Frame lateral bending multi-parameter joint optimization method, system and equipment and storage medium

Abstract

The invention discloses a vehicle frame lateral bending multi-parameter joint optimization method, system and device and a storage medium, and relates to the technical field of vehicle frame design and optimizing.The method comprises the steps that vehicle frame actual measurement related data are collected, and a vehicle frame dynamic model is built based on simulation software according to the collected vehicle frame actual measurement related data; initial setting is carried out on bushing preload and cross beam tolerance parameters in the vehicle frame dynamic model, and the bushing preload is adjusted, so that the lateral bending condition of the vehicle frame dynamic model is consistent with the actual measurement condition; performing static balance simulation analysis on the frame dynamic model under different cross beam tolerance combinations in combination with the adjusted bushing preload; and according to simulation results under different cross beam tolerance combinations, selecting a cross beam tolerance combination meeting set requirements. According to the method, the accuracy of frame lateral bending optimization can be effectively improved.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle frame design and optimization, and in particular to a method, system, device and storage medium for joint optimization of multi-parameters of vehicle frame lateral bending. Background Art

[0002] At present, the optimization of vehicle frame lateral bending is mainly based on empirical design system, finite element analysis system, real vehicle test system, etc. The empirical design system is a parametric design system based on engineer experience, the finite element analysis system is a system that uses finite element software to perform static analysis on the vehicle frame, and the real vehicle test system is a system that selects the optimal solution through real vehicle tests of multiple samples.

[0003] However, the empirical design system method relies on personal experience, resulting in low accuracy and difficulty in handling complex situations; the finite element analysis system method does not fully consider actual assembly errors and dynamic factors, resulting in insufficient reliability of results; the actual vehicle test system method has high costs and long cycles, making it difficult to perform large-scale parameter optimization. Summary of the invention

[0004] The present application provides a frame lateral bending multi-parameter joint optimization method, system, device and storage medium, which can effectively improve the accuracy of frame lateral bending optimization.

[0005] In a first aspect, an embodiment of the present application provides a frame side bending multi-parameter joint optimization method, the frame side bending multi-parameter joint optimization method comprising:

[0006] Collecting relevant data of vehicle frame measurement, and building a vehicle frame dynamics model based on simulation software according to the collected relevant data of vehicle frame measurement;

[0007] Initially set the bushing preload and beam tolerance parameters in the frame dynamics model, and adjust the bushing preload to make the lateral bending of the frame dynamics model consistent with the actual measurement;

[0008] Combined with the adjusted bushing preload, static balance simulation analysis of the frame dynamics model under different beam tolerance combinations is performed;

[0009] According to the simulation results under different beam tolerance combinations, the beam tolerance combination that meets the set requirements is selected.

[0010] In combination with the first aspect, in one implementation, the collecting of the frame measured data and constructing the frame dynamics model based on the simulation software according to the collected frame measured data specifically includes:

[0011] Collect the position information of each section of the frame and the side bending data of the whole vehicle, and obtain the spatial coordinates of each section of the frame longitudinal beam through three-dimensional measuring equipment, and record the side bending of the frame in the actual assembly state to obtain the relevant data of the frame actual measurement;

[0012] A frame dynamics model is constructed based on ADAMS software, and the relative positions of the various sections of the frame longitudinal beam in the frame dynamics model are set in combination with the relevant data of the frame actual measurement;

[0013] Bushing elements are used to connect the frame longitudinal beams in the frame dynamics model to make the frame dynamics model consistent with the actual vehicle frame structure.

[0014] In combination with the first aspect, in one implementation, the initial setting of bushing preload and beam tolerance parameters in the frame dynamics model specifically includes:

[0015] For the bushing in the frame dynamics model, set the initial stiffness value and the initial preload to zero;

[0016] The installation position tolerance of the crossbeam in the frame dynamics model is set as a variable, and the corresponding range and step length of the variable are set;

[0017] The stiffness and preload of the bushing at the connection between the longitudinal beam segments in the frame dynamics model are set as adjustable parameters.

