Automobile door dynamic simulation optimization method and system based on multiple physical fields

Abstract

The invention provides an automobile door dynamic simulation optimization method and system based on multiple physical fields, and the method comprises the steps: S1, building a virtual automobile door model based on an actual physical automobile door model, and carrying out the finite element analysis of the virtual automobile door model based on the automobile door material parameters in the current temperature range and the stress range, simulation data of the vehicle door weight and the structural strength are obtained; s2, constructing a target function for the simulation data of the vehicle door weight and the structural strength, wherein the target function is set to be that the vehicle door weight meets the minimum weight and the structural strength can pass a vehicle crashworthiness test; and S3, the optimal vehicle door weight and the optimal structural strength output by the target function are searched through a differential optimization algorithm, and vehicle door material parameters corresponding to the optimal vehicle door weight and the optimal structural strength are obtained. The design efficiency and accuracy of the automobile door are improved, and the research and development cost of the automobile is reduced.

Description

Technical Field

[0001] The present invention relates to the field of vehicle testing technology, and more specifically, to a method and system for dynamic simulation optimization of automobile doors based on multi-physical fields. Background Art

[0002] Existing technologies usually optimize the performance of automotive doors through traditional design and testing methods. These methods include the production and testing of physical samples, the application of empirical formulas, and the preliminary application of finite element analysis. Specifically, engineers first build a geometric model of the door, and then use the static performance data of existing materials to perform finite element analysis to evaluate the performance of the door under specific force and environmental conditions. Then, the simulation results are verified through physical tests, and the design is finally adjusted to meet the strength and weight requirements. This process often relies on experience and repeated test adjustments, which is inefficient and costly.

[0003] The main defects of the existing technology include: first, the traditional method usually lacks comprehensive consideration of multiple environmental conditions, and cannot fully evaluate the performance of the door under different temperature and stress conditions, resulting in less than optimal design results; second, the time and cost required for physical testing are high, especially in the process of multiple iterations, the cycle of specimen production and testing delays the time to market; third, the existing technology relies more on manual measurement and empirical data in data acquisition, which may lead to inaccuracy and inconsistency of data, thus affecting the reliability of the design; finally, the traditional optimization method often uses simple empirical formulas, which makes it difficult to find the global optimal solution in a complex design space, limiting the potential for design innovation and performance improvement. Therefore, there is a lot of room for improvement in the efficiency, accuracy and innovation of the existing technology. Summary of the invention

[0004] In view of the technical problems existing in the prior art, the present invention provides a dynamic simulation optimization method and system for automobile doors based on multi-physical fields, so as to improve the efficiency and accuracy of automobile door design and reduce R&D costs.

[0005] According to a first aspect of the present invention, a method for dynamic simulation optimization of a vehicle door based on multi-physics fields is provided, comprising: S1, constructing a virtual door model based on the actual physical door model, performing finite element analysis on the virtual door model based on the door material parameters within the current temperature range and the force range, and obtaining simulation data of the door weight and structural strength; S2, constructing an objective function for the simulation data of the door weight and structural strength, wherein the objective function is set such that the door weight meets the minimum weight and the structural strength can pass the automobile crashworthiness test; S3, using a differential optimization algorithm to find the optimal door weight and optimal structural strength output by the objective function, and obtaining the door material parameters corresponding to the optimal door weight and optimal structural strength.

[0006] Based on the above technical solution, the present invention can also make the following improvements.

[0007] Optionally, in step S1, constructing a virtual door model based on the actual physical door model includes: Obtaining material properties of each component in the actual door assembly and determining the bonding method between the components, wherein the material properties at least include Young's modulus, Poisson's ratio and yield strength; Establish three-dimensional models of each component according to its size, assemble the three-dimensional models of each component according to the combination mode between the components, and construct a door dynamics model; The material properties of each component and the door dynamics model are combined to form a virtual door model.

