A cast aluminum rear floor structure design method and device, a terminal and a storage medium

Abstract

The present application belongs to the technical field of automobile, specifically a cast aluminum rear floor structure design method, device, terminal and storage medium. The present application extracts the displacement of the cast aluminum floor and the body sheet metal connection point when the vehicle body is twisted, then loads the displacement on the cast aluminum floor and performs topology optimization. The consistency of the topology optimization analysis result under this working condition and the vehicle body torsional stiffness working condition analysis result is relatively high, and the calculation period can be shortened, greatly improving the optimization efficiency. And for the topology optimization analysis result, based on the parameterized optimization technology, the topology result is analyzed, the size and number of the reinforcing ribs and ribs that need to be added are optimized, the topology optimization analysis time is reduced, and the topology optimization analysis efficiency is greatly improved.

Description

Technical Field

[0001] This invention belongs to the field of automotive technology, specifically a method, device, terminal, and storage medium for designing a cast aluminum rear floor structure. Background Technology

[0002] As the requirements for automotive lightweighting continue to increase, the application of cast aluminum structures in automobiles is also growing. Current technologies only address the structural design and lightweighting of small structures such as cast aluminum front suspension mounts and cast aluminum brackets based on topology optimization results, while design methods for large cast aluminum structures such as cast aluminum rear floors have not yet been explored. Summary of the Invention

[0003] This invention provides a method, apparatus, terminal, and storage medium for designing a cast aluminum rear floor structure. It extracts the displacement at the connection point between the cast aluminum floor and the body sheet metal during vehicle torsion, then applies this displacement to the cast aluminum floor and performs topology optimization. Under this condition, the topology optimization analysis results show high consistency with the vehicle body torsional stiffness analysis results, and the calculation cycle can be shortened, significantly improving optimization efficiency. Furthermore, based on the topology optimization analysis results, this invention proposes a parametric optimization technique to analyze the topology results, determining the size and number of reinforcing ribs and stiffeners needed for optimization, thereby reducing the topology optimization analysis time and greatly improving its efficiency.

[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 method for designing a cast aluminum floor structure is provided, comprising the following steps:

[0006] Step 1: Build a finite element model of the cast aluminum rear floor, analyze the torsional stiffness of the body-in-white, and extract the displacement of the connection point between the cast aluminum rear floor and the sheet metal based on the analysis results of the torsional stiffness of the body-in-white.

[0007] Step 2: Use the displacement of the connection point between the cast aluminum floor and the sheet metal in Step 1 as the boundary condition for topology optimization, and perform topology optimization on the cast aluminum floor.

[0008] Step 3: Compare the topology optimization results of the white body with those of Step 2 to see if they are consistent;

[0009] Step 4: Analyze the topology optimization results and perform parametric modeling of the stiffeners and reinforcing ribs based on parametric modeling software;

[0010] Step 5: Parametric optimization of reinforcing ribs, optimizing the position, size, and number of reinforcing ribs;

[0011] Step 6: Perform performance verification on the final optimized solution.

[0012] Furthermore, in step one, the cast aluminum back floor is modeled using tetrahedral elements, with the minimum mesh size of the back floor being 6mm.

[0013] Furthermore, in step one, the connection points between the cast aluminum floor and the sheet metal are renumbered and a set is established.

[0014] Furthermore, the load condition for topology optimization of the cast aluminum floor in step two is based on the displacement of the vehicle body torsional stiffness analysis results. The goal is to achieve the lowest flexibility under the load condition, retaining only 30% of the volume, and then performing topology optimization analysis.

[0015] Furthermore, the specific method for step four is as follows:

[0016] 41) Using parametric modeling software, build the outer surface of the reinforcing ribs and stiffeners, and then generate tetrahedral elements using Hypermesh software. The coupling between the cast aluminum floor and the sheet metal is achieved through rigid elements.

[0017] 42) Based on the constructed parametric model, the position is controlled by controlling the baseline of the base point, the size of the stiffener is controlled by controlling the cross section of the stiffener, and the correct connection relationship is ensured, thereby generating a sample space and performing parametric optimization.

