Integrated die-casting floor multi-objective optimization method and device, terminal and storage medium

Abstract

The application belongs to the technical field of automobiles, and particularly relates to an integrated die-casting floor multi-target optimization method, device, terminal and storage medium. The optimization method comprises the following steps: 1. a finite element model of the integrated die-casting floor is established, and the performance of the vehicle body strength, overall stiffness, mode and rear shock absorber fixing point is analyzed; 2. a topology optimization space is determined according to the position of the shock absorber and the distance between the candidate fixing seat and the wrapping frame; 3. topology optimization analysis is performed on the topology optimization space; 4. a planar parameterized model connected with the rear suspension fixing seat and the shock absorber is established; 5. the finite element model and the parameterized model are coupled; 6. parameter optimization is performed on the coupled model; and 7. whether the optimized parameters meet the performance requirements is checked. The application optimizes the structure of the key position of the integrated die-casting floor, so that the final optimization scheme meets the vehicle body strength and other performance requirements and has the lowest weight. The application of the process can reduce the repeated checking cycles, save time and manpower.

Description

Technical Field

[0001] This invention belongs to the field of automotive technology, specifically a method, apparatus, terminal, and storage medium for multi-objective optimization of an integrated die-cast floor. Background Technology

[0002] With the development of the automotive industry, modularization and fewer parts in vehicle assembly have become a trend. A one-piece die-cast floor can integrate the rear floor into a die-cast aluminum structure. Using a one-piece die-cast structure for the rear floor not only reduces the number of assembly parts but also lowers the vehicle's weight. However, existing technologies only optimize small cast aluminum structures through topology optimization to achieve weight reduction, without a method for forward design of the one-piece die-cast floor. Furthermore, the yield strength of die-cast aluminum is much lower than that of high-strength steel (where high-strength steel is mostly used in sheet metal near the suspension mount to meet strength requirements). Therefore, to meet the vehicle's strength requirements at key stress points (rear suspension mount), the one-piece die-cast floor requires repeated optimization of the design, which is time-consuming. Summary of the Invention

[0003] This invention provides a multi-objective optimization method, device, terminal, and storage medium for an integrated die-cast floor, which optimizes the integrated die-cast structure to meet the vehicle body strength and other performance requirements with the lowest possible mass, thus solving the aforementioned problems existing in the optimization of small cast aluminum structures.

[0004] The technical solution of this invention is described below in conjunction with the accompanying drawings:

[0005] According to a first aspect of the present invention, a multi-objective optimization method for an integral die-cast floor is provided, comprising the following steps:

[0006] Step 1: Build a finite element model of the integrated die-cast floor and analyze the vehicle body strength, overall stiffness, modal analysis, and performance of the rear shock absorber mounting points;

[0007] Step 2: Determine the topology optimization space based on the location of the shock absorber and the distance between the candidate mounting base and the package frame;

[0008] Step 3: Perform topology optimization analysis on the topology optimization space determined in Step 2;

[0009] Step 4: Construct a planar parametric model connecting the rear suspension mounting base and the shock absorber;

[0010] Step 5: Couple the finite element model built in Step 1 with the parametric model built in Step 4;

[0011] Step 6: Optimize the parameters of the coupled model from Step 5;

[0012] Step 7: Verify whether the parameters optimized in Step 6 meet the performance requirements.

[0013] Furthermore, in step one, the integral die-cast floor is modeled using second-order tetrahedral elements, wherein the mesh size of the integral die-cast floor is 8mm.

[0014] Furthermore, in step two, the lower boundary of the topology optimization space does not interfere with the spring damper, and the upper boundary does not interfere with the suspension mounting and the package frame.

[0015] Step three, topology optimization analysis of the topology optimization space, is based on the vehicle body strength condition, with the goal of minimizing mass and the constraint that the maximum stress is below the stress limit.

[0016] Furthermore, in step four, based on the topology optimization results of step three and by establishing a basic parametric model using SFE software, the corresponding position variables and cross-sectional variables are entered, and the ranges of the corresponding variables are determined to provide input conditions for subsequent optimization. The ranges of the position variables and cross-sectional variables are determined based on the arrangement of the shock absorbers and the enclosure structure of the vehicle model. When the position variables and cross-sectional variables change within the specified range, the generated parametric model will not interfere with the structure of the shock absorbers and enclosure of the vehicle model. Additionally, the ranges of each variable in the parametric model need to be determined.