[0018] In combination with the first aspect, in one implementation, adjusting the bushing preload so that the lateral bending condition of the frame dynamics model is consistent with actual measurement specifically includes:

[0019] Based on the iterative optimization method, the stiffness and preload of the bushing in the frame dynamics model are jointly adjusted to make the lateral bending of the frame dynamics model in the static equilibrium state consistent with the lateral bending of the actual vehicle frame in the actual assembly state;

[0020] Save the adjusted bushing stiffness and preload.

[0021] In combination with the first aspect, in one implementation,

[0022] The static balance simulation analysis of the frame dynamics model under different beam tolerance combinations is performed in combination with the adjusted bushing preload, specifically including:

[0023] Based on the bushing stiffness and preload under the condition that the lateral bending of the frame dynamics model is consistent with the actual measurement, and the crossbeam tolerance is randomly combined, the static balance simulation analysis of the frame dynamics model under different crossbeam tolerance combinations is performed, and the simulation results are recorded, and the simulation results include the frame lateral bending and stress distribution;

[0024] The selection of a beam tolerance combination that meets the set requirements according to the simulation results under different beam tolerance combinations specifically includes:

[0025] The simulation results under different beam tolerance combinations are evaluated, and according to the preset camber standard, the beam tolerance combination that meets the set requirements is selected, and the optimal beam tolerance combination is screened from the selected beam tolerance combinations.

[0026] In combination with the first aspect, in one embodiment, after selecting a beam tolerance combination that meets the set requirements, the method further includes:

[0027] The frame is manufactured and assembled based on the optimal beam tolerance combination obtained by screening out the beam tolerance combinations that meet the set requirements;

[0028] The camber of the manufactured frame was measured and compared with the corresponding simulation results;

[0029] Based on the comparison results, the parameters of the frame dynamics model are adjusted.

[0030] In a second aspect, an embodiment of the present application provides a frame side bending multi-parameter joint optimization system, the frame side bending multi-parameter joint optimization system comprising:

[0031] A data acquisition module, which is used to collect relevant data of the actual measurement of the frame;

[0032] A model building module, which is used to build a frame dynamics model through simulation software based on the frame actual measurement related data collected by the data collection module;

[0033] A parameter setting module, which is used to initially set bushing preload and beam tolerance parameters in the frame dynamics model;

[0034] A simulation analysis module is used to adjust the bushing preload of the frame dynamics model so that the lateral bending of the frame dynamics model is consistent with the actual measurement, and to perform static balance simulation analysis on the frame dynamics model under different beam tolerance combinations in combination with the adjusted bushing preload;

[0035] The result evaluation module is used to select a beam tolerance combination that meets the set requirements according to the simulation results under different beam tolerance combinations.

[0036] In conjunction with the second aspect, in one implementation,

[0037] The frame side bending multi-parameter joint optimization system also includes a verification feedback module;

[0038] The verification feedback module is used to perform actual vehicle verification based on the selected beam tolerance combination that meets the set requirements, and adjust the frame dynamics model parameters based on the verification results.

[0039] In a third aspect, an embodiment of the present application provides a frame side bending multi-parameter joint optimization device, the frame side bending multi-parameter joint optimization device comprising a processor, a memory, and a frame side bending multi-parameter joint optimization program stored in the memory and executable by the processor, wherein when the frame side bending multi-parameter joint optimization program is executed by the processor, the steps of the frame side bending multi-parameter joint optimization method described above are implemented.

[0040] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which is stored a frame side bending multi-parameter joint optimization program, wherein when the frame side bending multi-parameter joint optimization program is executed by a processor, the steps of the above-mentioned frame side bending multi-parameter joint optimization method are implemented.

[0041] The beneficial effects brought by the technical solution provided by the embodiments of the present application include:

[0042] It can improve the accuracy of frame lateral bending optimization and achieve more accurate frame lateral bending control through multi-parameter joint optimization based on measured data; at the same time, it can reduce design costs, reduce the number of physical tests through virtual simulation systems, improve optimization efficiency, and improve design efficiency. It uses parametric design and automated simulation to speed up the frame optimization process and improve product quality. Through a systematic optimization process, it can improve vehicle performance and reliability, while enhancing adaptability, and can be applied to frame optimization of different models. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of the process of the multi-parameter joint optimization method for frame side bending of this application;

[0044] Figure 2 This is a schematic diagram of the functional modules of the multi-parameter joint optimization system for frame side bending of this application;

[0045] Figure 3 This is a schematic diagram of the hardware structure of the multi-parameter joint optimization equipment for frame side bending in this application. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0048] In a first aspect, an embodiment of the present application provides a multi-parameter joint optimization method for frame lateral bending, so as to solve the problem that lateral bending is difficult to be accurately controlled in frame design.