[0018] 43) Determine the variable matrix based on the range of the variables, drive the parameterized model changes according to the variable matrix, and generate the corresponding finite element model.

[0019] Furthermore, when establishing the parametric model of the stiffeners and reinforcing ribs in step 43), the corresponding position variables and cross-sectional variables are entered, and the range of the corresponding variables is determined.

[0020] Furthermore, the specific method for step five is as follows:

[0021] 51) First, based on the variables and corresponding variable ranges of the parameter model established in step four, determine the variable matrix corresponding to each sample according to the Latin hypercube algorithm;

[0022] 52) Based on the variable matrix, drive the parametric software to perform meshing, couple the parametric model and the finite element model, generate the required sample space, and analyze the torsional stiffness performance of the sample space.

[0023] 53) Then, the response surface methodology is used to construct the second-order polynomial surrogate model as shown below:

[0024]

[0025] In the formula: y represents the torsional stiffness performance of the vehicle body; β0, β i ,β ii ,β ijFor unknown parameters; x i Let be the i-th variable; ε be the error;

[0026] 54) Take the adjustment coefficient R 2 The adjustment coefficient formula is shown below to evaluate the fitting accuracy of the surrogate model: when the adjustment coefficient is greater than 0.9, the accuracy of the surrogate model meets the condition.

[0027]

[0028] In the formula, n is the number of test sample points; yi is 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.

[0029] 55) Based on the surrogate model, seek the combination of reinforcing variables that maximizes the improvement of various performance aspects; construct the optimization model as follows:

[0030] Find y(x1,x2,…,x n )

[0031] MAX{K T (x),f T (x)}

[0032] In the formula: y(x1,x2,…,x) n (x1, x2, ..., x) represents the surrogate model; n K is a variable; T (x), f T (x) represents torsional stiffness and first-order torsional frequency, respectively, and the adaptive simulated annealing method is used for optimization analysis.

[0033] According to a second aspect of the present invention, a device for designing a cast aluminum rear floor structure is provided, comprising:

[0034] The first module is used to build a finite element model of the cast aluminum rear floor, analyze the torsional stiffness of the body-in-white, and extract the displacement of the connection point between the cast aluminum rear floor and the sheet metal based on the analysis results of the torsional stiffness of the body-in-white.

[0035] The topology optimization module is used to perform topology optimization on the cast aluminum rear floor by using the displacement of the connection point between the cast aluminum rear floor and the sheet metal as the boundary condition for topology optimization.

[0036] The comparison module is used to compare whether the topology optimization results of the white body are consistent with the topology optimization results of step two;

[0037] The second module is used to analyze the topology optimization results and to perform parametric modeling of stiffeners and reinforcing ribs based on parametric modeling software.

[0038] The optimization module is used to optimize the parameterization of stiffeners, including the position, size, and quantity of stiffeners and ribs.

[0039] The verification module is used to verify the performance of the final optimization solution.

[0040] According to a third aspect of the present invention, a terminal is provided, comprising:

[0041] One or more processors;

[0042] Memory for storing the one or more processor-executable instructions;

[0043] Wherein, the one or more processors are configured as follows:

[0044] Perform the method described in the first aspect of the embodiments of the present invention.

[0045] 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.

[0046] 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.

[0047] The beneficial effects of this invention are as follows:

[0048] 1) This invention defines a working condition for topology optimization analysis. The analysis results based on this working condition are consistent with the results based on the whole vehicle torsion working condition analysis. Furthermore, this working condition can reduce the topology optimization analysis time and greatly improve the efficiency of topology optimization analysis.

[0049] 2) This invention provides a method for parsing and parametrically optimizing topology results based on parametric optimization technology. This method can better parse topology optimization results and achieve better performance. Attached Figure Description

[0050] 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.

[0051] Figure 1 This is a flowchart illustrating the design method for a cast aluminum floor structure according to the present invention.

