MPV trim body dynamic stiffness analysis method and device

Abstract

Embodiments of the present application provide a method, apparatus, device, and computer-readable storage medium for analyzing the dynamic stiffness of an MPV trim body. The method includes obtaining a reordered first system matrix of the MPV trim body and a reordered first external steady-state excitation vector; converting the first system matrix into a second system matrix using a constructed projection model; converting the first external steady-state excitation vector into a second external steady-state excitation vector based on the positions of non-zero elements in the first external steady-state excitation vector; calculating a residual vector based on the second system matrix and the second external steady-state excitation vector; calculating a global residual vector based on the residual vector; and completing the dynamic stiffness analysis of the MPV trim body based on the global residual vector. In this way, efficient scheduling and solving of large-scale residual vector tasks under hundreds of working conditions are achieved, significantly improving the overall computational efficiency and resource utilization of frequency response analysis.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of data processing, and in particular to a method, device, equipment and computer-readable storage medium for analyzing the dynamic stiffness of an MPV vehicle body. Background Art

[0002] MPV curb weight analysis is an important step in the NVH performance evaluation of the vehicle. Its goal is to obtain the steady-state response characteristics of the body structure under typical excitation loads, which is used to guide the design of the body structure stiffness, optimize vibration and noise reduction, and improve the comfort of the vehicle.

[0003] Currently, various industrial software programs generally use a frequency-domain calculation process based on the modal superposition method for dynamic stiffness analysis of MPV bodywork. In this process, the residual vector is typically solved by directly solving a system of linear equations or using an explicitly constructed projection matrix. In recent years, the automatic multiple substructuring algorithm (AMLS) has been gradually introduced into frequency response analysis, but existing solutions primarily rely on explicit projection, directly using a global projection matrix to transform the residual terms back and forth. While this approach has a certain dimensionality reduction effect, when faced with the typical simulation requirements of MPV body models (including multiple excitation points and multiple frequency conditions), the large number of matrix multiplications, data access, and storage operations required for explicit projection incurs significant computational and memory overhead, severely limiting the efficiency of the overall dynamic stiffness calculation and making it difficult to meet the high-performance and fast-response requirements of large-scale engineering simulations. Summary of the Invention

[0004] According to an embodiment of the present application, a solution for dynamic stiffness analysis of the entire MPV vehicle body is provided. By implicitly performing vector transformations and solving linear equations in a low-dimensional substructure space, the high computational and memory overheads caused by the explicit construction and storage of projection matrices are effectively avoided. When processing multiple excitation load points or frequency conditions in a typical analysis scenario of an MPV vehicle, the method of the present invention supports batch parallel solution of residual vectors, which can greatly improve the calculation efficiency of a single condition while maintaining the accuracy of dynamic stiffness analysis, significantly optimize the total time consumption of engineering simulation, and possess excellent parallel expansion capabilities and hardware resource adaptability. That is, the method of the present invention can demonstrate the advantages of low computational overhead and easy parallel implementation in the dynamic stiffness analysis of the MPV vehicle structure, can be adapted to existing platforms, and is particularly suitable for the efficient engineering simulation needs of vehicle body dynamic stiffness response analysis and NVH characteristic optimization.

[0005] In a first aspect of the present application, a method for analyzing the dynamic stiffness of an MPV vehicle body is provided. The method comprises:

[0006] Obtaining a reordered first system matrix of the MPV trim body and a reordered first external steady-state excitation vector;

[0007] Converting the first system matrix into a second system matrix using the constructed projection model; converting the first external steady-state excitation vector into a second external steady-state excitation vector based on the positions of non-zero elements in the first external steady-state excitation vector;

[0008] calculating a residual vector based on the second system matrix and the second external steady-state excitation vector;

[0009] Based on the residual vector, a global residual vector is calculated; based on the global residual vector, dynamic stiffness analysis of the MPV trim body is completed.

[0010] In some embodiments, converting the first system matrix into the second system matrix using the constructed projection model includes:

[0011] Based on the acquired working condition data, the projection matrix of the substructure is calculated;

[0012] calculating a projection model based on the projection matrix of the substructure;

[0013] Based on the projection model, the first system matrix is ​​converted into a second system matrix.

