Automated method, device, terminal and storage medium for optimizing body thickness

Abstract

The application discloses a kind of car body thickness optimization automation method, device, terminal and storage medium, belong to car body thickness optimization design technical field, include: when obtaining car body thickness optimization request data, obtain the original car body stiffness matrix in the car body thickness optimization request data and obtain car body stiffness matrix;Initial thickness mixed stiffness matrix is obtained by the car body stiffness matrix and fixture stiffness matrix;The associated symmetrical piece matrix is obtained by the initial thickness mixed stiffness matrix and bill of materials;The associated symmetrical piece matrix is used as the target parameter of the car body thickness optimization with the construction parameter corresponding to the minimum car body mass.The patent is automatically parameterized design to the thickness attribute of spare part and the discrete design interface variable of spare part, and is matched to establish discrete parameterization car body stiffness model, and the associated symmetrical piece matrix is used as the target parameter of the car body thickness optimization with the construction parameter corresponding to the minimum car body mass.

Description

TECHNICAL FIELD

[0001] The application discloses a vehicle body thickness optimization automation method and device, a terminal and a storage medium, and belongs to the technical field of vehicle body thickness optimization design. BACKGROUND

[0002] The light weight level is an important index of vehicle body product development, and through thickness sensitivity analysis of vehicle body performance and multi-disciplinary optimization based on an approximate model, optimal design of thickness can be quickly and effectively realized, thereby providing important support for achieving the light weight goal of the vehicle body. However, there are three difficulties in manual operation in the thickness sensitivity and thickness optimization analysis of the vehicle body: 1) multi-level, large batch and high-discretization design variable input work; 2) stiffness constraint condition and optimization target definition work of multi-point displacement coupling; and 3) thickness sensitivity and thickness optimization result extraction and scheme selection work. The application discloses a vehicle body thickness optimization automation method for the part of the manual operation difficulty, which can improve the efficiency and accuracy of the thickness sensitivity and thickness optimization analysis of the vehicle body.

[0003] The vehicle body thickness optimization is matched with the specific application position of the vehicle body material performance in the body-in-white, high and low sensitivity components are screened out through sensitivity calculation, the material thickness of the vehicle body components is matched with the specific application position of the body-in-white, and the structure of the body-in-white components is optimized according to the high and low sensitivity, thereby improving the performance of the components and the vehicle.

[0004] The above-mentioned vehicle body light weight method can optimize the performance of the vehicle body and the whole vehicle through the finite element method, but due to the problems of multi-level, large batch and high-discretization of the thickness matrix of the vehicle body components, and the complex constraint condition and optimization target calculation method, the manual operation period is long and the error rate is high. SUMMARY

[0005] In view of the defects of the prior art, the application provides a vehicle body thickness optimization automation method, device, terminal and storage medium, which can improve the efficiency and accuracy of the thickness sensitivity and thickness optimization analysis of the vehicle body.

[0006] The technical scheme of the application is as follows:

[0007] According to a first aspect of the embodiment of the application, a vehicle body thickness optimization automation method is provided, which comprises the following steps:

[0008] When the vehicle body thickness optimization request data is acquired, the original vehicle body stiffness matrix in the vehicle body thickness optimization request data is acquired, and a vehicle body stiffness matrix is obtained;

[0009] An initial thickness hybrid stiffness matrix is obtained through the vehicle body stiffness matrix and a fixture stiffness matrix;

[0010] The initial thickness-mixed stiffness matrix and the bill of materials are associated to obtain a symmetrical matrix;

[0011] The symmetrical matrix is associated to obtain a symmetrical matrix corresponding to the construction parameters of the minimum body mass as the target parameters of the body thickness optimization.

[0012] Preferably, the initial thickness-mixed stiffness matrix and the bill of materials are associated to obtain a symmetrical matrix, including:

[0013] Each part of the initial thickness-mixed stiffness matrix is automatically matched with each part of the bill of materials to obtain a stiffness parameterized sub-matrix;

[0014] Each part of the bill of materials is automatically matched with each part of the initial thickness-mixed stiffness matrix to obtain a part number discrete design variable parameterized matrix and a material brand discrete design variable parameterized matrix;

[0015] The part design variable matrix is obtained by matching the stiffness parameterized sub-matrix with the part number discrete design variable parameterized matrix and the material brand discrete design variable parameterized matrix, respectively;

[0016] The symmetrical matrix is obtained by the stiffness parameterized sub-matrix and the part design variable matrix.

[0017] Preferably, the original body stiffness matrix in the body thickness optimization request data is obtained to obtain a body stiffness matrix, including:

[0018] The naming and attributes of the parts of the original body stiffness matrix are obtained to determine whether they meet the requirements:

[0019] Yes, the original body stiffness matrix is taken as the body stiffness matrix;

[0020] No, the naming and attributes of the parts of the original body stiffness matrix are modified and the determination of whether they meet the requirements is repeated.

