Personalized frame lightweight design method and system

Abstract

The invention provides a personalized frame lightweight design method and system, and belongs to the technical field of frame optimization and personalized design. The method comprises the steps of receiving personalized frame design requirements input by a user, determining a target design frame template, analyzing the personalized frame design requirements to obtain frame personalized design parameters, fusing the frame personalized design parameters and a frame data set to obtain a lightweight design data set, and constructing a frame finite element model based on the lightweight design data set; and solving the finite element model of the frame and the like. The system is used for implementing the method. According to the technical scheme, the personalized demand of the user can be fully considered during lightweight design of the frame, and personalized demand parameters of the user can be fused to the greatest extent on the premise of meeting design specifications, so that interaction with the user is realized in the optimization design process of the frame, and the product experience can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of frame optimization and personalized design, and in particular relates to a personalized frame lightweight design method and system, a computer-readable storage medium for implementing the method, a computer program product and an electronic device. Background Art

[0002] Automobile lightweight technology reduces the weight of the car by adopting lightweight materials such as aluminum alloy, magnesium alloy and high-strength steel, as well as reasonable optimization design and manufacturing process. Automobile lightweighting can improve the utilization efficiency of materials, reduce waste and resource waste, and help reduce carbon emissions while maintaining the strength and safety of the vehicle. Lightweight frame is the focus of vehicle lightweight design, and it plays a key role in load bearing and connection. The static and dynamic performance of the frame is closely related to the stiffness, NVH (noise, vibration and shock) and durability of the vehicle. Therefore, the rapid lightweight design of the frame has received widespread attention in the industry.

[0003] In the lightweight design of vehicle frames, commonly used methods include finite element model analysis, response surface method, decision tree method, and deep neural network model method. Among them, the finite element model analysis method is the most mature. For example, the literature (Optimization of Torsional Stiffness for Heavy Commercial Vehicle Chassis Frame[J]. Gawande SH et al.; Automotive Innovation, 2018, 1(4)) established a stiffness characteristic model of the frame beam structure of a heavy commercial vehicle through finite element analysis, and achieved stiffness characteristic optimization under weight constraints through cross-section optimization design; the Chinese invention patent publication CN118656912A proposed a lightweight method for the frame of an unmanned sightseeing vehicle. By establishing a finite element model of the frame and considering multiple working conditions, the frame of the unmanned sightseeing vehicle was optimized by multiple objectives to achieve lightweight design.

[0004] With the popularization of intelligent automobile industry, automobile design will pay more attention to the interactive experience with users. Ordinary users can also participate in the whole process of automobile design and even submit personalized customized products. Personalized design has become an important direction of future automobile design. However, how to maximize the integration of user personalized demand parameters to achieve lightweight design of the frame under the premise of meeting the design specifications has not been reported in relevant technologies. Summary of the invention

[0005] In view of the above technical problems, the present invention proposes a personalized frame lightweight design method, a computer-readable storage medium, a computer program product and an electronic device for implementing the method.

[0006] In a first aspect of the present invention, a personalized frame lightweight design method is proposed, the method is implemented based on electronic equipment; The method comprises the following steps: S110: receiving a personalized frame design requirement input by a user; S120: Determine a target design frame template from a plurality of candidate frame design templates based on the personalized frame design requirement; S130: Analyze the personalized frame design requirement to obtain at least one personalized frame design parameter; S140: Analyze the target design frame template to obtain a frame data set, and fuse the at least one frame personalized design parameter with the frame data set to obtain a lightweight design data set; S150: constructing a frame finite element model based on the lightweight design data set; S160: Solving the frame finite element model, and determining whether the model solution meets preset requirements; If yes, output the frame finite element model; If not, the vehicle frame finite element model is optimized.

[0007] In the step S160, if the model solution result does not meet the preset requirements, the frame finite element model is optimized, which specifically includes: After optimizing at least part of the network architecture in the frame finite element model, re-solving the optimized frame finite element model to determine whether the model solution meets the preset requirements; If the model solution still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements and the process returns to step S110.