[0008] Optionally, step S1 further includes obtaining the door material parameters within the current temperature range and the force range, specifically including: Determine the actual door temperature according to the current door ambient temperature, and set the temperature change range according to the actual door temperature; Get the force currently borne by the door, and set the force variation range according to the force borne by the door; Constructing a two-dimensional temperature-force space according to the temperature variation interval and the force variation interval; Selecting values ​​of N different coordinate points in the temperature-force space to form N sets of ambient temperature and force condition data; At least N groups of material parameters regarding temperature and stress conditions corresponding to different material positions on the door are obtained according to the N groups of ambient temperature and stress condition data, wherein the material parameters at least include Young's modulus and yield strength.

[0009] Optionally, in step S1, the finite element analysis of the virtual door model is performed based on the door material parameters within the current temperature range and the force range to obtain simulation data of the door weight and structural strength, including: Substitute the at least N groups of material parameters related to temperature and stress conditions into finite element analysis software as simulation conditions, perform finite element analysis on the virtual door model, evaluate the structural strength of the door under different temperature and stress conditions, and obtain simulation data of the door weight and structural strength.

[0010] Optionally, in step S2, the objective function is: , in, is the minimum weight of the door, is the weight coefficient, Obtained through relevant collision simulation tests, For the structural strength of the car door.

[0011] Optionally, step S3 includes: Constructing a genetic function about the weight and structural strength of the vehicle door, inputting the maximum value of the genetic function as a search target into the differential evolution algorithm to search the solution space of the objective function, and continuously iterating the search results until the maximum value of the objective function is obtained; The door weight corresponding to the maximum value of the objective function is taken as the optimal door weight, and the structural strength corresponding to the maximum value of the objective function is taken as the optimal structural strength, and the door material parameters corresponding to the optimal door weight and the optimal structural strength are obtained.

[0012] Optionally, the genetic function is: , Among them, Y is the result of the genetic function, is the structural strength obtained from the finite element analysis, is the door weight obtained from finite element analysis.

[0013] According to a second aspect of the present invention, a multi-physics field-based automobile door dynamic simulation optimization system is provided, comprising: A construction and simulation module, used to construct a virtual door model based on the actual physical door model, and perform finite element analysis on the virtual door model based on the door material parameters within the current temperature range and the force range to obtain simulation data of the door weight and structural strength; A constraint module, used to construct an objective function for the simulation data of the door weight and structural strength, wherein the objective function is set such that the door weight meets the minimum weight and the structural strength can pass the automobile crashworthiness test; The optimization module is used to find the optimal door weight and optimal structural strength output by the objective function by using a differential optimization algorithm, so as to obtain the door material parameters corresponding to the optimal door weight and optimal structural strength.

[0014] According to a third aspect of the present invention, there is provided an electronic device comprising a memory and a processor, wherein the processor is used to implement the steps of the above-mentioned multi-physical field-based automobile door dynamic simulation optimization method when executing a computer management program stored in the memory.

[0015] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium on which a computer management program is stored. When the computer management program is executed by a processor, the steps of the above-mentioned automobile door dynamic simulation optimization method based on multi-physical fields are implemented.

[0016] The present invention provides a method, system, electronic device and storage medium for dynamic simulation optimization of automobile doors based on multi-physical fields. First, by establishing a virtual door model, the dynamic characteristics of the actual door can be accurately simulated in a simulation environment, thereby providing reliable data support for the design. Secondly, the present invention can dynamically adjust the material parameters used for finite element analysis according to the current environmental conditions (temperature, stress conditions). This process ensures a comprehensive evaluation of the door performance under different temperatures and stress conditions, and significantly improves the scientificity and accuracy of the door design. In addition, the door is subjected to detailed structural strength analysis and door weight analysis through finite element analysis, and the door weight and structural strength are constrained through the objective function, so that the design team can identify potential weak links and make timely improvements to ensure the structural safety and reliability of the door. Using the differential evolution algorithm to optimize the objective function not only improves the efficiency of the optimization process, but also can quickly find the optimal solution of the door weight and structural strength in a complex design space, thereby shortening the research and development cycle and reducing the research and development cost. At the same time, the present invention plays an important role in improving automobile safety, and enhances the overall crashworthiness of the vehicle by ensuring the performance of the door under extreme conditions. The introduction of this optimization design method has promoted the technological progress of the automotive industry, promoted sustainable development, and helped to enhance the market competitiveness of automotive products. Ultimately, based on the design concept of this invention, companies can achieve a more efficient and economical automobile manufacturing process, bringing significant economic benefits and social value. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of a dynamic simulation optimization method for automobile doors based on multi-physical fields provided by the present invention; Figure 2 A flow chart of a dynamic simulation optimization method for a vehicle door based on multi-physics fields provided in a certain embodiment; Figure 3 A block diagram of the composition of a multi-physics field based automobile door dynamic simulation optimization system provided by the present invention; Figure 4 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention; Figure 5 A schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0018] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0019] Figure 1 A flow chart of a dynamic simulation optimization method for a vehicle door based on multi-physics fields provided by the present invention, such as Figure 1 As shown, the method includes steps S1 to S3: S1, constructing a virtual door model based on the actual physical door model, performing finite element analysis on the virtual door model based on the door material parameters within the current temperature range and the force range, and obtaining simulation data of the door weight and structural strength; S2, constructing an objective function for the simulation data of the door weight and structural strength, wherein the objective function is set such that the door weight meets the minimum weight and the structural strength can pass the automobile crashworthiness test; S3, using a differential optimization algorithm to find the optimal door weight and optimal structural strength output by the objective function, and obtaining the door material parameters corresponding to the optimal door weight and optimal structural strength.

