Vehicle finite element model correction method, device and equipment for NVH analysis

Abstract

The application relates to a whole vehicle finite element model correction method, device and equipment for NVH analysis. The method comprises the following steps: determining an initial standardized whole vehicle finite element model; adjusting a parameter variable of the whole vehicle finite element model within a preset parameter variable range; determining simulation frequency response functions of N preset reference points of the whole vehicle according to simulation of the whole vehicle finite element model under the parameter variable; determining test frequency response functions of the N preset reference points of the whole vehicle; determining optimized parameter variables of the corresponding parameters of each reference point when the correlation degree target function is maximum according to the simulation frequency response functions and the test frequency response functions, in combination with the correlation degree target function established between the simulation frequency response functions and the test frequency response functions; and performing weighted summation according to each optimized parameter variable and a preset weight coefficient to determine a correction parameter of the whole vehicle finite element model, so that the whole vehicle finite element model after parameter correction has high model precision, the accuracy of NVH analysis is improved, and the adjustment time of vehicle structure parameters is shortened.

Description

Technical Field

[0001] This invention is applicable to the field of NVH analysis, and particularly relates to a method, apparatus and equipment for correcting a whole vehicle finite element model for NVH analysis. Background Technology

[0002] In existing technologies, NVH analysis is usually performed using a whole vehicle finite element model. The whole vehicle finite element model is a hybrid vehicle model composed of super-element sub-module models and finite element sub-module models, which is established by modal synthesis. The advantage is that it improves the calculation speed of the model when the number of repeated calculations and time of the finite element sub-modules are changed. However, due to the low accuracy of this whole vehicle finite element model, the subsequent NVH analysis is inaccurate, which prolongs the calibration time of vehicle structural parameters and may even reduce the quality of the vehicle. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method, apparatus and equipment for correcting a whole vehicle finite element model for NVH analysis, so as to solve the problem that the low accuracy of existing whole vehicle finite element models affects the accuracy of NVH analysis.

[0004] Firstly, a method for correcting a whole vehicle finite element model for NVH analysis is provided, the method comprising the following steps:

[0005] Determine the initial standardized finite element model of the whole vehicle;

[0006] Adjust the parameter variables of the whole vehicle finite element model within the preset parameter variable range, and determine the simulation frequency response function of N preset benchmark points of the whole vehicle based on the simulation of the whole vehicle finite element model under the preset parameter variables, where N≥3;

[0007] Determine the test frequency response function of the N preset benchmark points of the vehicle;

[0008] Based on the simulated frequency response function and the test frequency response function, and combined with the correlation objective function established between the simulated frequency response function and the test frequency response function, the optimized parameter variables corresponding to the parameters of each benchmark point are determined when the correlation objective function is maximized;

[0009] The corrected parameters of the whole vehicle finite element model are determined by weighted summation of the optimized parameter variables corresponding to each benchmark point and the preset weight coefficients of the optimized parameter variables, and the corrected whole vehicle finite element model is obtained.

[0010] Secondly, a vehicle finite element model correction device for NVH analysis is provided, the device comprising:

[0011] The model standardization module is used to determine the initial standardized finite element model of the whole vehicle;

[0012] The simulation frequency response function determination module is used to adjust the parameter variables of the whole vehicle finite element model within a preset parameter variable range, and determine the simulation frequency response function of N preset benchmark points of the whole vehicle based on the simulation of the whole vehicle finite element model under the preset parameter variables, where N≥3;

[0013] The test frequency response function determination module is used to determine the test frequency response function of the N preset benchmark points of the vehicle;

[0014] The optimization parameter variable calculation module is used to determine the optimized parameter variables corresponding to the parameters of each benchmark point when the correlation objective function is maximized, based on the simulated frequency response function and the test frequency response function, combined with the correlation objective function established between the simulated frequency response function and the test frequency response function;

[0015] The parameter correction determination module is used to determine the correction parameters of the whole vehicle finite element model by performing a weighted summation based on the optimized parameter variables corresponding to each benchmark point and the preset weight coefficients of the optimized parameter variables, thereby obtaining the parameter-corrected whole vehicle finite element model.

[0016] Thirdly, embodiments of the present invention provide a computer device, the computer device including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the whole vehicle finite element model correction method as described in the first aspect.

[0017] The advantages of this invention compared to the prior art are:

[0018] The whole vehicle finite element model correction method, apparatus, and equipment of the present invention utilize the standardized whole vehicle finite element model to derive the test frequency response functions of N preset benchmark points, obtain the test frequency response functions of the benchmark points through actual measurement, and establish a correlation objective function between the simulation frequency response function and the test frequency response function. This enables the determination of relatively optimal optimization parameter variables within a preset parameter variable range, thereby determining the correction parameters of the whole vehicle finite element model, realizing the correction of the whole vehicle finite element model. Moreover, the corrected whole vehicle finite element model has high accuracy, which can improve the accuracy of NVH analysis and greatly shorten the calibration time of vehicle structural parameters, thereby helping to improve vehicle quality. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of an application environment for a method for correcting a whole vehicle finite element model provided in Embodiment 1 of the present invention;

[0021] Figure 2 This is a flowchart illustrating a method for correcting a finite element model of a whole vehicle, as provided in Embodiment 1 of the present invention.