[0008] Furthermore, in a second aspect of the present invention, another personalized frame lightweight design method is also provided, the method comprising the following steps: S210: receiving a personalized frame design requirement input by a user; S220: Based on the personalized frame design requirement, determine a target design frame template from a plurality of candidate frame design templates, and analyze the target design frame template to obtain a basic frame data set; S230: Analyze the personalized frame design requirements to obtain N personalized frame design parameters S240: let i=1; S250: Personalized design parameters Fuse it into the basic frame dataset to obtain a lightweight design dataset; S260: constructing a frame finite element model based on the lightweight design data set; S270: Solving the frame finite element model, and determining whether the model solution meets preset requirements; If the model solution meets the preset requirements, set i=i+1; and determine whether i≤N is true; If i≤N holds true, the lightweight design data set is used as a basic frame data set, and the process returns to step S250; If i≤N is not true, the frame finite element model is output.

[0009] The step S230 specifically includes: Analyze the personalized frame design requirements and obtain N personalized frame design parameters; Arrange the N frame personalized design parameters in descending order of priority to obtain the N frame personalized design parameters .

[0010] In the step S270, if the model solution result does not meet the preset requirements, after optimizing at least part of the network architecture in the frame finite element model, the optimized frame finite element model is re-solved to determine whether the model solution result meets the preset requirements; If the model solution still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements and the process returns to step S210.

[0011] If the model solution does not meet the preset requirements, the user will be prompted to abandon the personalized design parameters. ; If the user agrees to give up the personalized design parameters , then let i=i+1; Determine whether i≤N holds; If i≤N holds true, the lightweight design data set is used as a basic frame data set, and the process returns to step S250; If i≤N is not true, the frame finite element model is output.

[0012] The personalized frame lightweight design methods of the above two aspects can be automatically implemented through various forms of electronic devices and computer program instructions; the computer program instructions can be stored in storage media of different forms and loaded into computer electronic devices for execution.

[0013] Therefore, in the third aspect of the present invention, a computer-readable storage medium is also provided for storing computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes the personalized frame lightweight design method of the above two aspects.

[0014] In a fourth aspect of the present invention, a computer device is also proposed, comprising a processor and a memory, wherein the memory is used to store instructions, and the processor is used to call the instructions in the memory, so that the computer device executes the personalized frame lightweight design method of the above two aspects.

[0015] In a fifth aspect of the present invention, a computer program product is also proposed, the product comprising a computer program, and when the computer program is executed, the personalized frame lightweight design method of the above two aspects is implemented.

[0016] In order to realize the personalized frame lightweight design method of the first aspect, in a sixth aspect of the present invention, a personalized frame lightweight design system is also proposed, the system comprising: Receiving unit: receiving the personalized frame design requirements input by the user; A target design frame template matching unit: determines a target design frame template from a plurality of candidate frame design templates based on the personalized frame design requirements; An analysis unit: analyzing the personalized frame design requirement to obtain at least one personalized frame design parameter; Fusion unit: analyzing the target design frame template to obtain a frame data set, fusing the at least one frame personalized design parameter with the frame data set to obtain a lightweight design data set; A finite element model building unit: building a frame finite element model based on the lightweight design data set; Finite element model solving unit: solving the frame finite element model and judging whether the model solving result meets the preset requirements; If yes, output the frame finite element model; If not, the vehicle frame finite element model is optimized.

[0017] If the model solution result does not meet the preset requirements, the frame finite element model is optimized, specifically including: After optimizing at least part of the network architecture in the frame finite element model, re-solving the optimized frame finite element model to determine whether the model solution meets the preset requirements; If the model solution still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements.

[0018] In order to realize the personalized frame lightweight design method of the second aspect, in a seventh aspect of the present invention, a personalized frame lightweight design system is also proposed, the system comprising: Receiving unit: receiving the personalized frame design requirements input by the user; A matching and analyzing unit: based on the personalized frame design requirement, determines a target design frame template from a plurality of candidate frame design templates, and analyzes the target design frame template to obtain a basic frame data set; Analysis unit: analyzes the personalized frame design requirements and obtains N frame personalized design parameters A lightweight design unit, wherein the lightweight design unit performs the following steps: Step 1: Let i=1; Step 2: Personalize the design parameters Fuse it into the basic frame dataset to obtain a lightweight design dataset; Step 3: Construct a frame finite element model based on the lightweight design data set; Step 4: Solve the finite element model of the frame and determine whether the model solution meets the preset requirements; If the model solution meets the preset requirements, set i=i+1; and determine whether i≤N is true; If i≤N holds true, the lightweight design data set is used as the basic frame data set, and the process returns to Step 2; If i≤N is not true, the frame finite element model is output.