[0020] It is understandable that, based on the defects in the background technology, the embodiment of the present invention proposes a dynamic simulation optimization method for automobile doors based on multi-physical fields. First, by establishing a virtual door model, the dynamic characteristics of the actual door can be accurately simulated in the simulation environment, thereby providing reliable data support for the design. Secondly, the present invention can dynamically adjust the material parameters used for finite element analysis according to the current environmental conditions (temperature, stress conditions). This process ensures a comprehensive evaluation of the door performance under different temperatures and stress conditions, and significantly improves the scientificity and accuracy of the door design. In addition, the door is subjected to detailed structural strength analysis and door weight analysis through finite element analysis, and the door weight and structural strength are constrained through the objective function, so that the design team can identify potential weak links and make timely improvements to ensure the structural safety and reliability of the door. Using the differential evolution algorithm to optimize the objective function not only improves the efficiency of the optimization process, but also can quickly find the optimal solution of the door weight and structural strength in a complex design space, thereby shortening the research and development cycle and reducing the research and development cost. At the same time, the present invention plays an important role in improving automobile safety, and enhances the overall crashworthiness of the vehicle by ensuring the performance of the door under extreme conditions.

[0021] The introduction of the optimization design method of the present invention has promoted the technological progress of the automotive industry, promoted sustainable development, and helped to enhance the market competitiveness of automotive products. Ultimately, based on the design concept of the invention, enterprises can achieve a more efficient and economical automobile manufacturing process, bringing significant economic benefits and social value.

[0022] In a possible implementation manner, in step S1, constructing a virtual door model based on an actual physical door model includes steps S101 to S103: S101, obtaining material properties of each component in an actual vehicle door assembly, and determining a bonding method between the components, wherein the material properties at least include Young's modulus, Poisson's ratio, and yield strength.

[0023] Material property parameters are crucial for evaluating the behavior of a material at different temperatures and under different load conditions. Young's modulus reflects the stiffness of the material, Poisson's ratio describes the ratio of lateral contraction to longitudinal extension of a material under load, and yield strength is the critical point at which a material begins to permanently deform under load.

[0024] The combination methods mainly include welding and bolting. Welding is suitable for connections that bear large loads, while bolting is often used for connections that need to be easy to disassemble and replace. In step S101, the material properties and combination methods of all components must be obtained through field measurements, standard databases or literature references to ensure the accuracy and reliability of the data.

[0025] S102, establishing three-dimensional models of each component according to the size of each component, assembling the three-dimensional models of each component according to the combination method between the components, and constructing a door dynamics model.

[0026] This process is usually carried out through computer-aided design software. Based on the material properties and size data provided in step S101, the various components are assembled in a welding or bolting manner to form a complete door dynamics model. At this time, the connection mechanical properties between the components need to be appropriately set according to the combination method so as to accurately simulate the interaction between the components in the subsequent finite element analysis.