[0017] Furthermore, in step four, the planar parametric model connecting the rear suspension mounting base and the shock absorber has the same boundary as the finite element model built in step one, and the node number is the same as the node number of the finite element model.

[0018] Furthermore, the specific method for step six is ​​as follows:

[0019] 1) The optimized Latin hypercube algorithm is used to determine the variable matrix corresponding to each sample;

[0020] 2) Based on the variable matrix and using Isight software to drive parametric modeling software to perform network division, generate the required sample space, and analyze the vehicle body strength, overall stiffness, modal characteristics, and rear shock absorber fixed point performance of the sample space;

[0021] 3) Constructing the proxy model using the Kriging method:

[0022]

[0023] In the formula: λ i Let x0 be the unobserved point that needs to be estimated, and x1, x2, ... x be the weighting coefficients to be determined. N For the surrounding observation points;

[0024] 4) Use the adjustment coefficient to evaluate the fitting accuracy of the approximate model. The formula for the adjustment coefficient is shown below. When the adjustment coefficient is greater than 0.9, the accuracy of the surrogate model is considered to meet the condition.

[0025]

[0026] In the formula: n is the number of test sample points; y i Let be the simulated value of the i-th response; The approximate model prediction values ​​for the i-th response; This represents the average value of the simulation results.

[0027] 5) Based on the surrogate model, the multi-island genetic algorithm is used for optimization analysis to obtain the optimal combination of variables.

[0028] According to a second aspect of the present invention, a multi-objective optimization apparatus for an integrated die-cast floor is provided, comprising:

[0029] The first module is used to create a finite element model of the integrated die-cast floor and analyze the vehicle body strength, overall stiffness, modal characteristics, and performance of the rear shock absorber mounting points.

[0030] The topology optimization space module is used to determine the topology optimization space based on the position of the shock absorber and the distance between the candidate mounting base and the package frame;

[0031] The topology optimization analysis module is used to perform topology optimization analysis on a defined topology optimization space.

[0032] The second module is used to create a planar parametric model of the rear suspension mount and the shock absorber.

[0033] The coupling module is used to couple the finite element model and the parametric model;

[0034] The optimization module is used to optimize the parameters of the coupled model;

[0035] The verification module is used to verify whether the optimized parameters meet the performance requirements.

[0036] According to a third aspect of the present invention, a terminal is provided, comprising:

[0037] One or more processors;

[0038] Memory for storing the one or more processor-executable instructions;

[0039] Wherein, the one or more processors are configured as follows:

[0040] Perform the method described in the first aspect of the embodiments of the present invention.

[0041] According to a fourth aspect of the present invention, a non-transitory computer-readable storage medium is provided, wherein when instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to perform the method described in the first aspect of the present invention.

[0042] According to a fifth aspect of the present invention, an application product is provided that, when the application product is running on a terminal, causes the terminal to execute the method described in the first aspect of the present invention.

[0043] The beneficial effects of this invention are as follows:

[0044] This invention optimizes the structure of key areas in a one-piece die-cast floor, ensuring that the final optimized solution meets vehicle body strength and other performance requirements while minimizing weight. Applying this process reduces the number of repeated calculations, saving time and manpower. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a flowchart illustrating the multi-objective optimization method for the integrated die-cast flooring described in this invention.

[0047] Figure 2 This is a schematic diagram of the multi-objective optimization device for the integrated die-cast floor described in this invention;

[0048] Figure 3 This is a schematic block diagram of a terminal structure. Detailed Implementation

[0049] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0050] Example 1

[0051] Figure 1 The multi-objective optimization method for integrated die-cast flooring provided in Embodiment 1 of the present invention is applicable to the multi-objective optimization of integrated die-cast flooring. This method can be executed by the multi-objective optimization device for integrated die-cast flooring in the embodiments of the present invention, which can be implemented in software and / or hardware.