[0019] The technical solution of the present invention can fully consider the personalized needs of users when designing a lightweight frame, and can integrate the personalized demand parameters of users to the maximum extent under the premise of meeting the design specifications, so that the frame optimization design process can interact with the user and improve the product experience.

[0020] Further advantages of the present invention will be further reflected in detail in the specific embodiments section in conjunction with the drawings of the specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 It is a main flow diagram of a personalized frame lightweight design method according to an embodiment of the present invention; Figure 2 It is a main flow diagram of a personalized frame lightweight design method according to another embodiment of the present invention; Figure 3It is a schematic diagram of the original target design frame template and the frame finite element model after personalized design; Figure 4 It is a schematic diagram of the frame finite element model output after the user adjusts the personalized frame design requirements; Figure 5 It is a schematic diagram of the functional units of a personalized frame lightweight design system according to an embodiment of the present invention; Figure 6 It is a schematic diagram of the functional unit composition of a personalized frame lightweight design system according to another embodiment of the present invention. DETAILED DESCRIPTION

[0023] First of all, it should be pointed out that the embodiments of the personalized frame lightweight design method mentioned in this section can be implemented through computer programs on electronic devices and systems equipped with memory and processors. The electronic devices and systems can be in the form of physical machines, virtual machines, servers, clusters or any combination thereof.

[0024] Preferably, the specific form of the electronic device may also be a human-computer interaction terminal, and the human-computer interaction terminal may be a desktop terminal, a smart handheld terminal, a mobile terminal, etc. with a human-computer interaction interface.

[0025] See first Figure 1 , Figure 1 It is a flow chart of a personalized frame lightweight design method according to an embodiment of the present invention. Figure 1 The method includes steps S110-S160, and each step is specifically implemented as follows:

[0026] S110: receiving a personalized frame design requirement input by a user; S120: Determine a target design frame template from a plurality of candidate frame design templates based on the personalized frame design requirement; S130: Analyze the personalized frame design requirement to obtain at least one personalized frame design parameter; S140: Analyze the target design frame template to obtain a frame data set, and fuse the at least one frame personalized design parameter with the frame data set to obtain a lightweight design data set; S150: constructing a frame finite element model based on the lightweight design data set; S160: Solving the frame finite element model, and determining whether the model solution meets preset requirements; If yes, output the frame finite element model; If not, the vehicle frame finite element model is optimized.

[0027] If the model solution result does not meet the preset requirements, the frame finite element model is optimized, specifically including: After optimizing at least part of the network architecture in the frame finite element model, re-solving the optimized frame finite element model to determine whether the model solution meets the preset requirements; If the model solution still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements and the process returns to step S110.

[0028] Next, through a schematic description example, Figure 1 Each step of the method is described in detail.

[0029] Step S110: receiving the personalized frame design requirements input by the user.

[0030] It is understandable that the users here are ordinary users. Different from professional frame designers, ordinary users generally use natural language to describe their own personalized frame design requirements.

[0031] As an example, for ordinary users, the different parts of the entire vehicle frame can be described as the front, body, rear, chassis, driver's seat, co-driver's seat, rear space, etc., while professional designers may use professional terms such as "A-pillar", "engine hood", and "luggage compartment".

[0032] As an example, the personalized frame design requirements input by ordinary users may be: "I want the front of the car to be square with a point; the chassis to be no less than XX1cm; the passenger seat to be replaced with a backless platform pad"; Next, the process proceeds to step S120: based on the personalized frame design requirement, a target design frame template is determined from a plurality of candidate frame design templates.

[0033] A vehicle frame design template database may be pre-built to store design templates for different types of vehicle frames.