[0027] S103: Combining the material properties of each component and the door dynamics model to form a virtual door model.

[0028] It can be understood that the virtual door model is based on the actual door physical model, so the constructed virtual door model is consistent with the actual door in structure and material properties and conforms to the door dynamics principles.

[0029] In the process of modeling the virtual door model, the anisotropy and nonlinear properties of the material need to be considered in order to more realistically reflect the performance of the door under actual working conditions. For example, when modeling, the door can be regarded as a composite material structure composed of multiple different materials, and the stress-strain relationship of each material can be described by the following formula: , in, is stress, E is Young's modulus, When building a virtual door model, the stress-strain relationship of each component needs to be specifically set according to its material properties. In addition, the contact conditions of the connection area need to be defined to simulate the interface effects caused by welding or bolting.

[0030] Through the above steps S101 to S103, an accurate virtual door model can be generated to provide necessary basic data and parameters for subsequent finite element analysis. This virtual door model will be used to evaluate the dynamic response of the door under different working conditions, thereby providing a basis for optimal design.

[0031] In a possible embodiment, in step S1, Figure 2 As shown, it also includes obtaining the door material parameters within the current temperature range and the force range, specifically including steps S104 to S108: S104, determining the actual temperature of the vehicle door according to the current ambient temperature of the vehicle door, and setting a temperature variation range according to the actual temperature of the vehicle door.

[0032] This step measures and monitors the ambient temperature of the door to determine the actual door temperature. This step needs to take into account the change in ambient temperature and set a temperature change range, which can usually be expressed as: , in, and are the minimum and maximum ambient temperatures respectively. The goal of this process is to simulate the changes in material properties of the door under different temperature conditions for subsequent analysis.

[0033] S105, obtaining the force currently borne by the vehicle door, and setting a force variation range according to the force borne by the vehicle door.

[0034] This step is responsible for measuring the external forces that the door is subjected to during use. These forces may include static loads and dynamic loads. The force condition acquisition unit needs to set the force variation range according to the actual situation, which can usually be expressed as: , in, and In this step, data is obtained through sensors or numerical simulation to ensure that the response characteristics of the door are evaluated under different working conditions.

[0035] S106, constructing a two-dimensional temperature-force space according to the temperature change interval and the force change interval, wherein the space is formed by a temperature axis and a force axis, and the coordinate value of each position point in the space includes the value of the temperature axis and the value of the force axis.

[0036] This step uses the temperature change interval and the force change interval to construct a two-dimensional temperature-force space. This space can be represented as a two-dimensional graph with temperature and force as coordinate axes, which can effectively show the performance changes of materials under different environmental conditions. The two-dimensional temperature-force space can be constructed in the following ways: In this space, N is the number of different values ​​of temperature and force selected, that is, the number of coordinate points selected in the temperature-force space in the subsequent step S107. The construction of this space provides multi-dimensional basic data for subsequent analysis.

[0037] S107, selecting values ​​of N different coordinate points in the temperature-force space to form N groups of ambient temperature and force condition data.

[0038] This step selects the coordinate values ​​of N different points in the temperature-force space constructed by the temperature change range and the force change range, thereby forming N sets of ambient temperature and force conditions. These selected values ​​can be obtained by equal spacing or random sampling to ensure the diversity and representativeness of the sample. For example, if the temperature range is 20 to 80 degrees and the force range is 1000 to 5000 Newtons, 5 temperature values ​​and 5 force values ​​can be set to generate the following combinations: .

[0039] S108, obtaining at least N groups of material parameters regarding temperature and stress conditions corresponding to different material positions on the vehicle door according to the N groups of ambient temperature and stress condition data, wherein the material parameters at least include Young's modulus and yield strength.

[0040] This step uses these N groups of ambient temperature and stress data as variable inputs, and selects material parameters at different material locations in the door as outputs. The output material parameters include Young's modulus and yield strength, which are crucial to the mechanical properties of the material. You can use experimental data or material libraries to query the variation patterns of these material parameters, and associate the parameters based on different temperatures and stress conditions. For example, the relationship between Young's modulus and yield strength and temperature and stress can be obtained through regression analysis:

[0041] , in, and Base temperature Young's modulus and yield strength under and is the temperature influence coefficient, T is the temperature variable, is Young's modulus under the action of temperature variable, is the yield strength under the action of temperature variables. Through the above steps, the changes of materials under different environmental conditions can be specifically evaluated, thereby providing accurate material parameters for subsequent finite element analysis.