[0052] Figure 2 This is a schematic diagram of the structure of the cast aluminum rear floor structure design device according to the present invention;

[0053] Figure 3 This is a schematic block diagram of a terminal structure. Detailed Implementation

[0054] 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.

[0055] Example 1

[0056] Figure 1 This invention provides a method for designing a cast aluminum rear floor structure, applicable to the design of cast aluminum rear floor structures. This method can be executed by a cast aluminum rear floor structure device, which can be implemented in software and / or hardware.

[0057] Step 1: Build a finite element model of the cast aluminum rear floor, analyze the torsional stiffness of the body-in-white, and extract the displacement of the connection point between the cast aluminum rear floor and the sheet metal based on the analysis results of the torsional stiffness of the body-in-white.

[0058] To improve topology optimization efficiency, it is recommended that the minimum mesh size for the back floor be 6mm (except for areas with thick walls), and that details such as chamfers be ignored, and that tetrahedral elements be used for modeling.

[0059] Renumber the connection points between the cast aluminum floor and the sheet metal, and create a set.

[0060] Based on the torsional stiffness results, the displacement at the connection between the cast aluminum floor and the body sheet metal is extracted (a node set can be created to facilitate the extraction of node displacements), providing input for the subsequent topology optimization of the cast aluminum floor.

[0061] Step 2: Use the displacement of the connection point between the cast aluminum floor and the sheet metal in Step 1 as the boundary condition for topology optimization, and perform topology optimization on the cast aluminum floor.

[0062] The load conditions for topology optimization of the cast aluminum floor are based on the displacements obtained from the vehicle body torsional stiffness analysis. The objective is to minimize the flexibility under the load conditions, retaining only 30% of the volume, and then perform topology optimization analysis.

[0063] Step 3: Compare the topology optimization results of the white body with those of Step 2 to see if they are consistent;

[0064] To demonstrate that the topology optimization results under the proposed operating conditions are consistent with the topology optimization analysis results based on the whole vehicle torsion condition, it is necessary to compare the topology optimization results under the two operating conditions. This comparison will not be repeated in subsequent development of the cast aluminum floor. Therefore, topology optimization analysis can be performed on the floor plate separately, which can significantly reduce computation time and improve the efficiency of analysis and optimization.

[0065] Step 4: Analyze the topology optimization results and perform parametric modeling of the stiffeners and reinforcing ribs based on parametric modeling software;

[0066] The specific method is as follows:

[0067] 41) Using parametric modeling software, build the outer surface of the reinforcing ribs and stiffeners, and then generate tetrahedral elements using Hypermesh software. The coupling between the cast aluminum floor and the sheet metal is achieved through rigid elements.

[0068] 42) Based on the constructed parameterized model, the position is controlled by controlling the baseline of the base point, the size of the stiffener is controlled by controlling the cross section of the stiffener, and the connection relationship is ensured to generate a sample space and perform parameterized optimization; the sample space is based on the Latin hypersolution method.

[0069] 43) Determine the variable matrix based on the range of the variables, drive the parameterized model changes according to the variable matrix, and generate the corresponding finite element model.

[0070] When establishing the parametric model of the stiffeners and reinforcing ribs in step 43), the corresponding position variables and cross-sectional variables are entered, and the range of the corresponding variables is determined at the same time.

[0071] Step 5: Parametric optimization of reinforcing ribs, optimizing the position, size, and number of reinforcing ribs;

[0072] The specific method is as follows:

[0073] 51) First, based on the variables and corresponding variable ranges of the parameter model established in step four, determine the variable matrix corresponding to each sample according to the Latin hypercube algorithm;

[0074] 52) Based on the variable matrix, drive the parametric software to perform meshing, couple the parametric model and the finite element model, generate the required sample space, and analyze the torsional stiffness performance of the sample space.

