-off parameter and its variation range. Among them, the Latin hypercube method is a stratified random sampling that can efficiently sample from the distribution interval of the variable. For the falling-off parameter, this embodiment takes out N samples from the variation range of the falling-off parameter, and the variation range of each falling-off parameter is divided into N small intervals, and a value is randomly selected from each interval, and the N values ​​of each falling-off parameter are randomly combined with the values ​​of other falling-off parameters to obtain N sample parameter values. Different from random sampling, the DOE experimental design can ensure that the variation range of each falling-off parameter is fully covered, and has the advantages of high uniformity and strong representativeness.

[0068] In one embodiment, if Figure 2 As shown, after performing optimization analysis through the response surface model in step S106 to obtain the optimal shedding parameters of the rear point structure of the subframe, the method further includes:

[0069] S107, performing engineering optimization on the rear point structure of the subframe according to the optimal shedding parameters;

[0070] S108, obtaining the subframe rear point structure after engineering optimization to perform vehicle simulation tests and component tests.

[0071] The engineering optimization refers to the engineering adjustment performed to obtain the subframe rear point structure that meets the engineering design requirements. After obtaining the optimal shedding parameters, the subframe rear point structure is optimized based on the optimal shedding parameters to obtain the subframe rear point structure that meets the engineering design requirements, and then a simulation verification is performed to confirm.

[0072] As an example, step S107, namely, performing engineering optimization on the rear point structure of the subframe according to the optimal shedding parameter, further includes:

[0073] S1071, regularizing the sheet metal thickness of the root portion of the rear point structure of the subframe according to a preset numerical unit;

[0074] S1072, optimizing the boundary of the rear point structure of the subframe;

[0075] S1073, adjusting the induction ribs according to the splicing process.

[0076] Among them, when regularizing the root sheet metal thickness, regularize it in units of 0.1mm. For example, if the optimal solution is 1.43mm, regularize it to 1.4mm. When optimizing the boundary, consider the actual situation and splicing process, and adjust the range of the induction rib appropriately. Finally, put the adjusted rear point structure of the subframe into the full vehicle full head-on collision and offset collision model for verification and confirmation. After verification and confirmation, the lightweight design is completed.

[0077] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0078] In one embodiment, a terminal device is provided, including a memory, a controller, and a computer program stored in the memory and executable on the controller. When the controller executes the computer program, the optimization method of the rear point structure of the subframe in the above embodiment is implemented, for example Figure 1 S101-S106 shown are not described here in detail to avoid repetition.

[0079] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing the rear point structure of the subframe in the above embodiment is implemented, for example Figure 1 S101-S106 shown are not described here in detail to avoid repetition.

[0080] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0081] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0082] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for optimizing the rear point structure of a subframe, characterized in that: include: Obtain the root section force information of the rear point structure of the subframe in the frontal collision model as a simplified model load; Extracting a bolt section force curve of a rear mounting point of the subframe, and obtaining a peak value of the bolt section force curve as a bolt section constraint value; Setting the shedding parameters of the rear point structure of the subframe, and generating a plurality of groups of sample parameter sets according to the shedding parameters; Applying simplified model loads and boundaries to each set of sample parameter sets to generate corresponding sample models and obtain a sample library; Establishing a response surface model according to the sample library, wherein the response surface model takes the minimum mass of the subframe assembly as a target and the cross-sectional force as a constraint condition; The optimal shedding parameters of the rear point structure of the subframe are obtained by performing optimization analysis using the response surface model.

2. The method for optimizing the rear point structure of the subframe according to claim 1, characterized in that: The step of setting the shedding parameters of the rear point structure of the subframe and generating a plurality of groups of sample parameter sets according to the shedding parameters comprises: Setting the type of shedding parameters of the rear point structure of the subframe and the variation range of each shedding parameter; Constructing a DOE experimental design according to the types of shedding parameters and their variation ranges; In the DOE experimental design, a Latin hypercube method is used to generate several groups of sample parameter sets.

3. The method for optimizing the rear point structure of a subframe according to claim 1 or 2, characterized in that: The fall-off parameters include the weakened position and diameter of the mounting bolts, the root sheet metal thickness and material of the rear point structure of the subframe, and the depth and root section of the induction ribs.

4. The method for optimizing the rear point structure of the subframe according to claim 1, characterized in that: The response surface model adopts neural network, standard quadratic response surface method or Kriging.

5. The method for optimizing the rear point structure of the subframe according to claim 1, characterized in that: The method further comprises: Performing engineering optimization on the rear point structure of the subframe according to the optimal shedding parameters; Obtain the rear point structure of the subframe after engineering optimization to conduct corresponding vehicle simulation tests and component tests.

6. The method for optimizing the rear point structure of the subframe as claimed in claim 5, characterized in that: The engineering optimization of the rear point structure of the subframe according to the optimal shedding parameters includes: Regularizing the sheet metal thickness of the root portion of the rear point structure of the subframe according to a preset numerical unit; Optimizing the boundary of the rear point structure of the subframe; The induction ribs are adjusted according to the splicing process.

7. The method for optimizing the rear point structure of a subframe as claimed in claim 1, characterized in that: Before setting the shedding parameters of the rear point structure of the subframe, the method further includes: The sub-frame rear point structure is intercepted to obtain a simplified sub-frame rear point structure.

8. An optimization device for a rear point structure of a subframe, characterized in that: The device comprises An acquisition module is used to obtain the root section force information of the rear point structure of the subframe in the frontal collision model as a simplified model load; An extraction module, used to extract a bolt section force curve of a rear mounting point of a subframe, and obtain a peak value of the bolt section force curve as a bolt section constraint value; A sample parameter generation module, used to set the shedding parameters of the rear point structure of the subframe, and generate a plurality of sample parameter sets according to the shedding parameters; A sample model generation module is used to apply simplified model loads and boundaries to each set of sample parameter sets, generate corresponding sample models, and obtain a sample library; An establishment module is used to establish a response surface model according to the sample library, wherein the response surface model takes the minimum mass of the subframe assembly as a target and the cross-sectional force as a constraint condition; The optimization module is used to perform optimization analysis through the response surface model to obtain the optimal shedding parameters of the rear point structure of the subframe.

9. A terminal device, comprising a memory, a controller, and a computer program stored in the memory and executable on the controller, characterized in that: When the controller executes the computer program, the method for optimizing the rear point structure of the subframe as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for optimizing the rear point structure of the subframe as claimed in any one of claims 1 to 7 is implemented.

Images