[0042] It is understandable that if Figure 2 As shown, steps S104 to S108 of obtaining the door material parameters within the current temperature range and the force range are in no particular order with steps S101 to S103 of constructing the virtual door model in the previous embodiment.

[0043] In a possible embodiment, in step S1, the finite element analysis of the virtual door model is performed based on the door material parameters within the current temperature range and the force range to obtain simulation data of the door weight and structural strength, including: S109, substituting the at least N groups of material parameters related to temperature and stress conditions as simulation conditions into finite element analysis software, the finite element analysis software preferably adopts Ansys software; in the finite element analysis software, performing finite element analysis on the virtual door model according to each group of simulation conditions in turn, evaluating the structural strength of the door under different temperature and stress conditions, and obtaining simulation data of the door weight and structural strength.

[0044] It is understandable that, through finite element analysis, N groups of simulation data of vehicle door weight and structural strength corresponding to N groups of material parameters related to temperature and stress conditions are obtained. These simulation data serve as the original data for optimizing the vehicle door weight and structural strength in subsequent steps S2-S3.

[0045] In a possible implementation manner, in step S2, the objective function is: , in, is the minimum weight of the door obtained by finite element analysis, is the weight coefficient, Obtained through relevant collision simulation tests, The structural strength of the car door obtained by finite element analysis.

[0046] It can be understood that in this step, the door weight and structural strength output by the finite element analysis are constrained by the constructed objective function.

[0047] In a possible implementation manner, step S3 includes steps S301 to S303: S301, constructing a genetic function related to the weight and structural strength of the vehicle door, wherein the genetic function is: , Among them, Y is the result of the genetic function, is the structural strength obtained from the finite element analysis, is the door weight obtained from finite element analysis; S302, inputting the maximum value of the genetic function as a search target into the differential evolution algorithm to search the solution space of the objective function, and continuously iterating the search results until the maximum value of the objective function is obtained; More specifically, the principle of the differential evolution algorithm in this step is: first, generate an initial population according to the solution space of the objective function, then calculate the fitness value of the solution of the objective function according to the maximum value of the genetic function. Then, use mutation, crossover and selection operations to continuously evolve the population. Finally, screen out the optimal solution of the objective function.

[0048] S303, taking the door weight corresponding to the maximum value of the objective function as the optimal door weight, taking the structural strength corresponding to the maximum value of the objective function as the optimal structural strength, and obtaining the door material parameters corresponding to the optimal door weight and the optimal structural strength.

[0049] It can be understood that in this step, the differential evolution algorithm is used in combination with the genetic function and the objective function to optimize the door weight and structural strength simulation data to find the optimal door weight and the corresponding optimal structural strength, and then the temperature and stress conditions corresponding to the optimal door weight and the optimal structural strength are reversely found, and then the corresponding door material parameters are found, and the door material parameters found are substituted into the virtual door model to obtain the optimized virtual door model, thereby realizing the simulation optimization of the door.

[0050] Figure 3 A structural diagram of a dynamic simulation optimization system for a vehicle door based on multi-physics fields provided by an embodiment of the present invention, such as Figure 3 As shown, a dynamic simulation and optimization system for automobile doors based on multi-physics fields includes a construction and simulation module, a constraint module and an optimization module, wherein: A construction and simulation module, used to construct a virtual door model based on the actual physical door model, and perform finite element analysis on the virtual door model based on the door material parameters within the current temperature range and the force range to obtain simulation data of the door weight and structural strength; A constraint module, used to construct an objective function for the simulation data of the door weight and structural strength, wherein the objective function is set such that the door weight meets the minimum weight and the structural strength can pass the automobile crashworthiness test; The optimization module is used to find the optimal door weight and optimal structural strength output by the objective function by using a differential optimization algorithm, so as to obtain the door material parameters corresponding to the optimal door weight and optimal structural strength.