[0021] Preferably, the initial thickness-mixed stiffness matrix includes a torsion clamp stiffness matrix and a bending clamp stiffness matrix.

[0022] Preferably, the initial thickness-mixed stiffness matrix is obtained by the body stiffness matrix and the clamp stiffness matrix, including:

[0023] The body torsion stiffness matrix is obtained by the body stiffness matrix and the torsion clamp stiffness matrix;

[0024] The body bending stiffness matrix is obtained by the body stiffness matrix and the bending clamp stiffness matrix;

[0025] An initial thickness hybrid stiffness matrix is obtained through the body torsional stiffness matrix and the body bending stiffness matrix.

[0026] Preferably, a part design variable matrix is obtained by matching the stiffness parameterization sub-matrix with a part number discrete design variable parameterization matrix and a material brand discrete design variable parameterization matrix respectively, comprising:

[0027] An initial thickness is obtained through the stiffness parameterization sub-matrix.

[0028] A part number-based discrete thickness variable and a material brand-based discrete thickness variable are obtained through the part number discrete design variable parameterization matrix and the material brand discrete design variable parameterization matrix respectively.

[0029] A part design variable matrix is obtained through the initial thickness, the part number-based discrete thickness variable and the material brand-based discrete thickness variable.

[0030] Preferably, a correlation symmetric part matrix is obtained through the stiffness parameterization sub-matrix and the part design variable matrix, comprising:

[0031] A filtered stiffness parameterization sub-matrix is obtained by automatically filtering the symmetry of the part in the stiffness parameterization sub-matrix,

[0032] The filtered stiffness parameterization sub-matrix and the part design variable matrix are used to obtain the correlation symmetric part matrix.

[0033] According to a second aspect of the embodiment of the present application, an automobile body thickness optimization automation device is provided, comprising:

[0034] An acquisition data module is configured to acquire an original body stiffness matrix in body thickness optimization request data and obtain a body stiffness matrix when the body thickness optimization request data is acquired.

[0035] An initial conversion module is configured to obtain an initial thickness hybrid stiffness matrix through the body stiffness matrix and a fixture stiffness matrix.

[0036] A correlation symmetry module is configured to obtain a correlation symmetric part matrix through the initial thickness hybrid stiffness matrix and a bill of materials.

[0037] A determination parameter module is configured to take a construction parameter corresponding to the minimum body mass of the correlation symmetric part matrix as a target parameter to be optimized for the body thickness.

[0038] According to a third aspect of the embodiment of the present application, a terminal is provided, comprising:

[0039] One or more processors;

[0040] a memory for storing the one or more processor-executable instructions;

[0041] wherein the one or more processors are configured to:

[0042] perform the method of the first aspect of the embodiments of the application.

[0043] According to a fourth aspect of the embodiments of the application, there is provided a non-transitory computer-readable storage medium, which, when instructions in the storage medium are executed by a processor of a terminal, causes the terminal to perform the method of the first aspect of the embodiments of the application.

[0044] According to a fifth aspect of the embodiments of the application, there is provided an application program product, which, when the application program product is running on a terminal, causes the terminal to perform the method of the first aspect of the embodiments of the application.

[0045] The application has the following beneficial effects:

[0046] The patent provides a vehicle body thickness optimization automation method, device, terminal and storage medium. The thickness attribute of a part and the discrete design interface variable of the part are automatically parameterized and matched to establish a discrete parameterized vehicle body stiffness model. The symmetry of the part is automatically screened and matched with the associated symmetric matrix. The construction parameter corresponding to the minimum vehicle body mass is used as the target parameter for vehicle body thickness optimization.

[0047] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the application. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 is a flowchart of a vehicle body thickness optimization automation method according to an exemplary embodiment;

[0049] Figure 2 is a flowchart of a vehicle body thickness optimization automation method according to an exemplary embodiment;

[0050] Figure 3 is a partial flowchart of a vehicle body thickness optimization automation method according to an exemplary embodiment;

[0051] Figure 4 is a partial flowchart of a vehicle body thickness optimization automation method according to an exemplary embodiment;

[0052] Figure 5 is a partial flowchart of a vehicle body thickness optimization automation method according to an exemplary embodiment;

[0053] Figure 6is a partial flow chart of a vehicle body thickness optimization automation method according to an exemplary embodiment;

[0054] Figure 7 is a partial flow chart of a vehicle body thickness optimization automation method according to an exemplary embodiment;

[0055] Figure 8 is a partial flow chart of a vehicle body thickness optimization automation method according to an exemplary embodiment;

[0056] Figure 9 is a structural schematic block diagram of a vehicle body thickness optimization automation device according to an exemplary embodiment;

[0057] Figure 10 is a terminal structural schematic block diagram according to an exemplary embodiment. DETAILED DESCRIPTION

[0058] The technical solutions of the present application will be described clearly and completely below in conjunction with the drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0059] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0060] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connection" should be understood broadly, for example, it can be fixed connection, or detachable connection, or integral connection; it can be mechanical connection, or electrical connection; it can be direct connection, or indirect connection through intermediate medium; it can be the internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0061] The embodiment of the present application provides a vehicle body thickness optimization automation method, which is realized by a terminal, and the terminal can be a smart phone, a desktop computer or a notebook computer, etc. The terminal at least includes a CPU, etc.