[0075] 53) Then, the response surface methodology is used to construct the second-order polynomial surrogate model as shown below:

[0076]

[0077] In the formula: y represents the torsional stiffness performance of the vehicle body; β0, β i ,β ii,β ij For unknown parameters; x i Let be the i-th variable; ε be the error;

[0078] 54) Take the adjustment coefficient R 2 The adjustment coefficient formula is shown below to evaluate the fitting accuracy of the surrogate model: when the adjustment coefficient is greater than 0.9, the accuracy of the surrogate model meets the condition.

[0079]

[0080] In the formula, n is the number of test sample points; yi is the simulated value of the i-th response; For the i-th response, the approximate model prediction is given. The average value is the simulation value; the error accuracy of the surrogate model is shown in Table 1.

[0081] Table 1. Error Accuracy of the Surrogate Model

[0082] proxy model object R-squared ≥ 0.9 quality 0.99 Torsional stiffness 0.99 Modal 0.98

[0083] 55) Based on the surrogate model, seek the combination of reinforcing variables that maximizes the improvement of various performance aspects; construct the optimization model as follows:

[0084] Find y(x1,x2,…,x n )

[0085] MAX{K T (x),f T (x)}

[0086] In the formula: y(x1,x2,…,x) n (x1, x2, ..., x) represents the surrogate model; n K is a variable; T (x), f T (x) represents torsional stiffness and first-order torsional frequency, respectively, and the adaptive simulated annealing method is used for optimization analysis.

[0087] Step 6: Perform performance verification on the final optimized solution.

[0088] The study aimed to verify whether the torsional stiffness of the vehicle body improved when the optimized cast aluminum floor structure was connected to the vehicle body, and to compare whether the weight of the cast aluminum floor was reduced.

[0089] Example 2

[0090] See Figure 2 This invention provides a device for designing a cast aluminum rear floor structure, comprising:

[0091] The first module is used to build a finite element model of the cast aluminum rear floor, analyze the torsional stiffness of the body-in-white, and extract the displacement of the connection point between the cast aluminum rear floor and the sheet metal based on the analysis results of the torsional stiffness of the body-in-white.

[0092] The topology optimization module is used to perform topology optimization on the cast aluminum rear floor by using the displacement of the connection point between the cast aluminum rear floor and the sheet metal as the boundary condition for topology optimization.

[0093] The comparison module is used to compare whether the topology optimization results of the white body are consistent with the topology optimization results of step two;

[0094] The second module is used to analyze the topology optimization results and to perform parametric modeling of stiffeners and reinforcing ribs based on parametric modeling software.

[0095] The optimization module is used to optimize the parameterization of stiffeners, including the position, size, and quantity of stiffeners and ribs.

[0096] The verification module is used to verify the performance of the final optimization solution.

[0097] Example 3

[0098] 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.

[0099] Typically, terminal 300 includes a processor 301 and a memory 302.

[0100] 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.

[0101] The memory 302 may include one or more computer-readable storage media, which may be tangible and non-transitory. The 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 the memory 302 are used to store at least one instruction, which is executed by the processor 301 to implement a cast aluminum rear floor structure design method provided in this application.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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).

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] Example 4

[0112] 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 a method for designing a cast aluminum rear floor structure as provided in all embodiments of the present application.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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).

[0117] Example 5

[0118] 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 method for designing a cast aluminum floor structure.