[0051] It can be understood that the automobile door dynamic simulation and optimization system based on multi-physical fields provided by the present invention corresponds to the automobile door dynamic simulation and optimization method based on multi-physical fields provided by the aforementioned embodiments. The relevant technical features of the automobile door dynamic simulation and optimization system based on multi-physical fields can refer to the relevant technical features of the automobile door dynamic simulation and optimization method based on multi-physical fields, which will not be repeated here.

[0052] See also Figure 4 , Figure 4 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 4 As shown, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented: S1, constructing a virtual door model based on the actual physical door model, performing finite element analysis on the virtual door model based on the door material parameters within the current temperature range and the force range, and obtaining simulation data of the door weight and structural strength; S2, constructing an objective function for the simulation data of the door weight and structural strength, wherein the objective function is set such that the door weight meets the minimum weight and the structural strength can pass the automobile crashworthiness test; S3, using a differential optimization algorithm to find the optimal door weight and optimal structural strength output by the objective function, and obtaining the door material parameters corresponding to the optimal door weight and optimal structural strength.

[0053] See also Figure 5 , Figure 5 Schematic diagram of an embodiment of a computer-readable storage medium provided by the present invention. Figure 5 As shown, this embodiment provides a computer-readable storage medium 500, on which a computer program 511 is stored. When the computer program 511 is executed by a processor, the following steps are implemented: S1, constructing a virtual door model based on the actual physical door model, performing finite element analysis on the virtual door model based on the door material parameters within the current temperature range and the force range, and obtaining simulation data of the door weight and structural strength; S2, constructing an objective function for the simulation data of the door weight and structural strength, wherein the objective function is set such that the door weight meets the minimum weight and the structural strength can pass the automobile crashworthiness test; S3, using a differential optimization algorithm to find the optimal door weight and optimal structural strength output by the objective function, and obtaining the door material parameters corresponding to the optimal door weight and optimal structural strength.

[0054] The embodiment of the present invention provides a method, system, electronic device and storage medium for dynamic simulation optimization of automobile doors based on multi-physical fields. First, by establishing a virtual door model, the dynamic characteristics of the actual door can be accurately simulated in a simulation environment, thereby providing reliable data support for the design. Secondly, the present invention can dynamically adjust the material parameters used for finite element analysis according to the current environmental conditions (temperature, stress conditions). This process ensures a comprehensive evaluation of the door performance under different temperatures and stress conditions, and significantly improves the scientificity and accuracy of the door design. In addition, the door is subjected to detailed structural strength analysis and door weight analysis through finite element analysis, and the door weight and structural strength are constrained through the objective function, so that the design team can identify potential weak links and make timely improvements to ensure the structural safety and reliability of the door. Using the differential evolution algorithm to optimize the objective function not only improves the efficiency of the optimization process, but also can quickly find the optimal solution of the door weight and structural strength in a complex design space, thereby shortening the research and development cycle and reducing the research and development cost. At the same time, the present invention plays an important role in improving automobile safety, and enhances the overall crashworthiness of the vehicle by ensuring the performance of the door under extreme conditions. The introduction of this optimization design method has promoted the technological progress of the automotive industry, promoted sustainable development, and helped to enhance the market competitiveness of automotive products. Ultimately, based on the design concept of this invention, companies can achieve a more efficient and economical automobile manufacturing process, bringing significant economic benefits and social value.

[0055] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0056] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0057] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0058] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0059] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0060] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0061] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A dynamic simulation optimization method for automobile doors based on multi-physics fields, characterized in that: include: S1, constructing a virtual door model based on the actual physical door model, performing finite element analysis on the virtual door model based on the door material parameters within the current temperature range and the force range, and obtaining simulation data of the door weight and structural strength; S2, constructing an objective function for the simulation data of the door weight and structural strength, wherein the objective function is set such that the door weight meets the minimum weight and the structural strength can pass the automobile crashworthiness test; S3, using the differential optimization algorithm to find the optimal door weight and optimal structural strength output by the objective function, and obtaining the door material parameters corresponding to the optimal door weight and optimal structural strength.