[0062] Embodiment one

[0063] Figure 1 is a flow chart of a body thickness optimization automation method according to an exemplary embodiment, the method is used in a terminal, the method comprises the following steps:

[0064] Step 101, when the body thickness optimization request data is obtained, the original body stiffness matrix in the body thickness optimization request data is obtained, and the body stiffness matrix is obtained;

[0065] Step 102, the initial thickness mixed stiffness matrix is obtained by the body stiffness matrix and the fixture stiffness matrix;

[0066] Step 103, the associated symmetry matrix is obtained by the initial thickness mixed stiffness matrix and the bill of materials;

[0067] Step 104, the associated symmetry matrix is constructed as the target parameter of the body thickness optimization with the minimum body mass corresponding to the construction parameter.

[0068] Preferably, the associated symmetry matrix obtained by the initial thickness mixed stiffness matrix and the bill of materials comprises:

[0069] Each part of the initial thickness mixed stiffness matrix is automatically matched with each part of the bill of materials to obtain a stiffness parameterized submatrix;

[0070] Each part of the bill of materials is automatically matched with each part of the initial thickness mixed stiffness matrix to obtain a part number discrete design variable parameterized matrix and a material brand discrete design variable parameterized matrix;

[0071] The part design variable matrix is obtained by matching the stiffness parameterized submatrix with the part number discrete design variable parameterized matrix and the material brand discrete design variable parameterized matrix respectively;

[0072] The associated symmetry matrix is obtained by the stiffness parameterized submatrix and the part design variable matrix.

[0073] Preferably, the original body stiffness matrix in the body thickness optimization request data is obtained, and the body stiffness matrix is obtained, comprising:

[0074] The original body stiffness matrix in the body thickness optimization request data is obtained to determine whether the naming and attributes of the parts meet the requirements:

[0075] Yes, the original body stiffness matrix is taken as the body stiffness matrix;

[0076] No, the naming and attributes of the parts of the original body stiffness matrix are modified, and it is repeatedly determined whether they meet the requirements.

[0077] Preferably, the initial gauge mixed stiffness matrix is obtained by the body stiffness matrix and the fixture stiffness matrix, including:

[0078] Preferably, the initial gauge mixed stiffness matrix is obtained by the body stiffness matrix and the fixture stiffness matrix, including:

[0079] The body torsional stiffness matrix is obtained by the body stiffness matrix and the torsional fixture stiffness matrix;

[0080] The body bending stiffness matrix is obtained by the body stiffness matrix and the bending fixture stiffness matrix;

[0081] The initial gauge mixed stiffness matrix is obtained by the body torsional stiffness matrix and the body bending stiffness matrix.

[0082] Preferably, the part design variable matrix is obtained by matching the stiffness parameterization sub-matrix with the part number discrete design variable parameterization matrix and the material grade discrete design variable parameterization matrix, respectively, including:

[0083] The initial gauge is obtained by the stiffness parameterization sub-matrix;

[0084] The part number-based discrete gauge variable and the material grade-based discrete gauge variable are obtained by the part number discrete design variable parameterization matrix and the material grade discrete design variable parameterization matrix, respectively;

[0085] The part design variable matrix is obtained by the initial gauge, the part number-based discrete gauge variable, and the material grade-based discrete gauge variable.

[0086] Preferably, the associated symmetric part matrix is obtained by the stiffness parameterization sub-matrix and the part design variable matrix, including:

[0087] The filtered stiffness parameterization sub-matrix is obtained by automatically filtering the symmetry of the parts in the stiffness parameterization sub-matrix,

[0088] The associated symmetric part matrix is obtained by the filtered stiffness parameterization sub-matrix and the part design variable matrix.

[0089] Embodiment two

[0090] Figure 2 is a flow chart of a body gauge optimization automation method according to an exemplary embodiment, the method is used in a terminal, the method includes the following steps:

[0091] Step 201, when the body gauge optimization request data is obtained, the original body stiffness matrix in the body gauge optimization request data is obtained, and the body stiffness matrix is obtained, the specific content is as follows:

[0092] First, when obtaining the body material thickness optimization request data, such as Figure 3 As shown, the original body stiffness matrix K is obtained from the body material thickness optimization request data. ori Determine whether the naming and attributes of its parts meet the requirements:

[0093] Yes, the original body stiffness matrix is ​​used as the body stiffness matrix;

[0094] No, modify the naming and attributes of the parts in the original body stiffness matrix and repeat the check to see if they all meet the requirements.