[0014] In some embodiments, calculating the projection matrix of the substructure based on the acquired working condition data includes:

[0015] ;

[0016] Among them, V i is the eigenvector of the i-th substructure;

[0017] Ns is the number of substructures;

[0018] A i are all ancestor nodes of substructure i;

[0019] Ψ ij is the constraint mode matrix of substructure i and substructure j;

[0020] I is the identity matrix.

[0021] In some embodiments, converting the first external steady-state excitation vector into a second external steady-state excitation vector based on positions of non-zero elements in the first external steady-state excitation vector comprises:

[0022] Obtaining positions of non-zero elements in the first external steady-state excitation vector;

[0023] constructing a first structural combination based on the position of the non-zero element;

[0024] Traversing the first structure combination, and constructing a second structure set based on each substructure in the first structure combination and all ancestor nodes corresponding to each substructure;

[0025] Based on the second structure set, the first external steady-state excitation vector is converted into a second external steady-state excitation vector.

[0026] In some embodiments, the calculating the residual vector based on the second system matrix and the second external steady-state excitation vector comprises:

[0027] Calculating a modal space load vector based on the second system matrix and the second external steady-state excitation vector;

[0028] Calculating a loss load vector based on the second external steady-state excitation vector and the modal space load vector;

[0029] calculating a projection matrix based on the second system matrix and the loss load vector;

[0030] Calculating an eigenvector based on the projection matrix and the second system matrix;

[0031] A residual vector is calculated based on the projection matrix and the eigenvector.

[0032] In some embodiments, calculating the eigenvector based on the projection matrix and the second system matrix includes:

[0033] ;

[0034] in, is the system stiffness matrix obtained by transforming the second system matrix through the projection matrix;

[0035] is the system mass matrix obtained by transforming the second system matrix through the projection matrix;

[0036] is the eigenvalue;

[0037] Q is the eigenvector.

[0038] In some embodiments, calculating a global residual vector based on the residual vector comprises:

[0039] Calculating a global residual vector matrix based on the residual vector and the model projection matrix;

[0040] Based on the global residual vector matrix, the global residual vector is calculated by the following formula:

[0041] ;

[0042] in, is the global residual vector matrix;

[0043] Z is the reordering transformation matrix;

[0044] is the transformation matrix of the Z matrix.

[0045] In a second aspect of the present application, a device for analyzing the dynamic stiffness of an MPV vehicle body is provided. The device comprises:

[0046] An acquisition module, configured to acquire a reordered first system matrix of the MPV prepared body and a reordered first external steady-state excitation vector;

[0047] a conversion module, configured to convert the first system matrix into a second system matrix using the constructed projection model; and convert the first external steady-state excitation vector into a second external steady-state excitation vector based on the positions of non-zero elements in the first external steady-state excitation vector;

[0048] a first calculation module, configured to calculate a residual vector based on the second system matrix and a second external steady-state excitation vector;

[0049] The second calculation module is used to calculate a global residual vector based on the residual vector; and complete the dynamic stiffness analysis of the MPV trim body based on the global residual vector.

[0050] In a third aspect of the present application, an electronic device is provided, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor implements the above method when executing the program.

[0051] In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the method according to the first aspect of the present application is implemented.

[0052] The MPV trim body dynamic stiffness analysis method provided in the embodiment of the present application obtains a reordered first system matrix of the MPV trim body and a reordered first external steady-state excitation vector; converts the first system matrix into a second system matrix through a constructed projection model; converts the first external steady-state excitation vector into a second external steady-state excitation vector based on the position of non-zero elements in the first external steady-state excitation vector; calculates a residual vector based on the second system matrix and the second external steady-state excitation vector; calculates a global residual vector based on the residual vector; and completes the dynamic stiffness analysis of the MPV trim body based on the global residual vector, thereby achieving efficient scheduling and solution of large-scale residual vector tasks under hundreds of working conditions, and significantly improving the overall computational efficiency and resource utilization of frequency response analysis.