2. The method for dynamic simulation and optimization of automobile doors based on multi-physics fields according to claim 1 is characterized in that: In step S1, constructing a virtual door model based on the actual physical door model includes: Obtaining material properties of each component in the actual door assembly and determining the bonding method between the components, wherein the material properties at least include Young's modulus, Poisson's ratio and yield strength; Establish three-dimensional models of each component according to its size, assemble the three-dimensional models of each component according to the combination mode between the components, and construct a door dynamics model; The material properties of each component and the door dynamics model are combined to form a virtual door model.

3. The method for dynamic simulation and optimization of automobile doors based on multi-physics fields according to claim 2 is characterized in that: Step S1 also includes obtaining the door material parameters within the current temperature range and the force range, specifically including: Determine the actual door temperature according to the current door ambient temperature, and set the temperature change range according to the actual door temperature; Get the force currently borne by the door, and set the force variation range according to the force borne by the door; Constructing a two-dimensional temperature-force space according to the temperature variation interval and the force variation interval; Selecting values ​​of N different coordinate points in the temperature-force space to form N sets of ambient temperature and force condition data; At least N groups of material parameters regarding temperature and stress conditions corresponding to different material positions on the door are obtained according to the N groups of ambient temperature and stress condition data, wherein the material parameters at least include Young's modulus and yield strength.

4. The method for dynamic simulation and optimization of automobile doors based on multi-physics fields according to claim 3 is characterized in that: In step S1, the finite element analysis is performed on the virtual door model based on the door material parameters within the current temperature range and the force range to obtain simulation data of the door weight and structural strength, including: Substitute the at least N groups of material parameters related to temperature and stress conditions into finite element analysis software as simulation conditions, perform finite element analysis on the virtual door model, evaluate the structural strength of the door under different temperature and stress conditions, and obtain simulation data of the door weight and structural strength.

5. A method for dynamic simulation and optimization of automobile doors based on multi-physical fields according to any one of claims 1 to 4, characterized in that: In step S2, the objective function is: ， in, is the minimum weight of the door, is the weight coefficient, Obtained through relevant collision simulation tests, For the structural strength of the car door.

6. The method for dynamic simulation and optimization of automobile doors based on multi-physics fields according to claim 5, characterized in that: Step S3 includes: Constructing a genetic function about the weight and structural strength of the vehicle door, inputting the maximum value of the genetic function as a search target into the differential evolution algorithm to search the solution space of the objective function, and continuously iterating the search results until the maximum value of the objective function is obtained; The door weight corresponding to the maximum value of the objective function is taken as the optimal door weight, and the structural strength corresponding to the maximum value of the objective function is taken as the optimal structural strength, and the door material parameters corresponding to the optimal door weight and the optimal structural strength are obtained.

7. The method for dynamic simulation and optimization of automobile doors based on multi-physics fields according to claim 6, characterized in that: The genetic function is: ， Among them, Y is the result of the genetic function, is the structural strength obtained from the finite element analysis, is the door weight obtained from finite element analysis.

8. A dynamic simulation and optimization system for automobile doors based on multi-physics fields, characterized in that: include: A construction and simulation module, used to construct a virtual door model based on the actual physical door model, and perform finite element analysis on the virtual door model based on the door material parameters within the current temperature range and the force range to obtain simulation data of the door weight and structural strength; A constraint module, used to construct an objective function for the simulation data of the door weight and structural strength, wherein the objective function is set such that the door weight meets the minimum weight and the structural strength can pass the automobile crashworthiness test; The optimization module is used to find the optimal door weight and optimal structural strength output by the objective function by using a differential optimization algorithm, so as to obtain the door material parameters corresponding to the optimal door weight and optimal structural strength.

9. An electronic device, characterized in that: It comprises a memory and a processor, wherein the processor is used to implement the steps of the automobile door dynamic simulation optimization method based on multi-physical fields as described in any one of claims 1 to 7 when executing the computer management program stored in the memory.

10. A computer-readable storage medium, characterized in that: A computer management program is stored thereon, and when the computer management program is executed by the processor, the steps of the automobile door dynamic simulation optimization method based on multi-physical fields as described in any one of claims 1 to 7 are implemented.

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