[0049] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of the multi-parameter joint optimization method for frame side bending in this application. Figure 1 As shown in FIG. 1 , the multi-parameter joint optimization method for frame side bending includes:

[0050] S1: Collecting the relevant data of the actual measurement of the frame, and building the frame dynamics model based on the simulation software according to the collected relevant data of the actual measurement of the frame;

[0051] Furthermore, in one embodiment, collecting the frame measured data, and constructing the frame dynamics model based on the collected frame measured data based on the simulation software, specifically includes:

[0052] S101: collecting the position information of each section of the frame and the side bending data of the whole vehicle, and obtaining the spatial coordinates of each section of the frame longitudinal beam through a three-dimensional measuring device, and recording the side bending condition of the frame in the actual assembly state, and obtaining the frame actual measurement related data;

[0053] Specifically, the actual measured data of the actual vehicle frame is collected, including the position information of each section of the frame and the lateral bending data of the whole vehicle. At the same time, high-precision three-dimensional measurement equipment is used to obtain the spatial coordinates of each section of the frame longitudinal beam. At the same time, the lateral bending conditions of the actual vehicle frame in the actual assembly state are recorded as a reference for subsequent optimization.

[0054] S102: constructing a vehicle frame dynamics model based on ADAMS software, and setting the relative positions of various sections of the frame longitudinal beam in the vehicle frame dynamics model in combination with the relevant data of the actual measurement of the frame; ADAMS, which stands for Automatic Dynamic Analysis of Mechanical Systems, is a virtual prototype analysis software.

[0055] S103: Using bushing elements to connect the frame longitudinal beams in the frame dynamics model, so that the frame dynamics model is consistent with the actual vehicle frame structure.

[0056] Specifically, a frame dynamics model is constructed in the ADAMS software, and the collected frame measured data is combined to accurately restore the relative positions of each section of the frame longitudinal beam in the frame dynamics model, and bushing elements are used to connect each section of the frame longitudinal beam. The bushing stiffness is not set at the beginning, so as to construct a complete frame dynamics model including the crossbeam to ensure that the model structure is consistent with the actual frame.

[0057] S2: Initially set the bushing preload and beam tolerance parameters in the frame dynamics model, and adjust the bushing preload so that the lateral bending of the frame dynamics model is consistent with the actual measurement;

[0058] Furthermore, in one embodiment, the bushing preload and beam tolerance parameters in the frame dynamics model are initially set, specifically including:

[0059] S201: for the bushing in the frame dynamics model, an initial stiffness value and an initial zero preload are set;

[0060] S202: setting the installation position tolerance of the crossbeam in the frame dynamics model as a variable, and setting the corresponding range and step length of the variable;

[0061] S203: The stiffness and preload of the bushing at the connection between the longitudinal beam segments of the frame dynamics model are set as adjustable parameters.

[0062] Specifically, for the 11 pairs of bushing connections in the frame dynamics model, a smaller stiffness value and zero preload are initially set, and a parameter interface is reserved for subsequent simultaneous adjustment of stiffness and preload. Then, the installation position tolerance of 9 to 11 beams is set as a variable with a range of ±5 mm and a step size of 0.5 mm. Then, the stiffness and preload of the bushings at the connections between the longitudinal beam segments are set as adjustable parameters, and the range is determined based on empirical values.

[0063] Furthermore, in one embodiment, adjusting the bushing preload so that the lateral bending of the frame dynamics model is consistent with the actual measurement specifically includes:

[0064] S211: Based on the iterative optimization method, the stiffness and preload of the bushing in the frame dynamics model are jointly adjusted so that the lateral bending of the frame dynamics model in the static equilibrium state is consistent with the lateral bending of the actual vehicle frame in the actual assembly state;

[0065] S212: Save the adjusted stiffness and preload of the bushing.