[0095] The specific requirements are as follows: 1) The part name must be “part number (7 digits)_material_XXX”; 2) The part number cannot be duplicated; 3) The part and the attribute must correspond one-to-one, and one attribute cannot correspond to multiple parts; 4) The part number of symmetrical parts must meet the part number + 1 principle.

[0096] Step 202: Obtain the initial material thickness mixed stiffness matrix using the vehicle body stiffness matrix and the fixture stiffness matrix. The specific details are as follows:

[0097] The initial material thickness mixed stiffness matrix includes: a torsional clamp stiffness matrix and a bending clamp stiffness matrix. This is achieved through the vehicle body stiffness matrix K. body With the stiffness matrix K of the torsion clamp fix_T Obtain the torsional stiffness matrix K of the vehicle body T ; through the vehicle body stiffness matrix K body With bending fixture stiffness matrix K fix_B Obtain the vehicle body bending stiffness matrix K B ; through the vehicle body torsional stiffness matrix K T and vehicle body bending stiffness matrix K B The initial material thickness mixing stiffness matrix K is obtained. mix .

[0098]

[0099] Step 203: Each part of the initial material thickness mixing stiffness matrix is ​​automatically matched with each part of the bill of materials to obtain a stiffness parameterized submatrix;

[0100] Each part in the initial material thickness mixed stiffness matrix can be automatically matched with each part in the bill of materials, providing initial material thickness for design variables and preparing for matching symmetrical parts. Iterate through the part number, material grade, material thickness, and mass of each component in the initial material thickness mixed stiffness matrix Kmix, and sequentially place them into Ln. i , Lm i Lt i ,Lg iThe above four arrays are coupled to form a part number-material grade-gauge-weight rigidity parameterization sub-matrix Lnmtg, and the detailed process is shown in Figure 4 .

[0101] Step 204, each part of the bill of materials is automatically matched with each part of the initial gauge-weight rigidity matrix to obtain a part number discrete design variable parameterization matrix and a material grade discrete design variable parameterization matrix, and the specific content is as follows:

[0102] Each part in the bill of materials BOM information is traversed, and the part number and discrete gauge information are sequentially placed in Bn j and Bt j arrays, and the above two arrays are coupled to form a part number-based discrete design variable parameterization matrix Bnt; the name of each material grade in the BOM information is traversed, and the discrete gauge information is sequentially placed in Mn k and Mt k arrays, and the above two arrays are coupled to form a material grade-based discrete design variable parameterization matrix Mnt, and the establishment process of the two sub-matrices is shown in Figure 5 .

[0103] Step 205, the part design variable matrix is obtained by matching the rigidity parameterization sub-matrix with the part number discrete design variable parameterization matrix and the material grade discrete design variable parameterization matrix, and the specific content is as follows:

[0104] The part design variable matrix includes a part number discrete gauge variable (DDVAL) and a material grade part design variable (DESVAR) in two modes of part number-based design variable automatic matching and material grade-based design variable automatic matching.

[0105] The part number-based design variable automatic matching mode is as follows:

[0106] The rigidity parameterization sub-matrix Lnmtg obtained in step 203 is sequentially traversed according to the part number, and the parameter Ln i is compared with Bn j in the part number discrete design variable parameterization matrix Bnt obtained in step 204, if Ln i is consistent with Bn j , the part number-based part design variable (DESVAR) is established, wherein the part number-based part design variable (DESVAR) contains two parameters, parameter 1 is the initial gauge, and the parameter is obtained from Lt iData acquisition; Parameter 2 is a discrete material thickness variable, which needs to be established as a discrete material thickness variable (DDVAL) based on the part number. The discrete material thickness variable (DDVAL) based on the part number is obtained by reading the Bt in the parameterized matrix Bnt of the discrete design variable of the part number obtained in step 204. j Once the values ​​are obtained, perform the matching process sequentially as described above. Detailed procedures are as follows: Figure 6 As shown.

[0107] The automatic matching mode for design variables based on material grade is as follows:

[0108] Iterate through the stiffness parameterization submatrix Lnmtg obtained in step 203 according to the part number, and set the parameter Lm i Mn in the material grade discrete design variable parameterization matrix Mnt obtained in step 204 k Perform a comparison; if Ln i With Mn k If consistent, then establish the part design variable (DESVAR) based on the material grade. The design variable (DESVAR) contains two parameters: parameter 1 is the initial material thickness, which is determined by Lt in the parameterized submatrix Lnmtg obtained in Step 3. i Data acquisition; Parameter 2 is a discrete material thickness variable based on material grade. A discrete material thickness variable based on material grade (DDVAL) needs to be established. The discrete material thickness variable based on material grade (DDVAL) is obtained by reading Mt from the parameterized matrix of the discrete design variables of the material grade obtained in step 204. j Once the numerical value is obtained, perform the matching process sequentially as described above. Figure 7 As shown.