[0034] As an example, a frame design template database is shown in Table 1 below: Serial number Front shape Rear shape Chassis height Co-pilot Template A Adjustable Not adjustable (XX1, XX2) internally adjustable Not customizable Template B Not adjustable Not adjustable (XX0, XX1) adjustable Customizable Template C Adjustable Adjustable (XX1, XX3) internally adjustable Customizable Template D Not adjustable Adjustable Not adjustable Not customizable Table 1 It can be understood that each frame design template corresponds to an original basic finite element model in the frame design template database, for example Figure 3 and Figure 4 Left picture.

[0035] The basic finite element model connects the frame with hollow pipes of different thickness and length. The main structure of the frame is a spatial triangular structure, including a small number of rectangular and polygonal structures (the circle is fitted with an N-gon).

[0036] Continuing with the above example, it can be seen that based on the personalized frame design requirements ("I want the front of the car to be square with a point; the chassis should not be less than XX1cm; the co-pilot seat should be replaced with a backless platform pad"), the target design frame template is determined to be template C from multiple candidate frame design templates; Next, step S130 is performed: analyzing the personalized frame design requirement to obtain at least one frame personalized design parameter; Continuing with the above example, the frame personalized design parameter set P can be: Front of the car: square (rectangular right angle 90°) + middle sharp angle (triangular vertex angle 150°); Chassis height: >XX1cm; Co-pilot seat: circle (diameter YYCM) (in actual design, the circle is fitted with an N-gon).

[0037] Preferably, the process of analyzing the personalized frame design requirements and deriving at least one personalized frame design parameter can be completed by a professional designer, or a parameter recognition model can be pre-trained, and the personalized frame design requirements can be input into the pre-trained parameter recognition model, and the pre-trained parameter recognition model can output at least one personalized frame design parameter.

[0038] Preferably, the training samples of the pre-trained parameter recognition model are paired "personalized frame design requirement text + standard design parameters".

[0039] At this point, the target design frame template C and the frame personalized design parameter set P have been obtained, and the personalized fusion and design stage is entered, that is, step S140: the target design frame template is analyzed to obtain a frame data set, and the at least one frame personalized design parameter is integrated with the frame data set to obtain a lightweight design data set.

[0040] Preferably, the analyzing the target design frame template to obtain a frame data set specifically includes: Based on the target design frame template C to obtain the corresponding basic finite element model Lc; Performing DOE (Design of Experiments) analysis on the basic finite element model Lc to obtain frame performance table data as an original frame data set DLc; Then, the frame personalized design parameter set P is fused with the original frame data set DLc to obtain a lightweight design data set DPc; Preferably, when performing DOE (Design of Experiments) analysis on the basic finite element model Lc and obtaining the frame performance table data, multiple characteristic points and characteristic variables are selected from the basic finite element model Lc according to engineering design experience, and then the frame performance table data is derived; The selected multiple feature points and feature variables at least include feature points corresponding to the frame personalized design parameter set. Continuing with the above example, the feature points corresponding to the frame personalized design parameter set include the front of the vehicle, the chassis, and the co-pilot seat. At this time, the frame personalized design parameters corresponding to the front of the vehicle, the chassis and the co-pilot seat can be updated to the "frame standard design parameters corresponding to the front of the vehicle, the chassis and the co-pilot seat" in the frame performance table data, that is, the lightweight design data set DPc is obtained; Then, step S150 can obtain the updated frame finite element model Lc '; That is, step S150 constructs a frame finite element model Lc' based on the lightweight design data set.

[0041] Next, the updated finite element model solving and optimization phase is entered, namely step S160.

[0042] Preferably, the finite element model solving and optimization stage of step S160 specifically includes: (1) Determine the material properties of each element in the model, such as elastic modulus, density, Poisson’s ratio, etc. These properties can truly reflect the performance of the material and are crucial to the behavior and response of the model.

[0043] (2) Meshing: The structure is discretized into a finite number of small elements, called finite elements. This process is called meshing. The meshing needs to take into account the complexity of the geometric shape and the accuracy requirements of the analysis. The quality and accuracy of the meshing results have a great impact on the calculation results.

[0044] (3) Establish loading and boundary conditions: Define loading conditions and boundary conditions in the model. Loading conditions may include force, pressure, temperature, etc., which need to be added according to actual conditions. Boundary conditions specify the constraints and conditions at the boundaries of the model.