[0119] 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 method of integrated die cast floor multi-objective optimization, characterized by, Comprise: Step one, build the finite element model of cast aluminum rear floor, analyze the body-in-white torsional stiffness, based on the body-in-white torsional stiffness analysis results, extract the displacement of the cast aluminum rear floor and sheet metal connecting point; Step two, the displacement of the cast aluminum rear floor and sheet metal connecting point in step one is used as the boundary condition of topology optimization, and the cast aluminum rear floor is subjected to topology optimization; Step three, compare whether the topology optimization results of the body-in-white are consistent with the topology optimization results of step two; Step four, analyze the topology optimization results, and parameterize the reinforcement rib based on the parametric modeling software; Step five, reinforcement rib parameterization optimization, optimize the position, size and quantity of the reinforcement rib and the reinforcement rib; Step six, performance recheck of the final optimization scheme; In step one, the cast aluminum rear floor is modeled using tetrahedral elements, wherein the grid size of the rear floor is at least 6mm; In step one, the cast aluminum rear floor and sheet metal connecting point are renumbered and set is established; In step two, the load condition for topology optimization of the cast aluminum floor is the displacement based on the body-in-white torsional stiffness analysis results, and the target is the lowest flexibility under the working condition, with only 30% volume reserved as the target for topology optimization analysis; The specific method of step four is as follows: 41) Use parametric modeling software to build the outer surface of the reinforcement rib and the reinforcement rib, then generate tetrahedral elements through Hypermesh software, and realize the coupling of the cast aluminum floor and sheet metal connecting point through rigid elements; 42) Based on the built parametric model, control the position by controlling the base point baseline, control the size of the reinforcement rib by controlling the reinforcement rib section, and ensure the correct connection relationship, and then generate sample space and perform parameterization optimization; 43) Determine the variable matrix according to the range of the variable, and drive the parametric model to change according to the variable matrix, and generate the corresponding finite element model; When establishing the parametric model of the reinforcement rib and the reinforcement rib in 43), the corresponding position variable, section variable and the range of the corresponding variable are input; The specific method of step five is as follows: 51) First, according to the variables and corresponding variable ranges of the parameter model established in step four, determine the variable matrix corresponding to each sample according to the Latin hypercube algorithm; 52) According to the variable matrix, drive the parametric software to mesh, couple the parametric model and the finite element model, generate the required sample space, and analyze the torsional stiffness performance of the sample space; 53) Then construct the second-order polynomial proxy model as shown below using the response surface method: In the formula: y represents the torsional stiffness performance of the vehicle body; β0, β i ,β ii ,β ij For unknown parameters; x i Let be the i-th variable; ε be the error; 54) take the adjustment coefficient R 2 The fitting accuracy of the agent model is evaluated, and the adjustment coefficient formula is as follows: when the adjustment coefficient is greater than 0.9, the accuracy of the agent model meets the condition; where n is the number of test sample points; yi is the simulation value of the i-th response; is the predicted value of the i-th response by the approximation model; is the average of the simulation values. 55) Based on the proxy model, seek the reinforcement rib variable combination that can maximize the performance improvement; construct the optimization model as follows: Find y(x1,x2,…,x n ) MAX{K T (x),f T (x)} where y(x1,x2,…,x n ) is the surrogate model; x1,x2,…,x n are the variables; K T (x), f T (x) are the torsional stiffness, the first order torsional frequency respectively, and the adaptive simulated annealing method is used for optimization analysis.

2. The integrated die cast floor multi-objective optimization method of claim 1, wherein, A cast aluminum rear floor structure design device is realized, comprising: A first model creation module is configured to build a finite element model of a cast aluminum rear floor, analyze the body-in-white torsional stiffness, and extract the displacement of the cast aluminum rear floor and sheet metal connecting point based on the body-in-white torsional stiffness analysis results; A topology optimization module is configured to use the displacement of the cast aluminum rear floor and sheet metal connecting point as the boundary condition of topology optimization, and to perform topology optimization on the cast aluminum rear floor; A comparison module is configured to compare whether the body-in-white topology optimization result is consistent with the topology optimization result of step two. A second model creation module is configured to analyze the topology optimization result, and perform parameterized modeling on the stiffener and the stiffening rib based on a parameterized modeling software. An optimization module is configured to optimize the parameterization of the stiffener, and optimize the position, size and quantity of the stiffener and the stiffening rib. A rechecking module is configured to perform performance rechecking on the final optimization scheme.

3. A terminal, characterized by comprising: The method comprises: one or more processors; a memory for storing instructions executable by the one or more processors; wherein the one or more processors are configured to: perform a cast aluminum rear floor structure design method as claimed in claim 1.

4. A non-transitory computer-readable storage medium, comprising: When the instructions in the storage medium are executed by the processor of the terminal, the terminal can perform a cast aluminum rear floor structure design method as claimed in claim 1.

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