[0109] Step 206: Obtain the associated symmetric component matrix through the stiffness parameterized submatrix and the part design variable matrix, as detailed below:

[0110] Symmetrical components need to be associated to ensure that their thickness changes consistently during the thickness optimization process. Symmetrical components have three main characteristics: 1) the part number ends in +1 (e.g., 5021021 and 5021022 are symmetrical components); 2) the initial thickness is the same; and 3) the weight is approximately equal. Based on these characteristics, the components in the stiffness parameterization submatrix Lnmtg obtained in step 203 are traversed, and Ln... i ~Ln i+n Compare the results (i+n is the total number of parts), if condition 1 is met: Ln i+x -Ln i =1 (part number + 1 principle), then determine whether condition 2 is met: Lt i =Lt i+x (Equal initial material thickness principle) If condition 2 is met, then determine whether condition 3 is met: (weight similarity principle), if condition 3 is met, the part design variable matrix DESVAR in step 205 is changed to DESVAR i and the part design variable matrix DESVAR i+x The associated symmetric part matrix Dlink is established, in which the part with a smaller part number is the main part and the part with a larger part number is the slave part, and the flow is as shown in Figure 8 .

[0111] In step 207, the associated symmetric part matrix is constructed with the construction parameter corresponding to the minimum body mass as the target parameter for the body thickness optimization.

[0112] The present application automatically parameterizes the part thickness attribute and the part discrete design boundary variable, matches them, establishes a discrete parameterized body stiffness model, automatically screens the part symmetry and matches the symmetric parts, and constructs the associated symmetric part matrix with the construction parameter corresponding to the minimum body mass as the target parameter for the body thickness optimization.

[0113] Example Three

[0114] In an exemplary embodiment, a body thickness optimization automation device is also provided, as shown in Figure 9 , the device comprises:

[0115] The data acquisition module 310 is used to acquire the original body stiffness matrix in the body thickness optimization request data and obtain the body stiffness matrix when the body thickness optimization request data is acquired.

[0116] The initial conversion module 320 is used to obtain the initial thickness mixed stiffness matrix through the body stiffness matrix and the fixture stiffness matrix.

[0117] The associated symmetric module 330 is used to obtain the associated symmetric part matrix through the initial thickness mixed stiffness matrix and the bill of materials.

[0118] The parameter determination module 340 is used to construct the associated symmetric part matrix with the construction parameter corresponding to the minimum body mass as the target parameter for the body thickness optimization.

[0119] The present application automatically parameterizes the part thickness attribute and the part discrete design boundary variable, matches them, establishes a discrete parameterized body stiffness model, automatically screens the part symmetry and matches the symmetric parts, and constructs the associated symmetric part matrix with the construction parameter corresponding to the minimum body mass as the target parameter for the body thickness optimization.

[0120] Example Four

[0121] Figure 10is a structural block diagram of a terminal provided by an embodiment of the present application. The terminal can be the terminal in the above embodiments. The terminal 400 can be a portable mobile terminal, such as a smartphone, a tablet computer. The terminal 400 can also be referred to as a user equipment, a portable terminal, or other names.

[0122] Generally, the terminal 400 includes a processor 401 and a memory 402.

[0123] The processor 401 can include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 401 can be implemented in at least one of a hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), a PLA (Programmable Logic Array). The processor 401 can also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also referred to as a CPU (Central Processing Unit). The coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 401 can be integrated with a GPU (Graphics Processing Unit) for rendering and drawing content required to be displayed by a display screen. In some embodiments, the processor 401 can further include an AI (Artificial Intelligence) processor for processing computing operations related to machine learning.

[0124] The memory 402 can include one or more computer-readable storage media, which can be tangible and non-transitory. The memory 402 can also include a high-speed random access memory, and a non-volatile memory such as one or more disk storage devices, flash storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 402 is used to store at least one instruction for being executed by the processor 401 to implement an automotive body thickness optimization automation method provided in the present application.

[0125] In some embodiments, the terminal 400 can also optionally include a peripheral device interface 403 and at least one peripheral device. Specifically, the peripheral device includes at least one of a radio frequency circuit 404, a touch display screen 405, a camera 406, an audio circuit 407, a positioning component 408, and a power supply 409.

[0126] The peripheral interface 403 can be used to connect at least one I / O (Input / Output) related peripheral device to the processor 401 and the memory 402. In some embodiments, the processor 401, the memory 402 and the peripheral interface 403 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 401, the memory 402 and the peripheral interface 403 can be implemented on a separate chip or circuit board, and the present embodiments are not limited in this regard.

[0127] The radio frequency circuit 404 is configured to receive and send RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 404 communicates with communication networks and other communication devices through electromagnetic signals. The radio frequency circuit 404 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the radio frequency circuit 404 includes an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and the like. The radio frequency circuit 404 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to the World Wide Web, a metropolitan area network, an intranet, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network, and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 404 can also include NFC (Near Field Communication) related circuitry, and the present application is not limited in this regard.