[0052] A multi-objective optimization method for an integral die-cast floor includes the following steps:

[0053] Step 1: Build a finite element model of the integrated die-cast floor, analyze the body strength, overall stiffness, modal analysis, and performance of the rear shock absorber fixing points, and obtain the performance analysis results of the initial data as the basis for optimization. Among them, in order to improve the analysis efficiency and subsequent optimization efficiency, the mesh size of the integrated die-cast floor is 8mm (except for the wall thickness). When performing strength analysis, second-order tetrahedral elements are used for modeling to improve the analysis accuracy.

[0054] Step 2: Determine the topology optimization space based on the location of the shock absorber and the distance between the candidate mounting base and the package frame;

[0055] The topology optimization space depends downward on the arrangement of the spring dampers, with the lower boundary not interfering with the spring dampers, and upward on the space between the suspension mount and the package rack, with the upper boundary not interfering with the suspension mount and the package rack.

[0056] Step 3: Perform topology optimization analysis on the topology optimization space determined in Step 2;

[0057] Topology optimization analysis of the topology optimization space is based on the vehicle body strength condition, with the goal of minimizing mass and the constraint that the maximum stress is lower than the stress limit.

[0058] Step 4: Construct a planar parametric model connecting the rear suspension mounting base and the shock absorber;

[0059] When building the parametric model, a basic parametric model is established with reference to the topology optimization results in step three. Simultaneously, corresponding position variables and cross-sectional variables are entered, and their ranges are determined to provide input conditions for subsequent optimization. The ranges of the position and cross-sectional variables are determined based on the arrangement of the shock absorber and enclosure structure of the vehicle model. When the position and cross-sectional variables change within the specified range, the generated parametric model will not interfere with the structure of the shock absorber and enclosure of the vehicle model. When parametrically modeling the rear suspension mount, to improve optimization efficiency, only the plane connecting the rear suspension mount and the shock absorber is parametrically modeled. Furthermore, the boundary of this parametric model is consistent with the boundary of the finite element model, and the node numbers are consistent with the node numbers in the finite element model.

[0060] Step 5: Couple the finite element model built in Step 1 with the parametric model built in Step 4;

[0061] Coupled parametric models and finite element models can be achieved by defining the same nodes (with identical positions and node numbers) in both models.

[0062] Step 6: Optimize the parameters of the coupled model from Step 5;

[0063] 1) Perform parameter optimization on the combined model. First, determine the range of each variable in the parameterized model in step four, and determine the variable matrix corresponding to each sample according to the optimized Latin hypercube algorithm (which generates more uniform sampling points compared to the traditional Latin hypercube method).

[0064] 2) Based on the variable matrix, use Isight software to drive parametric modeling software to perform meshing, generate the required sample space, and analyze the vehicle body strength, overall stiffness, modal and local stiffness performance of the sample space.

[0065] 3) Construct a surrogate model using the Kriging method (also known as spatial local interpolation):

[0066]

[0067] In the formula: λ i Let x0 be the unobserved point that needs to be estimated, and x1, x2, ... x be the weighting coefficients to be determined. N The observation points around it.

[0068] 4) In engineering practice, an adjustment coefficient is generally used to evaluate the fitting accuracy of the approximate model. The formula for the adjustment coefficient is shown below. When the adjustment coefficient is greater than 0.9, the accuracy of the surrogate model is considered to meet the requirements.

[0069]

[0070] In the formula: n is the number of test sample points; y i Let be the simulated value of the i-th response; For the i-th response, the approximate model prediction is given. This represents the average value of the simulation results.

[0071] 5) Based on the surrogate model, the multi-island genetic algorithm (MIGA) is used for optimization analysis to obtain the optimal combination of variables.

[0072] Step 7: Verify whether the parameters optimized in Step 6 meet the performance requirements.

[0073] Example 2

[0074] See Figure 2 This invention provides an integrated die-casting floor multi-objective optimization device, comprising:

[0075] The first module is used to create a finite element model of the integrated die-cast floor and analyze the vehicle body strength, overall stiffness, modal characteristics, and performance of the rear shock absorber mounting points.

[0076] The topology optimization space module is used to determine the topology optimization space based on the position of the shock absorber and the distance between the candidate mounting base and the package frame;

[0077] The topology optimization analysis module is used to perform topology optimization analysis on a defined topology optimization space.

[0078] The second module is used to create a planar parametric model of the rear suspension mount and the shock absorber.