[0053] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0055] Figure 1 Flowchart of a method for analyzing dynamic stiffness of an MPV trim body according to an embodiment of the present application;

[0056] Figure 2 is a schematic diagram of a substructure tree according to an embodiment of the present application;

[0057] Figure 3 1 is a block diagram of an MPV trim body dynamic stiffness analysis device according to an embodiment of the present application;

[0058] Figure 4 A schematic diagram of the structure of a terminal device or server suitable for implementing an embodiment of the present application. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0060] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document generally indicates that the related objects are in an "or" relationship.

[0061] Figure 1 A flow chart of a method for analyzing the dynamic stiffness of an MPV vehicle body according to an embodiment of the present invention is shown. The method includes:

[0062] S110 , obtaining a reordered first system matrix of the MPV prepared body and a reordered first external steady-state excitation vector.

[0063] The present invention can be used to solve the problem of efficient parallel scheduling and solving of residual vector calculation tasks under multiple working conditions and frequency points in the dynamic stiffness analysis of MPV body. For the convenience of description, let the total number of working conditions involved in the dynamic stiffness analysis be m, the total number of residual vectors to be calculated in all working conditions be n, and the number of threads used in the calculation process be , the number of substructures obtained by dividing the entire finite element model based on the automatic multiple substructure algorithm (AMLS) is The number of residual vectors corresponding to each working condition can be flexibly set by the user according to the actual simulation requirements. That is, the number of residual vectors for each working condition can be unevenly distributed and vary greatly.

[0064] In some embodiments, the basic frequency response equation for the MPV trim body dynamic stiffness analysis is set as follows:

[0065] ;

[0066] Among them, s is the frequency variable;

[0067] M is the finite element mass matrix of the MPV curb body;

[0068] u(s) is the steady-state response of the vehicle body structure to excitation in the frequency domain;

[0069] C is the finite element damping matrix of the MPV curb body;

[0070] K is the finite element stiffness matrix of the MPV curb body, f(s) is the external steady-state excitation spectrum;

[0071] Wherein M, C and K belong to the system matrix; that is, the system matrix includes M, C and K.

[0072] In some embodiments, the system degrees of freedom can be reordered by graph decomposition software or other methods to obtain a reordered system matrix:

[0073] ;

[0074] ;

[0075] ;

[0076] Among them, M is the original mass matrix of the MPV curb body; is the mass matrix of the system after reordering;

[0077] C is the original damping matrix of the MPV prepared body; is the damping matrix of the reordered system;

[0078] K is the original stiffness matrix of the MPV curb body; is the system stiffness matrix after reordering;

[0079] Z is the reordering transformation matrix, which represents the permutation matrix for renumbering the system's degrees of freedom. In practical applications, the Z matrix is ​​not explicitly constructed and only reflects the change in the degree of freedom number.

[0080] Z T is the transposed matrix of the Z matrix;

[0081] 、 、 Belongs to the first system matrix; that is, the first system matrix includes 、 、 .

[0082] In some embodiments, all operating conditions are traversed and the corresponding n steady-state excitation vectors f(s) are assembled according to their respective linear constraints and excitation application positions, without considering their distribution in the operating conditions. A static load balancing strategy is used to evenly divide the n vectors among Nt threads for processing to ensure task balance (the difference is at most 1). The residual vectors processed in each thread are renumbered in the data structure so that their order is consistent with the substructure elimination order in AMLS. This order is based on the METIS sorting results, which helps to improve cache hit rate and promote the reuse of substructure data, thereby improving parallel computing efficiency, namely:

[0083] ;

[0084] in, is the i-th external steady-state excitation vector;

[0085] is the i-th external steady-state excitation vector (the first external steady-state excitation vector) after reordering.

[0086] S120, converting the first system matrix into a second system matrix through the constructed projection model; and converting the first external steady-state excitation vector into a second external steady-state excitation vector based on the positions of non-zero elements in the first external steady-state excitation vector.

[0087] In some embodiments, the and Projection to a lower-dimensional subspace:

[0088] ;

[0089] ;

[0090] ;

[0091] in, is the reordered system mass matrix, is the system mass matrix with reduced dimension after the AMLS method conversion;

[0092] is the reordered system damping matrix, is the system damping matrix with reduced dimension after transformation by the AMLS method.