[0045] (4) Solution: Solving the finite element model by numerical methods. This involves solving linear or nonlinear equations, usually using computer software.

[0046] (5) Result analysis: After obtaining the solution of the model, the results are analyzed and interpreted. This may involve stress analysis, deformation analysis, displacement analysis, etc. to evaluate whether the performance and behavior of the structure meet the requirements.

[0047] (6) Verification and optimization: Verify the simulation results and compare them with experimental data or theoretical predictions. If necessary, the model can be optimized to improve its performance or meet design requirements.

[0048] In one embodiment, if the frame finite element model is solved through the above steps (1)-(6), and it is determined that the model solution results meet the preset requirements (for example, the performance and behavior of the structure meet the requirements, the simulation results match the experimental data or the results of theoretical predictions, etc.), the frame finite element model can be output, that is, all the user's personalized requirements can be met, and the personalized designed frame finite element model is output.

[0049] Figure 3 It is a schematic diagram of the original target design frame template and the frame finite element model after personalized design. Figure 3 The left picture is a schematic diagram of the original basic finite element model Lc. Figure 3 The right picture is a schematic diagram of the frame finite element model output after integrating the user's personalized demand parameters ( Figure 3 The right figure schematically indicates the update feature through arrows).

[0050] In another example, if the frame finite element model is solved through the above steps (1) to (6), and it is determined that the model solution result does not meet the preset requirements (for example, the performance and behavior of the structure do not meet the requirements, the simulation results do not match the experimental data or the results of theoretical predictions, etc.), it is necessary to optimize at least part of the network architecture in the frame finite element model, and then re-solve the optimized frame finite element model to determine whether the model solution result meets the preset requirements; If the model solution still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements and the process returns to step S110.

[0051] In this scenario, it means that although the user submits a personalized frame design requirement, the original basic finite element model Lc that meets the user's personalized frame design requirement can be matched in the frame design template database; however, the frame finite element model Lc' updated after data fusion cannot pass the design specifications. These design specifications include but are not limited to collision tests, pressure tests, stiffness tests, etc. Therefore, the updated frame finite element model Lc' cannot be used as a frame lightweight design solution.

[0052] At this time, at least part of the network structure in the frame finite element model can be adjusted, such as adding connecting rods, adjusting material properties, etc., and re-solving the optimized frame finite element model to determine whether the model solution meets the preset requirements; if so, output the frame finite element model; If the model solution still does not meet the preset requirements, it means that under the current conditions, the personalized needs of the user cannot be objectively met. Then the user is prompted to adjust the personalized frame design requirements and the process returns to step S110.

[0053] In one scenario, the user adjusts the personalized frame design requirements and re-executes Figure 1 After the method is implemented, a finite element model of the frame under a new personalized design can be output.

[0054] Figure 4 This is the schematic diagram of the frame finite element model output after the user adjusts the personalized frame design requirements. In this schematic diagram, the user no longer requires a "square front design with a point", so the frame finite element model under the adjusted personalized design can be realized ( Figure 4 right).

[0055] As you can see, Figure 1 The method described is to comprehensively consider multiple frame personalized design parameters of the user, hoping to be able to perform personalized design while satisfying all frame personalized design parameters, so as to meet the personalized needs of the user to the greatest extent.

[0056] In extreme cases, Figure 1 In the method, step S160 solves the frame finite element model for the first time. When it is determined that the model solution result does not meet the preset requirements, at least part of the network architecture in the frame finite element model is optimized, and then the optimized frame finite element model is solved again to determine whether the model solution result meets the preset requirements; if the model solution result still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements; return to step S110 and re-execute the method. At this time, when the method is executed again to step S160, the model solution result may still not meet the preset requirements, which means that the personalized frame lightweight design solution still fails after repeated attempts, which will also bring a bad experience to the user.

[0057] To this end, the inventors further noted that although the limitations of design specifications (design specifications include but are not limited to collision tests, pressure tests, stiffness tests, etc.) often cannot fully (and simultaneously) meet multiple personalized needs of users, that is, the tolerance for some of the personalized requirements is relatively high.