[0128] The touch display screen 405 is configured to display a UI (User Interface). The UI can include graphics, text, icons, video, and any combination thereof. The touch display screen 405 is also configured to capture touch signals on or above the surface of the touch display screen 405. The touch signals can be input to the processor 401 as control signals for processing. The touch display screen 405 is configured to provide virtual buttons and / or virtual keyboard, also known as soft buttons and / or soft keyboard. In some embodiments, the touch display screen 405 can be one, configured on the front panel of the terminal 400; in other embodiments, the touch display screen 405 can be at least two, respectively configured on different surfaces of the terminal 400 or in a folding design; in still other embodiments, the touch display screen 405 can be a flexible display screen, configured on a curved surface or a folding surface of the terminal 400. Even, the touch display screen 405 can also be configured in an irregular shape, i.e., a special-shaped screen. The touch display screen 405 can be made of materials such as LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), etc.

[0129] The camera assembly 406 is configured to capture images or videos. Optionally, the camera assembly 406 includes a front camera and a rear camera. Generally, the front camera is configured to implement video calls or selfies, and the rear camera is configured to implement photo or video shooting. In some embodiments, the rear camera is at least two, respectively any one of a main camera, a depth-of-field camera, and a wide-angle camera, to implement the background blurring function by fusing the main camera and the depth-of-field camera, and to implement the panoramic shooting and VR (Virtual Reality) shooting functions by fusing the main camera and the wide-angle camera. In some embodiments, the camera assembly 406 can further include a flash. The flash can be a single-color-temperature flash or a dual-color-temperature flash. The dual-color-temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation under different color temperatures.

[0130] The audio circuit 407 is configured to provide an audio interface between a user and the terminal 400. The audio circuit 407 can include a microphone and a speaker. The microphone is configured to collect sound waves of the user and the environment, and convert the sound waves into an electrical signal input to the processor 401 for processing, or input to the radio frequency circuit 404 for voice communication. The microphone can be multiple microphones arranged at different positions of the terminal 400 for stereo sound collection or noise reduction. The microphone can also be an array microphone or an omnidirectional collection microphone. The speaker is configured to convert an electrical signal from the processor 401 or the radio frequency circuit 404 into sound waves. The speaker can be a conventional diaphragm speaker, or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals into sound waves audible to humans, or sound waves inaudible to humans for ranging purposes. In some embodiments, the audio circuit 407 can further include a headphone jack.

[0131] The positioning component 408 is configured to locate a current geographic position of the terminal 400 for navigation or LBS (Location Based Service). The positioning component 408 can be a positioning component based on the GPS (Global Positioning System) of the United States, the Beidou system of China, or the Galileo system of Russia.

[0132] The power supply 409 is configured to supply power to various components in the terminal 400. The power supply 409 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 409 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. The wired rechargeable battery is a battery that is charged through a wired line, and the wireless rechargeable battery is a battery that is charged through a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0133] In some embodiments, the terminal 400 further includes one or more sensors 410. The one or more sensors 410 include, but are not limited to, an acceleration sensor 411, a gyroscope sensor 412, a pressure sensor 413, a fingerprint sensor 414, an optical sensor 415, and a proximity sensor 416.

[0134] The acceleration sensor 411 can detect the acceleration in three coordinate axes of a coordinate system established by the terminal 400. For example, the acceleration sensor 411 can be used to detect the components of gravitational acceleration in three coordinate axes. The processor 401 can control the touch display 405 to display a user interface in a landscape view or a portrait view according to the gravitational acceleration signals collected by the acceleration sensor 411. The acceleration sensor 411 can also be used for game or user motion data collection.

[0135] The gyroscope sensor 412 can detect the body direction and rotation angle of the terminal 400, and can collect 3D (3 Dimensions) motions of the user on the terminal 400 in cooperation with the acceleration sensor 411. The processor 401 can implement the following functions according to the data collected by the gyroscope sensor 412: motion sensing (e.g., changing a UI according to a tilt operation of the user), image stabilization when shooting, game control, and inertial navigation.

[0136] The pressure sensor 413 can be disposed on the side frame of the terminal 400 and / or the lower layer of the touch display 405. When the pressure sensor 413 is disposed on the side frame of the terminal 400, the holding signal of the user on the terminal 400 can be detected, and left / right hand recognition or a shortcut operation can be performed according to the holding signal. When the pressure sensor 413 is disposed on the lower layer of the touch display 405, the operability control on the UI interface can be controlled according to the pressure operation of the user on the touch display 405. The operability control includes at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0137] The fingerprint sensor 414 is used to collect the fingerprint of the user, so as to identify the identity of the user according to the collected fingerprint. When the identity of the user is identified as a trusted identity, the user is authorized by the processor 401 to perform a related sensitive operation, which includes unlocking the screen, viewing encrypted information, downloading software, payment, and changing settings, etc. The fingerprint sensor 414 can be disposed on the front, back or side of the terminal 400. When the terminal 400 is provided with a physical button or a manufacturer's logo, the fingerprint sensor 414 can be integrated with the physical button or the manufacturer's logo.