[0093] is the reordered system stiffness matrix, is the system stiffness matrix with reduced dimension after AMLS conversion;

[0094] 、 、 Belongs to the second system matrix; that is, the second system matrix includes 、 、 ;

[0095] T is the projection matrix of the entire model (projection model) when the AMLS method is used for calculation;

[0096] is the transposed matrix of matrix T; it is not explicitly calculated in the actual calculation process, but can be implicitly expressed as follows:

[0097] ;

[0098] in, is the projection matrix of the i-th substructure;

[0099] is the number of substructures;

[0100] Further, It can be calculated as follows:

[0101] ;

[0102] Among them, Vi is the eigenvector of the i-th substructure;

[0103] Ns is the number of substructures;

[0104] Ai is all ancestor nodes of substructure i;

[0105] Ψij is the constraint mode matrix of substructure i and substructure j;

[0106] I is the identity matrix.

[0107] In summary, implicit calculation is:

[0108] ;

[0109] ;

[0110] ;

[0111] In some embodiments, the residual vector projection method proposed in the present invention may also refer to the above-mentioned implicit strategy to avoid constructing a large-scale dense matrix.

[0112] Specifically, the converted vector Project onto the same subspace:

[0113] ;

[0114] is the i-th external steady-state excitation vector after reordering, i.e., the second external steady-state excitation vector;

[0115] Furthermore, substitute the expression of T matrix:

[0116] ;

[0117] In some embodiments, when When there are fewer non-zero elements in , especially in single-point excitation conditions, where the number of non-zero elements is usually between a few and dozens, the second external steady-state excitation vector conversion can be performed in the following way.

[0118] Specifically, statistics The position of the non-zero element in the vector, find the corresponding substructure id of each position in the AMLS method according to the corresponding relationship, record all substructures, and construct the first structure combined with Set1;

[0119] Traverse all substructures in Set1 and put each substructure and all its corresponding ancestor nodes into Set2. Figure 2 As shown, if the substructure id in set Set1 is only 1, then the corresponding set Set2 contains substructures 1, 3, 7, and 15; if the substructure ids in set Set1 are 1 and 11, then the corresponding set Set2 contains substructures 1, 3, 7, 11, 13, 14, and 15;

[0120] By the following method, Conversion:

[0121] ;

[0122] Furthermore, in order to ensure load balancing, in the present invention, when Nt threads calculate n vector transformations, the OpenMP task statement can be used for dynamic strategy scheduling to solve the vector The problem is that the difference in the number of non-zero elements may be large.

[0123] S130: Calculate a residual vector based on the second system matrix and the second external steady-state excitation vector.

[0124] In some embodiments, when calculating residual vectors in units of working conditions, it is necessary to consider that the number of residual vectors for each working condition may be different. Therefore, when Nt threads calculate m working conditions, dynamic scheduling is also required, for example, the dynamic mode in the schedule statement in OpenMP.

[0125] Specifically, the modal space load vector is calculated:

[0126] ;

[0127] in, is the modal space load vector;

[0128] is the external steady-state excitation vector obtained by dimensionality reduction after AMLS conversion;

[0129] is the eigenvector matrix of the reduced dimension characteristic equation calculated in the AMLS method;

[0130] for The transpose of a matrix;

[0131] Calculate the loss load vector:

[0132] ;

[0133] in, is the loss load vector;

[0134] Solve the linear equations to calculate the projection matrix X:

[0135] ;

[0136] Where X is the projection matrix to be solved;

[0137] Solve for the generalized eigenvalues:

[0138] ;

[0139] in, is the eigenvalue;

[0140] Q is the eigenvector;

[0141] Compute the reduced dimension residual vector:

[0142] ;

[0143] in, is the dimension-reduced residual vector.

[0144] S140, based on the residual vector, calculate the global residual vector; based on the global residual vector, complete the dynamic stiffness analysis of the MPV trim body

[0145] In some embodiments, the global residual vector may be obtained by back substitution.