[0058] Therefore, in order to improve the success rate of personalized frame lightweight design solutions and further enhance user experience, Figure 2 The embodiment of the present invention provides a more preferred personalized frame lightweight design method.

[0059] Figure 2 The flowchart includes steps S210-S270, and each step is specifically implemented as follows: S210: receiving a personalized frame design requirement input by a user; S220: Based on the personalized frame design requirement, determine a target design frame template from a plurality of candidate frame design templates, and analyze the target design frame template to obtain a basic frame data set; S230: Analyze the personalized frame design requirements to obtain N personalized frame design parameters S240: let i=1; S250: Personalized design parameters Fuse it into the basic frame dataset to obtain a lightweight design dataset; S260: constructing a frame finite element model based on the lightweight design data set; S270: Solving the frame finite element model, and determining whether the model solution meets preset requirements; If the model solution meets the preset requirements, set i=i+1; and determine whether i≤N is true; If i≤N holds true, the lightweight design data set is used as a basic frame data set, and the process returns to step S250; If i≤N is not true, the frame finite element model is output.

[0060] It can be seen that Figure 1 Compared with the embodiment, Figure 2 The main improvement starts from step S240, that is, after obtaining N frame personalized design parameters, Figure 2 The embodiment is to try to start integrating the frame personalized design parameters one by one, and Figure 1 An implementation example is to package and merge N frame personalized design parameters.

[0061] Obviously, Figure 2 The integration of the improvement methods one by one can greatly improve the success rate of the output of personalized frame lightweight design solutions, because the model and design specifications have a higher tolerance for some personalized requirements.

[0062] Furthermore, when the user has multiple frame personalized design parameters, the preference for each frame personalized design parameter may be different. Therefore, in a more preferred embodiment, step S230 specifically includes: Analyze the personalized frame design requirements and obtain N personalized frame design parameters; Arrange the N frame personalized design parameters in descending order of priority to obtain the N frame personalized design parameters .

[0063] when When the priorities are arranged in descending order, it can be seen that the personalized design parameter T1 with the highest user preference will be integrated and considered first, further improving the user experience.

[0064] On the other hand, if the current personalized parameter Ta cannot be integrated (the improved personalized frame lightweight design scheme cannot be output), further user guidance can be given to continue to consider other personalized parameters Tb (Ta≠Tb), so as to continue to improve the output success rate of the personalized frame lightweight design scheme.

[0065] Specifically, if the model solution does not meet the preset requirements, the user is prompted to abandon the personalized design parameters; If the user agrees to give up the personalized design parameters, let i=i+1; Determine whether i≤N holds; If i≤N holds true, the lightweight design data set is used as a basic frame data set, and the process returns to step S250; If i≤N is not true, the frame finite element model is output.

[0066] It can be seen that compared with Figure 1 , Figure 2 The implementation example is further improved to attempt to integrate personalized design parameters one by one, and if the current personalized design parameter cannot be met, continue to integrate the next personalized design parameter. This can maximize the integration of user personalized demand parameters under the premise of meeting the design specifications, and meet the user's more personalized frame design needs as much as possible, further enhancing the personalized interactive experience.

[0067] The aforementioned personalized frame lightweight design method can be automatically implemented through various forms of electronic devices through computer-readable program instructions; the computer-readable program instructions can be stored in storage media of different forms and loaded into computer electronic devices for execution.

[0068] According to an exemplary implementation of the present disclosure, a computer-readable storage medium is provided, on which computer-executable instructions are stored, wherein the computer-executable instructions are executed by a processor to implement the method described above. According to an exemplary implementation of the present disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method described above.

[0069] and Figure 1 , Figure 2 Corresponding to the method embodiment, Figure 5-Figure 6 The embodiments of the present invention respectively provide a corresponding schematic diagram of the functional unit composition of a personalized frame lightweight design system.