[0066] Specifically, the stiffness and preload of the bushing are first adjusted jointly so that the lateral bending of the frame dynamics model in the static equilibrium state is consistent with the lateral bending of the actual vehicle frame in the actual assembly state, that is, consistent with the above-mentioned collected frame measured related data. The joint adjustment can adopt an iterative optimization algorithm to adjust the stiffness and preload at the same time until the best match is achieved, and then save the adjusted stiffness and preload of the bushing.

[0067] S3: Combined with the adjusted bushing preload, static balance simulation analysis is performed on the frame dynamics model under different beam tolerance combinations;

[0068] Furthermore, in one embodiment, in combination with the adjusted bushing preload, a static balance simulation analysis is performed on the frame dynamics model under different beam tolerance combinations, specifically including:

[0069] Based on the lateral bending of the frame dynamics model and the bushing stiffness and preload under the condition consistent with the actual measurement, and the random combination of beam tolerances, the static balance simulation analysis of the frame dynamics model under different beam tolerance combinations is performed, and the simulation results are recorded, which include the frame lateral bending and stress distribution

[0070] Specifically, based on the stiffness and preload of the adjusted bushing, the beam tolerances are randomly combined each time, and the static balance simulation analysis of the frame dynamics model is automatically performed. The number of simulations can be more than 5,000 times, thereby covering more beam tolerance combinations, and the simulation results are recorded after each simulation. The simulation results include key data such as frame lateral curvature and stress distribution.

[0071] S4: According to the simulation results under different beam tolerance combinations, select the beam tolerance combination that meets the set requirements.

[0072] Furthermore, in one embodiment, according to the simulation results under different beam tolerance combinations, a beam tolerance combination that meets the set requirements is selected, specifically including:

[0073] The simulation results under different beam tolerance combinations are evaluated, and according to the preset camber standard, the beam tolerance combination that meets the set requirements is selected, and the optimal beam tolerance combination is screened from the selected beam tolerance combinations.

[0074] Specifically, after the simulation is completed, the simulation results are evaluated, the camber is evaluated and the optimal beam tolerance combination is selected, and a comprehensive evaluation is performed on the multiple simulation results obtained. According to the preset camber standard, the beam tolerance combination that meets the set requirements is selected. Furthermore, other factors, such as manufacturing feasibility, cost, etc., can be combined to screen the optimal beam tolerance combination from the selected beam tolerance combinations that meet the set requirements.

[0075] Furthermore, in one embodiment, after selecting a beam tolerance combination that meets the set requirements, the method further includes:

[0076] a: Manufacturing and assembling the frame based on the optimal beam tolerance combination obtained by screening out the beam tolerance combinations that meet the set requirements;

[0077] b: The lateral curvature of the manufactured frame is measured and compared with the corresponding simulation results;

[0078] c: Based on the comparison results, the frame dynamics model parameters are adjusted.

[0079] Specifically, actual vehicle verification is carried out and optimization results are fed back. According to the optimal beam tolerance combination, the actual vehicle frame is manufactured and assembled, the camber of the manufactured frame is measured, and then compared with the camber in the simulation results corresponding to the optimal beam tolerance combination. If there is a significant difference between the two, the frame dynamics model parameters are adjusted, and an optimization result database is established to provide a reference for the subsequent optimization of similar models.

[0080] The multi-parameter joint optimization method for frame side bending of the present application is specifically described below with reference to an example.

[0081] First, data collection is carried out. A high-precision three-coordinate measuring instrument is used to obtain the measured data of the actual vehicle frame. Twelve sections of the left and right longitudinal beams (a total of 24 sections) are measured. Multiple key points are selected for each section, and a total of more than 100 spatial coordinate points are obtained. The installation positions of 9 to 11 crossbeams (determined according to the actual vehicle model) are accurately measured, and the lateral bending data of the frame in the actual assembly state is recorded.

[0082] Then the model is constructed. A detailed frame dynamics model is created in the ADAMS environment. Based on the measured data, the left and right longitudinal beams are accurately modeled, with 12 sections on each side, for a total of 24 sections. 9 to 11 cross beams are added (the specific number is determined based on the actual vehicle model). The positions are based on the measured data, and 11 pairs of bushings are set between the longitudinal beam sections (one bushing is required between each of the 12 sections of the longitudinal beam on each side).