[0146] Specifically, back substitution is used to obtain the global residual vector after AMLS sorting:

[0147] ;

[0148] in, is the global residual vector matrix; in actual calculation, it can be combined with the back substitution calculation of the AMLS method to better utilize the cache characteristics of the computer to improve the calculation efficiency;

[0149] Furthermore, based on the degree of freedom correspondence of the reordered system degrees of freedom obtained in the above steps, the global residual vector of the finite element degree of freedom order is obtained in reverse:

[0150] ;

[0151] Where P is the global residual vector;

[0152] is the transposed matrix of the Z matrix.

[0153] According to the embodiments of the present invention, the following technical effects are achieved:

[0154] By identifying the minimum substructure set (Set1) and its ancestor set (Set2) involved in the non-zero terms of the excitation vector, the present invention significantly reduces the number of substructures involved in the projection calculation and realizes the efficient conversion of sparse excitation vectors, effectively improving the computational performance and storage efficiency of the dimensionality reduction load calculation in frequency response analysis.

[0155] In the projection stage, the present invention calculates on a per-residual-vector basis, does not rely on the balance of the number of residual vectors within the working condition, supports task allocation under arbitrary distribution conditions, and uses static partitioning to evenly distribute all residual vectors to multiple threads for execution, ensuring that the number of computational tasks for each thread is as consistent as possible.

[0156] During the calculation phase, the present invention adopts a dynamic grouping strategy based on working conditions. Based on the task and dynamic mechanisms provided by OpenMP, it supports flexible scheduling of unequal residual vectors under hundreds of working conditions and dynamically allocates parallel thread resources, effectively improving the overall computing throughput and multi-core resource utilization in multi-condition frequency response analysis.

[0157] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required by this application.

[0158] The above is an introduction to the method embodiment. The following is a device embodiment to further illustrate the solution described in this application.

[0159] Figure 3 FIG. 3 shows a block diagram of an MPV vehicle body dynamic stiffness analysis device 300 according to an embodiment of the present application, as shown in FIG. Figure 3 Shown include:

[0160] An acquisition module 310 is configured to acquire a reordered first system matrix of the MPV prepared body and a reordered first external steady-state excitation vector;

[0161] The conversion module 320 is configured to convert the first system matrix into a second system matrix using a first preset algorithm; and convert the first external steady-state excitation vector into a second external steady-state excitation vector using a second preset algorithm;

[0162] A first calculation module 330 is configured to calculate a residual vector based on the second system matrix and the second external steady-state excitation vector;

[0163] The second calculation module 340 is configured to calculate a global residual vector based on the residual vector; and perform a dynamic stiffness analysis of the MPV trim body based on the global residual vector.

[0164] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0165] Figure 4 A schematic diagram of the structure of a terminal device or server suitable for implementing an embodiment of the present application is shown.

[0166] like Figure 4As shown, the terminal device or server includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 into the random access memory (RAM) 403. Various programs and data required for the operation of the terminal device or server are also stored in the RAM 403. The CPU 401, ROM 402 and RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0167] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 408 including a hard disk; and a communication section 409 including a network interface card such as a LAN card or a modem. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. Removable media 411, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 410 as needed, so that computer programs read therefrom can be installed into the storage section 408 as needed.

[0168] In particular, according to an embodiment of the present application, the above method flow steps can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a machine-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication part 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, the above-mentioned functions defined in the system of the present application are executed.

[0169] It should be noted that the computer-readable medium shown in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this application, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, or any suitable combination thereof.

[0170] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the aforementioned module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0171] The units or modules involved in the embodiments described in this application may be implemented in software or hardware. The units or modules described may also be provided in a processor. The names of these units or modules do not, in certain circumstances, constitute limitations on the units or modules themselves.

[0172] As another aspect, the present application further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiments, or may exist independently and not be incorporated into the electronic device. The computer-readable storage medium stores one or more programs, which, when used by one or more processors, execute the method described in the present application.

[0173] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of application involved in this application is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the aforementioned application concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions applied for in this application.