[0070] exist Figure 5 In the figure, a personalized frame lightweight design system using an integrated bus architecture is shown, which includes a receiving unit, an analyzing unit, a fusion unit, a target design frame template matching unit, a finite element model building unit, and a finite element model solving unit; the receiving unit, the analyzing unit, the fusion unit, the target design frame template matching unit, the finite element model building unit, and the finite element model solving unit are all connected to the integrated bus; Figure 5 The functions of each functional component are as follows: Receiving unit: receiving the personalized frame design requirements input by the user; A target design frame template matching unit: determines a target design frame template from a plurality of candidate frame design templates based on the personalized frame design requirements; An analysis unit: analyzing the personalized frame design requirement to obtain at least one personalized frame design parameter; Fusion unit: analyzing the target design frame template to obtain a frame data set, fusing the at least one frame personalized design parameter with the frame data set to obtain a lightweight design data set; A finite element model building unit: building a frame finite element model based on the lightweight design data set; Finite element model solving unit: solving the frame finite element model and judging whether the model solving result meets the preset requirements; If yes, output the frame finite element model; If not, the vehicle frame finite element model is optimized.

[0071] If the model solution result does not meet the preset requirements, the frame finite element model is optimized, specifically including: After optimizing at least part of the network architecture in the frame finite element model, re-solving the optimized frame finite element model to determine whether the model solution meets the preset requirements; If the model solution still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements.

[0072] Figure 6 Further embodiments and examples of the personalized frame lightweight design system are provided. Figure 2 Corresponding to the method embodiment, the system includes: Receiving unit: receiving the personalized frame design requirements input by the user; A matching and analyzing unit: based on the personalized frame design requirement, determines a target design frame template from a plurality of candidate frame design templates, and analyzes the target design frame template to obtain a basic frame data set; Analysis unit: analyzes the personalized frame design requirements and obtains N frame personalized design parameters A lightweight design unit, wherein the lightweight design unit performs the following steps: Step 1: Let i=1; Step 2: Personalize the design parameters Fuse it into the basic frame dataset to obtain a lightweight design dataset; Step 3: Construct a frame finite element model based on the lightweight design data set; Step 4: Solve the finite element model of the frame and determine whether the model solution meets the preset requirements; If the model solution meets the preset requirements, set i=i+1; and determine whether i≤N is true; If i≤N holds true, the lightweight design data set is used as the basic frame data set, and the process returns to Step 2; If i≤N is not true, the frame finite element model is output.

[0073] The technical solution of the present invention can fully consider the personalized needs of users when designing a lightweight frame, and can integrate the personalized demand parameters of users to the maximum extent under the premise of meeting the design specifications, so that the frame optimization design process can interact with the user and improve the product experience.

[0074] For other technologies, principles, algorithms or models not elaborated in detail in this application, please refer to the prior art.

[0075] In the above-mentioned embodiment section, the present invention provides multiple embodiments, each of which can constitute an independent technical solution and may contribute to the prior art and solve corresponding technical problems. However, it should be pointed out that different embodiments can be combined with each other without violating logic; at the same time, each embodiment can solve at least one technical problem, but it is not required that each individual embodiment solves multiple or all technical problems.

[0076] At the same time, in the specific implementation of this application, if user-related data is involved, when the embodiment of this application is applied to a specific product or technology, the user's permission or consent must be obtained, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0077] The above descriptions of various implementations of the present disclosure are exemplary, non-exhaustive, and not limited to the disclosed implementations. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described implementations. The selection of terms used herein is intended to best explain the principles of the implementations, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the various implementations disclosed herein.

Claims

1. A personalized frame lightweight design method, characterized in that: The method comprises the following steps: S110: receiving a personalized frame design requirement input by a user; S120: Determine a target design frame template from a plurality of candidate frame design templates based on the personalized frame design requirement; S130: Analyze the personalized frame design requirement to obtain at least one personalized frame design parameter; S140: Analyze the target design frame template to obtain a frame data set, and fuse the at least one frame personalized design parameter with the frame data set to obtain a lightweight design data set; S150: constructing a frame finite element model based on the lightweight design data set; S160: Solving the frame finite element model, and determining whether the model solution meets preset requirements; If yes, output the frame finite element model; If not, the vehicle frame finite element model is optimized.

2. A personalized frame lightweight design method as claimed in claim 1, characterized in that: In step S160, if the model solution result does not meet the preset requirements, the frame finite element model is optimized, specifically including: After optimizing at least part of the network architecture in the frame finite element model, re-solving the optimized frame finite element model to determine whether the model solution meets the preset requirements; If the model solution still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements and the process returns to step S110.