[0138] The optical sensor 415 is used to collect the ambient light intensity. In an embodiment, the processor 401 can control the display brightness of the touch display 405 according to the ambient light intensity collected by the optical sensor 415. Specifically, when the ambient light intensity is high, the display brightness of the touch display 405 is increased; when the ambient light intensity is low, the display brightness of the touch display 405 is decreased. In another embodiment, the processor 401 can also dynamically adjust the shooting parameters of the camera assembly 406 according to the ambient light intensity collected by the optical sensor 415.

[0139] The proximity sensor 416, also referred to as a distance sensor, is usually arranged on the front face of the terminal 400. The proximity sensor 416 is used to collect the distance between the user and the front face of the terminal 400. In one embodiment, when the proximity sensor 416 detects that the distance between the user and the front face of the terminal 400 gradually decreases, the touch display screen 405 is switched from the bright screen state to the dark screen state under the control of the processor 401; when the proximity sensor 416 detects that the distance between the user and the front face of the terminal 400 gradually increases, the touch display screen 405 is switched from the dark screen state to the bright screen state under the control of the processor 401.

[0140] Those skilled in the art can understand that the structure shown in the above embodiments is not a limitation on the terminal 400, and the terminal 400 can include more or fewer components than those shown in the figure, or combine certain components, or adopt a different arrangement of components. Figure 10 Those skilled in the art can understand that the structure shown in the above embodiments is not a limitation on the terminal 400, and the terminal 400 can include more or fewer components than those shown in the figure, or combine certain components, or adopt a different arrangement of components.

[0141] Embodiment five

[0142] In the exemplary embodiments, a computer readable storage medium is also provided, and the computer program is stored on the computer readable storage medium, and the computer program is executed by the processor to implement the body thickness optimization automation method provided by all the inventive embodiments of the present application.

[0143] Any combination of one or more computer readable medium can be employed. The 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 electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer readable storage medium can be any tangible medium that contains, or stores a program for use by or in connection with an instruction execution system, apparatus, or device.

[0144] A computer readable signal medium can include a computer readable program code in a baseband or propagated as a carrier wave in a propagation medium. Such a propagated computer readable signal medium can take a variety of forms, including but not limited to, electro-magnetic, optical, or any suitable combination thereof. Computer readable signal medium can be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0145] The program code embodied on the computer readable media can be transmitted using any appropriate medium, including but not limited to wireless, wire line, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0146] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0147] Embodiment Six

[0148] In an exemplary embodiment, an application program product is also provided, comprising one or more instructions executable by the processor 401 of the above-mentioned device to accomplish the above-mentioned body thickness optimization automation method.

[0149] While the embodiments of the application have been disclosed as above, it is not limited to the applications listed in the specification and the embodiments. It can be fully applied to various fields suitable for the application. Additional modifications can be easily made by those skilled in the art. Therefore, the application is not limited to specific details and the figures shown and described herein. It does not depart from the general concept defined by the claims and their equivalents.

Claims

1. An automated method for optimizing vehicle body material thickness, characterized in that, include: When obtaining the body material thickness optimization request data, the original body stiffness matrix in the body material thickness optimization request data is obtained and the body stiffness matrix is ​​obtained. The initial material thickness mixed stiffness matrix is ​​obtained by combining the vehicle body stiffness matrix and the fixture stiffness matrix. The initial material thickness mixing stiffness matrix and the bill of materials yield the associated symmetric component matrix; The construction parameters corresponding to the minimum body mass of the associated symmetric component matrix are used as the target parameters for optimizing the body material thickness. The initial material thickness mixing stiffness matrix and the bill of materials yield an associated symmetric component matrix, including: Each part of the initial material thickness mixing stiffness matrix is ​​automatically matched with each part of the bill of materials to obtain a stiffness parameterized submatrix; Each part in the bill of materials is automatically matched with each part in the initial material thickness mixed stiffness matrix to obtain the part number discrete design variable parameterized matrix and the material grade discrete design variable parameterized matrix; The part design variable matrix is ​​obtained by matching the stiffness parameterized submatrix with the part number discrete design variable parameterized matrix and the material grade discrete design variable parameterized matrix, respectively. The matrix of the associated symmetric component is obtained by using the stiffness parameterization submatrix and the part design variable matrix; Obtaining the original body stiffness matrix from the body material thickness optimization request data and obtaining the body stiffness matrix includes: The original body stiffness matrix in the body material thickness optimization request data is obtained to determine whether the naming and attributes of its parts meet the requirements: Yes, the original body stiffness matrix is ​​used as the body stiffness matrix; No, modify the naming and attributes of the parts in the original body stiffness matrix and repeat the check to see if they all meet the requirements; The initial material thickness mixed stiffness matrix includes: torsional clamp stiffness matrix and bending clamp stiffness matrix; The initial material thickness mixed stiffness matrix is ​​obtained by combining the vehicle body stiffness matrix and the fixture stiffness matrix, including: The torsional stiffness matrix of the vehicle body is obtained by combining the vehicle body stiffness matrix and the torsional clamp stiffness matrix. The vehicle body bending stiffness matrix is ​​obtained by combining the vehicle body stiffness matrix and the bending fixture stiffness matrix. The initial material thickness mixed stiffness matrix is ​​obtained by using the vehicle body torsional stiffness matrix and the vehicle body bending stiffness matrix; The part design variable matrix is ​​obtained by matching the stiffness parameterized submatrix with the part number discrete design variable parameterized matrix and the material grade discrete design variable parameterized matrix, respectively, including: The initial material thickness is obtained through the stiffness parameterized submatrix; The discrete material thickness variables based on the part number and the discrete material thickness variables based on the material grade are obtained by using the parameterized matrix of the discrete design variables of the part number and the parameterized matrix of the discrete design variables of the material grade, respectively. The part design variable matrix is ​​obtained by using the initial material thickness, discrete material thickness variables based on part number, and discrete material thickness variables based on material grade. The associated symmetric component matrix is ​​obtained by using the stiffness parameterized submatrix and the part design variable matrix, including: The stiffness parameterized submatrix is ​​obtained by automatically filtering the parts in the stiffness parameterized submatrix based on symmetry. The filtered stiffness parameterized submatrix and the part design variable matrix are used to obtain the associated symmetric part matrix.