[0083] Then the parameters are set. For the 11 pairs of bushing connections, the stiffness is not set initially, and a parameter interface is reserved for subsequent adjustment of the preload. The installation position tolerance of 9 to 11 beams is set as a variable with a range of ±5mm and a step size of 0.5mm. The preload force at the connection between the longitudinal beam segments is set as an adjustable parameter, and the range is determined based on empirical values.

[0084] Then, a simulation analysis is performed and the bushing preload is adjusted to make the camber of the model in a static equilibrium state consistent with the measured data. The adjusted bushing preload is maintained and 5,000 simulation calculations are automatically performed (the number is increased to cover more combinations). The beam tolerance is randomly combined each time, and key data such as the vehicle camber and stress distribution are recorded after each simulation.

[0085] The results are then evaluated, and combinations with a camber less than 5 mm are screened as candidate solutions. A multi-objective evaluation is performed on the candidate solutions, taking into account factors such as camber, uniformity of stress distribution, and manufacturing feasibility. A weighted scoring method is used to select the top 5 solutions with the best overall performance. The optimal number can be flexibly determined based on needs.

[0086] Finally, verification feedback is given, and virtual assembly verification is performed on the Top 5 solutions to simulate assembly errors in actual production. The Top 3 solutions with the most stable performance are selected for actual vehicle manufacturing and verification. The actual vehicle test data, including static camber, dynamic driving data, etc., are recorded. The actual vehicle data is compared and analyzed with the simulation results, and the error rate is calculated. If the error rate exceeds the preset threshold (such as 5%), the model correction process is automatically started, the simulation parameters are adjusted, and an optimization result database is established at the same time to record the complete process and results of this optimization, providing a reference for subsequent optimization of similar models.

[0087] This application integrates the dynamic model building function of measured data, adopts a bushing preload adjustment mechanism, is closer to the actual assembly state, has the parameterized setting and optimization function of the beam tolerance, and combines ADAMS software for dynamic simulation to consider more practical factors.

[0088] In actual applications, the present application improves optimization accuracy. Through measured data and multi-parameter joint optimization, the lateral bending control accuracy is improved by about 20%; the cost is reduced, the number of virtual simulations is increased, and the physical tests are reduced by more than 50%; the efficiency is improved, and the design cycle is shortened by 30-40%; the quality is improved, and the consistency of the lateral bending of the frame is improved by 15-25%; the adaptability is enhanced, and it can be quickly applied to different models, and the adaptability is improved by more than 50%.

[0089] The frame side bending multi-parameter joint optimization method of the embodiment of the present application can improve the accuracy of frame side bending optimization, and achieve more accurate frame side bending control through multi-parameter joint optimization based on measured data; at the same time, it can reduce design costs, reduce the number of physical tests through a virtual simulation system, improve optimization efficiency, and improve design efficiency. It uses parametric design and automated simulation to speed up the frame optimization process and improve product quality. Through a systematic optimization process, it improves the performance and reliability of the entire vehicle, and at the same time enhances adaptability, and can be applied to frame optimization of different models.

[0090] In a second aspect, an embodiment of the present application also provides a multi-parameter joint optimization system for frame side bending.

[0091] In one embodiment, referring to Figure 2 , Figure 2 This is a schematic diagram of the functional modules of the multi-parameter joint optimization system for frame side bending in this application. Figure 2 As shown, the frame side bending multi-parameter joint optimization system includes: a data acquisition module, a model building module, a parameter setting module, a simulation analysis module, a result evaluation module, and a verification feedback module.

[0092] The data acquisition module is used to collect the relevant data of the actual measurement of the frame; the model construction module is used to build the frame dynamics model through the simulation software according to the relevant data of the actual measurement of the frame collected by the data acquisition module; the parameter setting module is used to initially set the bushing preload and beam tolerance parameters in the frame dynamics model; the simulation analysis module is used to adjust the bushing preload of the frame dynamics model to make the lateral bending of the frame dynamics model consistent with the actual measurement, and to perform static balance simulation analysis on the frame dynamics model under different beam tolerance combinations in combination with the adjusted bushing preload; the result evaluation module is used to select the beam tolerance combination that meets the set requirements according to the simulation results under different beam tolerance combinations. The verification feedback module is used to perform actual vehicle verification based on the selected beam tolerance combination that meets the set requirements, and adjust the frame dynamics model parameters based on the verification results.