[0079] The coupling module is used to couple the finite element model and the parametric model;

[0080] The optimization module is used to optimize the parameters of the coupled model;

[0081] The verification module is used to verify whether the optimized parameters meet the performance requirements.

[0082] Example 3

[0083] Figure 3 This is a structural block diagram of a terminal provided in an embodiment of this application. The terminal can be the terminal in the above embodiments. The terminal 300 can be a portable mobile terminal, such as a smartphone or tablet computer. The terminal 300 may also be referred to as user equipment, portable terminal, or other names.

[0084] Typically, terminal 300 includes a processor 301 and a memory 302.

[0085] Processor 301 may include one or more processing cores, such as a quad-core processor or an octa-core processor. Processor 301 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 301 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 301 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 301 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0086] Memory 302 may include one or more computer-readable storage media, which may be tangible and non-transitory. Memory 302 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in memory 302 is used to store at least one instruction, which is executed by processor 301 to implement the integrated die-casting floor multi-objective optimization method provided in this application.

[0087] In some embodiments, the terminal 300 may also optionally include: a peripheral device interface 303 and at least one peripheral device. Specifically, the peripheral device includes at least one of: a radio frequency circuit 304, a touch display screen 305, a camera 306, an audio circuit 307, a positioning component 308, and a power supply 309.

[0088] The peripheral device interface 303 can be used to connect at least one I / O (Input / Output) related peripheral device to the processor 301 and the memory 302. In some embodiments, the processor 301, memory 302, and peripheral device interface 303 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 301, memory 302, and peripheral device interface 303 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0089] The radio frequency (RF) circuit 304 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 304 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 304 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 304 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 304 can communicate with other terminals through at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 304 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0090] The touch display screen 305 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. The touch display screen 305 also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to the processor 301 for processing. The touch display screen 305 is used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one touch display screen 305, which is located on the front panel of the terminal 300; in other embodiments, there may be at least two touch display screens, respectively located on different surfaces of the terminal 300 or in a folded design; in still other embodiments, the touch display screen 305 may be a flexible display screen, located on a curved or folded surface of the terminal 300. Furthermore, the touch display screen 305 may be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. The touch display screen 305 may be made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0091] Camera assembly 306 is used to acquire images or videos. Optionally, camera assembly 306 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is used for video calls or selfies, and the rear-facing camera is used for taking photos or videos. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, and a wide-angle camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, and panoramic shooting and VR (Virtual Reality) shooting by fusion of the main camera and the wide-angle camera. In some embodiments, camera assembly 306 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash is a combination of a warm light flash and a cool light flash, which can be used for light compensation at different color temperatures.

[0092] Audio circuit 307 provides an audio interface between the user and terminal 300. Audio circuit 307 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting the sound waves into electrical signals that are input to processor 301 for processing, or input to radio frequency circuit 304 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each located at a different part of terminal 300. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert electrical signals from processor 301 or radio frequency circuit 304 into sound waves. The speaker may be a conventional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, audio circuit 307 may also include a headphone jack.

[0093] The positioning component 308 is used to determine the current geographic location of the terminal 300 in order to enable navigation or LBS (Location Based Service). The positioning component 308 can be a positioning component based on the US GPS (Global Positioning System), China's BeiDou system, or Russia's Galileo system.

[0094] The power supply 309 is used to power the various components in the terminal 300. The power supply 309 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When the power supply 309 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired connection, while a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0095] Those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on terminal 300, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0096] Example 4

[0097] In an exemplary embodiment, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the multi-objective optimization method for integral die-cast flooring as provided in all embodiments of the present application.

[0098] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0099] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0100] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0101] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0102] Example 5

[0103] In an exemplary embodiment, an application product is also provided, including one or more instructions that can be executed by the processor 301 of the aforementioned device to complete the aforementioned multi-objective optimization method for integral die-cast flooring.

[0104] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. It can be applied to various fields suitable for the invention. Further modifications can be readily made by those skilled in the art. Therefore, without departing from the general concept defined by the claims and their equivalents, the invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. A multi-objective optimization method for an integrated die-cast floor, characterized in that, include: Step 1: Build a finite element model of the integrated die-cast floor and analyze the vehicle body strength, overall stiffness, modal analysis, and performance of the rear shock absorber mounting points; Step 2: Determine the topology optimization space based on the location of the shock absorber and the distance between the candidate mounting base and the package frame; Step 3: Perform topology optimization analysis on the topology optimization space determined in Step 2; Step 4: Construct a planar parametric model connecting the rear suspension mounting base and the shock absorber; Step 5: Couple the finite element model built in Step 1 with the parametric model built in Step 4; Step 6: Optimize the parameters of the coupled model from Step 5; Step 7: Verify whether the parameters optimized in Step 6 meet the performance requirements.