Claims

1. A method for analyzing the dynamic stiffness of an MPV vehicle body, characterized in that: include: Obtaining a reordered first system matrix of the MPV trim body and a reordered first external steady-state excitation vector; The first system matrix includes the MPV curb body finite element mass matrix, the MPV curb body finite element damping matrix and the MPV curb body finite element stiffness matrix; The reordered first external steady-state excitation vector includes: Traverse all current working conditions and determine the reordered first external steady-state excitation vector based on the linear constraints and excitation application positions of each working condition; Converting the first system matrix into a second system matrix using the constructed projection model; converting the first external steady-state excitation vector into a second external steady-state excitation vector based on the positions of non-zero elements in the first external steady-state excitation vector; Calculating a residual vector based on the second system matrix and the second external steady-state excitation vector includes: Calculating a modal space load vector based on the second system matrix and the second external steady-state excitation vector; Calculating a loss load vector based on the second external steady-state excitation vector and the modal space load vector; calculating a projection matrix based on the second system matrix and the loss load vector; Calculating an eigenvector based on the projection matrix and the second system matrix; Calculating a residual vector based on the projection matrix and the eigenvector; Based on the residual vector, a global residual vector is calculated; based on the global residual vector, dynamic stiffness analysis of the MPV trim body is completed.

2. The method according to claim 1, characterized in that The converting the first system matrix into a second system matrix by using the constructed projection model includes: Based on the acquired working condition data, the projection matrix of the substructure is calculated; calculating a projection model based on the projection matrix of the substructure; Based on the projection model, the first system matrix is ​​converted into a second system matrix.

3. The method according to claim 2, characterized in that The calculation of the projection matrix of the substructure based on the acquired working condition data includes: ； Among them, V i is the eigenvector of the i-th substructure; Ns is the number of substructures; A i are all ancestor nodes of substructure i; Ψ ij is the constraint mode matrix of substructure i and substructure j; I is the identity matrix.

4. The method according to claim 3, characterized in that The converting the first external steady-state excitation vector into a second external steady-state excitation vector based on the position of the non-zero element in the first external steady-state excitation vector includes: Obtaining positions of non-zero elements in the first external steady-state excitation vector; constructing a first structural combination based on the position of the non-zero element; Traversing the first structure combination, and constructing a second structure set based on each substructure in the first structure combination and all ancestor nodes corresponding to each substructure; Based on the second structure set, the first external steady-state excitation vector is converted into a second external steady-state excitation vector.

5. The method according to claim 4, characterized in that The calculating the eigenvector based on the projection matrix and the second system matrix includes: ； in, is the system stiffness matrix obtained by transforming the second system matrix through the projection matrix; is the system mass matrix obtained by transforming the second system matrix through the projection matrix; is the eigenvalue; Q is the eigenvector.

6. The method according to claim 5, characterized in that The calculating a global residual vector based on the residual vector includes: Calculating a global residual vector matrix based on the residual vector and the model projection matrix; Based on the global residual vector matrix, the global residual vector is calculated by the following formula: ； in, is the global residual vector matrix; Z is the reordering transformation matrix; is the transformation matrix of the Z matrix.

7. An MPV body dynamic stiffness analysis device, characterized in that: include: An acquisition module, configured to acquire a reordered first system matrix of the MPV prepared body and a reordered first external steady-state excitation vector; The first system matrix includes the MPV curb body finite element mass matrix, the MPV curb body finite element damping matrix and the MPV curb body finite element stiffness matrix; The reordered first external steady-state excitation vector includes: Traverse all current working conditions and determine the reordered first external steady-state excitation vector based on the linear constraints and excitation application positions of each working condition; a conversion module, configured to convert the first system matrix into a second system matrix using the constructed projection model; and convert the first external steady-state excitation vector into a second external steady-state excitation vector based on the positions of non-zero elements in the first external steady-state excitation vector; A first calculation module, configured to calculate a residual vector based on the second system matrix and the second external steady-state excitation vector, includes: Calculating a modal space load vector based on the second system matrix and the second external steady-state excitation vector; Calculating a loss load vector based on the second external steady-state excitation vector and the modal space load vector; calculating a projection matrix based on the second system matrix and the loss load vector; Calculating an eigenvector based on the projection matrix and the second system matrix; Calculating a residual vector based on the projection matrix and the eigenvector; The second calculation module is used to calculate a global residual vector based on the residual vector; and complete the dynamic stiffness analysis of the MPV trim body based on the global residual vector.

8. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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