[0093] Specifically, the data acquisition module obtains measured data. The model building module builds a basic model in ADAMS based on the measured data. The parameter setting module initializes the bushing preload and beam tolerance parameters. The simulation analysis module first adjusts the bushing preload to make the model lateral bending consistent with the actual measurement, and then keeps the bushing preload unchanged and performs static balance analysis on different beam tolerance combinations. The result evaluation module analyzes the lateral bending of each combination and selects the optimal solution. The verification feedback module conducts actual vehicle testing, verifies the optimization results, and feeds the data back to the system for further optimization.

[0094] In a third aspect, an embodiment of the present application provides a multi-parameter joint optimization device for frame side bending. The multi-parameter joint optimization device for frame side bending can be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0095] Reference Figure 3 , Figure 3 Schematic diagram of the hardware structure of the multi-parameter joint optimization device for frame side bending involved in the embodiment of the present application. In the embodiment of the present application, the multi-parameter joint optimization device for frame side bending may include a processor, a memory, a communication interface and a communication bus.

[0096] The communication bus may be of any type and is used to interconnect the processor, the memory, and the communication interface.

[0097] The communication interface includes an input / output (I / O) interface, a physical interface, and a logical interface, etc., which are used to interconnect the devices inside the frame side bending multi-parameter joint optimization device, and an interface used to interconnect the frame side bending multi-parameter joint optimization device with other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, an optical fiber interface, an ATM interface, etc.; the user device can be a display (Display), a keyboard (Keyboard), etc.

[0098] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0099] The processor may be a general-purpose processor, which may call the frame side bending multi-parameter joint optimization program stored in the memory and execute the frame side bending multi-parameter joint optimization method provided in the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the frame side bending multi-parameter joint optimization program is called may refer to the various embodiments of the frame side bending multi-parameter joint optimization method of the present application, which will not be repeated here.

[0100] Those skilled in the art will understand that Figure 3 The hardware structure shown in the figure does not constitute a limitation on the present application, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0101] In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium.

[0102] The computer-readable storage medium of the present application stores a frame side bending multi-parameter joint optimization program, wherein when the frame side bending multi-parameter joint optimization program is executed by a processor, the steps of the frame side bending multi-parameter joint optimization method as described above are implemented.

[0103] Among them, the method implemented when the frame side bending multi-parameter joint optimization program is executed can refer to the various embodiments of the frame side bending multi-parameter joint optimization method of the present application, and will not be repeated here.

[0104] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0105] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0106] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0107] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0108] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0109] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A multi-parameter joint optimization method for frame side bending, characterized in that: The frame side bending multi-parameter joint optimization method comprises: Collecting relevant data of vehicle frame measurement, and building a vehicle frame dynamics model based on simulation software according to the collected relevant data of vehicle frame measurement; Initially set the bushing preload and beam tolerance parameters in the frame dynamics model, and adjust the bushing preload to make the lateral bending of the frame dynamics model consistent with the actual measurement; Combined with the adjusted bushing preload, static balance simulation analysis of the frame dynamics model under different beam tolerance combinations is performed; According to the simulation results under different beam tolerance combinations, the beam tolerance combination that meets the set requirements is selected.

2. A multi-parameter joint optimization method for frame side bending as claimed in claim 1, characterized in that: The collecting of the frame measured data and building the frame dynamics model based on the simulation software according to the collected frame measured data specifically includes: Collect the position information of each section of the frame and the side bending data of the whole vehicle, and obtain the spatial coordinates of each section of the frame longitudinal beam through three-dimensional measuring equipment, and record the side bending of the frame in the actual assembly state to obtain the relevant data of the frame actual measurement; A frame dynamics model is constructed based on ADAMS software, and the relative positions of the various sections of the frame longitudinal beam in the frame dynamics model are set in combination with the relevant data of the frame actual measurement; Bushing elements are used to connect the frame longitudinal beams in the frame dynamics model to make the frame dynamics model consistent with the actual vehicle frame structure.