2. The multi-objective optimization method for an integrated die-cast floor according to claim 1, characterized in that, In step one, the integral die-cast floor is modeled using second-order tetrahedral elements, wherein the mesh size of the integral die-cast floor is 8mm.

3. The multi-objective optimization method for an integrated die-cast floor according to claim 1, characterized in that, In step two, the lower boundary of the topology optimization space does not interfere with the spring damper, and the upper boundary does not interfere with the suspension mounting and the package frame.

4. The multi-objective optimization method for an integrated die-cast floor according to claim 1, characterized in that, Step three, topology optimization analysis of the topology optimization space, is based on the vehicle body strength condition, with the goal of minimizing mass and the constraint that the maximum stress is below the stress limit.

5. The multi-objective optimization method for an integrated die-cast floor according to claim 1, characterized in that, In step four, based on the topology optimization results of step three, a basic parametric model is established using SFE software. Simultaneously, the corresponding position variables and cross-sectional variables are entered, and their ranges are determined to provide input conditions for subsequent optimization. The ranges of the position and cross-sectional variables are determined based on the arrangement of the shock absorbers and frame structure of the vehicle model. When the position and cross-sectional variables change within the specified range, the generated parametric model will not interfere with the structure of the shock absorbers and frame of the vehicle model. Furthermore, the ranges of each variable in the parametric model need to be determined.

6. The multi-objective optimization method for an integrated die-cast floor according to claim 1, characterized in that, In step four, the planar parametric model connecting the rear suspension mounting base and the shock absorber has the same boundary as the finite element model built in step one, and the node number is the same as the node number of the finite element model.

7. The multi-objective optimization method for an integrated die-cast floor according to claim 1, characterized in that, The specific method for step six is ​​as follows: 1) The optimized Latin hypercube algorithm is used to determine the variable matrix corresponding to each sample; 2) Based on the variable matrix and using Isight software to drive parametric modeling software to perform network division, generate the required sample space, and analyze the vehicle body strength, overall stiffness, modal characteristics, and rear shock absorber fixed point performance of the sample space; 3) Constructing the proxy model using the Kriging method: In the formula: λ i Let x0 be the unobserved point that needs to be estimated, and x1, x2, ... x be the weighting coefficients to be determined. N For the surrounding observation points; 4) Use the adjustment coefficient to evaluate the fitting accuracy of the approximate model. The formula for the adjustment coefficient is shown below. When the adjustment coefficient is greater than 0.9, the accuracy of the surrogate model is considered to meet the condition. In the formula: n is the number of test sample points; y i Let be the simulated value of the i-th response; For the i-th response, the approximate model prediction is given. This represents the average value of the simulation results. 5) Based on the surrogate model, the multi-island genetic algorithm is used for optimization analysis to obtain the optimal combination of variables.

8. A multi-objective optimization device for an integrated die-cast floor, characterized in that, include: The first module is used to create a finite element model of the integrated die-cast floor and analyze the vehicle body strength, overall stiffness, modal characteristics, and performance of the rear shock absorber mounting points. The topology optimization space module is used to determine the topology optimization space based on the position of the shock absorber and the distance between the candidate mounting base and the package frame; The topology optimization analysis module is used to perform topology optimization analysis on a defined topology optimization space. The second module is used to create a planar parametric model of the rear suspension mount and the shock absorber. The coupling module is used to couple the finite element model and the parametric model; The optimization module is used to optimize the parameters of the coupled model; The verification module is used to verify whether the optimized parameters meet the performance requirements.

9. A terminal, characterized in that, include: One or more processors; Memory for storing the one or more processor-executable instructions; Wherein, the one or more processors are configured as follows: Perform the multi-objective optimization method for integral die-cast flooring as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the terminal, the terminal is able to perform the multi-objective optimization method for the integral die-cast floor as described in any one of claims 1 to 7.

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