3. A personalized frame lightweight design method, characterized in that: The method comprises the following steps: S210: receiving a personalized frame design requirement input by a user; S220: Based on the personalized frame design requirement, determine a target design frame template from a plurality of candidate frame design templates, and analyze the target design frame template to obtain a basic frame data set; S230: Analyze the personalized frame design requirements to obtain N personalized frame design parameters S240: let i=1; S250: Personalized design parameters Fuse it into the basic frame dataset to obtain a lightweight design dataset; S260: constructing a frame finite element model based on the lightweight design data set; S270: Solving the frame finite element model, and determining whether the model solution meets preset requirements; If the model solution meets the preset requirements, let i=i+1; Determine whether i≤N holds; If i≤N holds true, the lightweight design data set is used as a basic frame data set, and the process returns to step S250; If i≤N is not true, the frame finite element model is output.

4. A personalized frame lightweight design method as claimed in claim 3, characterized in that: In step S270, if the model solution result does not meet the preset requirements, after optimizing at least part of the network architecture in the frame finite element model, the optimized frame finite element model is re-solved to determine whether the model solution result meets the preset requirements; If the model solution still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements and the process returns to step S210.

5. A personalized frame lightweight design method as claimed in claim 3, characterized in that: If the model solution does not meet the preset requirements, the user will be prompted to abandon the personalized design parameters. ; If the user agrees to give up the personalized design parameters , then let i=i+1; Determine whether i≤N holds; If i≤N holds true, the lightweight design data set is used as a basic frame data set, and the process returns to step S250; If i≤N is not true, the frame finite element model is output.

6. A personalized frame lightweight design method as claimed in claim 3, characterized in that: The step S230 specifically includes: Analyze the personalized frame design requirements and obtain N personalized frame design parameters; Arrange the N frame personalized design parameters in descending order of priority to obtain the N frame personalized design parameters .

7. A personalized frame lightweight design system, characterized in that: The system comprises: Receiving unit: receiving the personalized frame design requirements input by the user; A target design frame template matching unit: based on the personalized frame design requirement, determining a target design frame template from a plurality of candidate frame design templates; An analysis unit: analyzing the personalized frame design requirement to obtain at least one personalized frame design parameter; Fusion unit: analyzing the target design frame template to obtain a frame data set, fusing the at least one frame personalized design parameter with the frame data set to obtain a lightweight design data set; A finite element model building unit: building a frame finite element model based on the lightweight design data set; Finite element model solving unit: solving the frame finite element model and judging whether the model solving result meets the preset requirements; If yes, output the frame finite element model; If not, the vehicle frame finite element model is optimized.

8. A personalized frame lightweight design system as claimed in claim 7, characterized in that: If the model solution result does not meet the preset requirements, the frame finite element model is optimized, specifically including: After optimizing at least part of the network architecture in the frame finite element model, re-solving the optimized frame finite element model to determine whether the model solution meets the preset requirements; If the model solution still does not meet the preset requirements, the user is prompted to adjust the personalized frame design requirements.

9. A personalized frame lightweight design system, characterized in that: The system comprises: Receiving unit: receiving the personalized frame design requirements input by the user; A matching and analyzing unit: based on the personalized frame design requirement, determines a target design frame template from a plurality of candidate frame design templates, and analyzes the target design frame template to obtain a basic frame data set; Analysis unit: analyzes the personalized frame design requirements and obtains N frame personalized design parameters A lightweight design unit, wherein the lightweight design unit performs the following steps: Step 1: Let i=1; Step 2: Personalize the design parameters Fuse it into the basic frame dataset to obtain a lightweight design dataset; Step 3: Construct a frame finite element model based on the lightweight design data set; Step 4: Solve the finite element model of the frame and determine whether the model solution meets the preset requirements; If the model solution meets the preset requirements, set i=i+1; and determine whether i≤N is true; If i≤N holds true, the lightweight design data set is used as the basic frame data set, and the process returns to Step 2; If i≤N is not true, the frame finite element model is output.

10. A computer program product, comprising a computer program or computer executable instructions, which, when executed by a processor, implements a personalized frame lightweight design method as claimed in any one of claims 1 to 6.

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