3. A multi-parameter joint optimization method for frame side bending as claimed in claim 1, characterized in that: The initial setting of bushing preload and beam tolerance parameters in the frame dynamics model specifically includes: For the bushing in the frame dynamics model, set the initial stiffness value and the initial preload to zero; The installation position tolerance of the crossbeam in the frame dynamics model is set as a variable, and the corresponding range and step length of the variable are set; The stiffness and preload of the bushing at the connection between the longitudinal beam segments in the frame dynamics model are set as adjustable parameters.

4. A multi-parameter joint optimization method for frame side bending as claimed in claim 3, characterized in that: The bushing preload is adjusted so that the lateral bending of the frame dynamics model is consistent with the actual measurement, specifically including: Based on the iterative optimization method, the stiffness and preload of the bushing in the frame dynamics model are jointly adjusted to make the lateral bending of the frame dynamics model in the static equilibrium state consistent with the lateral bending of the actual vehicle frame in the actual assembly state; Save the adjusted bushing stiffness and preload.

5. The multi-parameter joint optimization method for frame lateral bending according to claim 1, characterized in that: The static balance simulation analysis of the frame dynamics model under different beam tolerance combinations is performed in combination with the adjusted bushing preload, specifically including: Based on the bushing stiffness and preload under the condition that the lateral bending of the frame dynamics model is consistent with the actual measurement, and the crossbeam tolerance is randomly combined, the static balance simulation analysis of the frame dynamics model under different crossbeam tolerance combinations is performed, and the simulation results are recorded, and the simulation results include the frame lateral bending and stress distribution; The selection of a beam tolerance combination that meets the set requirements according to the simulation results under different beam tolerance combinations specifically includes: The simulation results under different beam tolerance combinations are evaluated, and according to the preset camber standard, the beam tolerance combination that meets the set requirements is selected, and the optimal beam tolerance combination is screened from the selected beam tolerance combinations.

6. A multi-parameter joint optimization method for frame lateral bending as claimed in claim 1, characterized in that: After selecting the beam tolerance combination that meets the set requirements, it also includes: The frame is manufactured and assembled based on the optimal beam tolerance combination obtained by screening out the beam tolerance combinations that meet the set requirements; The camber of the manufactured frame was measured and compared with the corresponding simulation results; Based on the comparison results, the parameters of the frame dynamics model are adjusted.

7. A multi-parameter joint optimization system for frame side bending, characterized in that: The frame side bending multi-parameter joint optimization system comprises: A data acquisition module, which is used to collect relevant data of the actual measurement of the frame; A model building module, which is used to build a frame dynamics model through simulation software based on the frame actual measurement related data collected by the data collection module; A parameter setting module, which is used to initially set bushing preload and beam tolerance parameters in the frame dynamics model; A simulation analysis module is used to adjust the bushing preload of the frame dynamics model so that the lateral bending of the frame dynamics model is consistent with the actual measurement, and to perform static balance simulation analysis on the frame dynamics model under different beam tolerance combinations in combination with the adjusted bushing preload; The result evaluation module is used to select a beam tolerance combination that meets the set requirements according to the simulation results under different beam tolerance combinations.

8. A frame side bending multi-parameter joint optimization system as claimed in claim 7, characterized in that: The frame side bending multi-parameter joint optimization system also includes a verification feedback module; The verification feedback module is used to perform actual vehicle verification based on the selected beam tolerance combination that meets the set requirements, and adjust the frame dynamics model parameters based on the verification results.

9. A multi-parameter joint optimization device for frame side bending, characterized in that: The frame side bending multi-parameter joint optimization device includes a processor, a memory, and a frame side bending multi-parameter joint optimization program stored in the memory and executable by the processor, wherein when the frame side bending multi-parameter joint optimization program is executed by the processor, the steps of the frame side bending multi-parameter joint optimization method as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a frame side bending multi-parameter joint optimization program, wherein when the frame side bending multi-parameter joint optimization program is executed by the processor, the steps of the frame side bending multi-parameter joint optimization method as described in any one of claims 1 to 6 are implemented.

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