2. An automated device for optimizing vehicle body material thickness, characterized in that, include: The data acquisition module is used to acquire the original body stiffness matrix in the body material thickness optimization request data and obtain the body stiffness matrix when acquiring body material thickness optimization request data. The initial conversion module is used to obtain the initial material thickness mixed stiffness matrix through the vehicle body stiffness matrix and the fixture stiffness matrix; The associated symmetry module is used to obtain the associated symmetry component matrix from the initial material thickness mixing stiffness matrix and the bill of materials; The parameter determination module is used to take the construction parameters corresponding to the minimum body mass of the associated symmetric component matrix as the target parameters for optimizing the body material thickness. The initial material thickness mixing stiffness matrix and the bill of materials yield an associated symmetric component matrix, including: Each part of the initial material thickness mixing stiffness matrix is ​​automatically matched with each part of the bill of materials to obtain a stiffness parameterized submatrix; Each part in the bill of materials is automatically matched with each part in the initial material thickness mixed stiffness matrix to obtain the part number discrete design variable parameterized matrix and the material grade discrete design variable parameterized matrix; The part design variable matrix is ​​obtained by matching the stiffness parameterized submatrix with the part number discrete design variable parameterized matrix and the material grade discrete design variable parameterized matrix, respectively. The matrix of the associated symmetric component is obtained by using the stiffness parameterization submatrix and the part design variable matrix; Obtaining the original body stiffness matrix from the body material thickness optimization request data and obtaining the body stiffness matrix includes: The original body stiffness matrix in the body material thickness optimization request data is obtained to determine whether the naming and attributes of its parts meet the requirements: Yes, the original body stiffness matrix is ​​used as the body stiffness matrix; No, modify the naming and attributes of the parts in the original body stiffness matrix and repeat the check to see if they all meet the requirements; The initial material thickness mixed stiffness matrix includes: torsional clamp stiffness matrix and bending clamp stiffness matrix; The initial material thickness mixed stiffness matrix is ​​obtained by combining the vehicle body stiffness matrix and the fixture stiffness matrix, including: The torsional stiffness matrix of the vehicle body is obtained by combining the vehicle body stiffness matrix and the torsional clamp stiffness matrix. The vehicle body bending stiffness matrix is ​​obtained by combining the vehicle body stiffness matrix and the bending fixture stiffness matrix. The initial material thickness mixed stiffness matrix is ​​obtained by using the vehicle body torsional stiffness matrix and the vehicle body bending stiffness matrix; The part design variable matrix is ​​obtained by matching the stiffness parameterized submatrix with the part number discrete design variable parameterized matrix and the material grade discrete design variable parameterized matrix, respectively, including: The initial material thickness is obtained through the stiffness parameterized submatrix; The discrete material thickness variables based on the part number and the discrete material thickness variables based on the material grade are obtained by using the parameterized matrix of the discrete design variables of the part number and the parameterized matrix of the discrete design variables of the material grade, respectively. The part design variable matrix is ​​obtained by using the initial material thickness, discrete material thickness variables based on part number, and discrete material thickness variables based on material grade. The associated symmetric component matrix is ​​obtained by using the stiffness parameterized submatrix and the part design variable matrix, including: The stiffness parameterized submatrix is ​​obtained by automatically filtering the parts in the stiffness parameterized submatrix based on symmetry. The filtered stiffness parameterized submatrix and the part design variable matrix are used to obtain the associated symmetric part matrix.

3. 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: The automated method for optimizing body material thickness as described in claim 1 is implemented.

4. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the terminal's processor, the terminal is able to execute the automated method for optimizing body material thickness as described in claim 1.

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