[0022] Figure 3 This is a flowchart illustrating a method for correcting a finite element model of a whole vehicle, provided in Embodiment 2 of the present invention.

[0023] Figure 4 This is a schematic diagram of the structure of a vehicle finite element model correction device provided in Embodiment 3 of the present invention;

[0024] Figure 5 This is a schematic diagram of the structure of a computer device provided in Embodiment 4 of the present invention. Detailed Implementation

[0025] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0026] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0027] It should also be understood that the term “and / or” as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0028] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0029] Furthermore, in the description of this invention and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0030] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of the invention include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0031] It should be understood that the sequence number of each step in the following embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0032] To illustrate the technical solution of the present invention, specific embodiments are described below.

[0033] The first embodiment of this invention provides a method for correcting a whole vehicle finite element model for NVH analysis, which can be applied to applications such as... Figure 1 In this application environment, the client communicates with the server. Clients include, but are not limited to, handheld computers, desktop computers, laptops, ultra-mobile personal computers (UMPCs), netbooks, cloud computing devices, and personal digital assistants (PDAs). The server can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0034] See Figure 2 This is a flowchart illustrating a method for correcting a vehicle finite element model for NVH analysis, provided in Embodiment 1 of the present invention. The aforementioned model correction method can be applied to... Figure 1 For clients in the system, the model correction method may include the following steps:

[0035] Step 201: Determine the initial standardized finite element model of the whole vehicle.

[0036] The initial standardized finite element model of the whole vehicle includes finite element sub-module models and super-element sub-module models of each component, and the connection between the components is realized by using fixed coding rules.

[0037] In this step, the finite element model of the whole vehicle is managed by component and subsystem file. Different components and subsystems are built into separate finite element submodule models, and super-element calculations are performed on some component and subsystem models to obtain super-element submodule models. Furthermore, the model management format adopts a composition of component models, bushing connection parameter files, and calculation header files to achieve model management.

[0038] The above-mentioned whole vehicle finite element model uses a super element submodule model in part, mainly to facilitate faster parameter optimization in subsequent steps. Therefore, in one example, the initial standardized whole vehicle finite element model may only include the finite element submodule models of each component, without using the super element submodule model.

[0039] In this step, the connections between components and subsystems are managed using a separate connection file. All connection parameters are contained within this file, and the key connection points for each component and subsystem are coded according to a unified set of rules. This fixed coding system facilitates comparisons between experimental and simulation data in subsequent steps.

[0040] Step 202: Adjust the parameter variables of the whole vehicle finite element model within the preset parameter variable range, and determine the simulation frequency response function of N preset benchmark points of the whole vehicle based on the simulation of the whole vehicle finite element model under the preset parameter variables, where N≥3.

[0041] Specifically, the origin frequency response function of the whole vehicle finite element model is calculated using the header file, and the calculation result file is placed in the model management file directory. Before calculating the origin frequency response function, representative points in the whole vehicle finite element model are selected as preset benchmark points, and their origin frequency response functions are calculated as the simulation frequency response functions of N preset benchmark points of the whole vehicle.

[0042] Before obtaining the simulated frequency response function, N preset benchmark points need to be determined. In one example, the number of benchmark points N is at least three. The methods for selecting benchmark points can include:

[0043] Starting from the wheel center, the reference points are selected sequentially, moving from the farthest point of the vehicle body to the chassis side where the body connects to the chassis, according to the vibration isolation levels. Generally, no more than 5 and no less than 3 reference points are selected for a single suspension structure. For example, the reference points for the rear suspension of a four-link vehicle could be: p1 is the rear axle node, p2 is a point taken on the rear subframe, and p3 is the active side point of the rear trailing arm body connection point.

[0044] After determining N preset benchmark points, the parameter variables of the whole vehicle finite element model can be selected according to the preset parameter variable range, and the whole vehicle finite element model under the selected parameter variables can be simulated to obtain N simulation frequency response functions.

[0045] Optionally, the parameter variables of the whole vehicle finite element model include a first parameter variable and a second parameter variable. The first parameter variable is a weighting coefficient for the stiffness parameter of the chassis bushing, and the second parameter variable is a weighting coefficient for the damping parameter of the chassis bushing. The preset parameter variable range includes the range of the first parameter variable and the range of the second parameter variable, used to select the weighting coefficient of the stiffness parameter within the range of the first parameter variable and the weighting coefficient of the damping parameter within the range of the second parameter variable, so as to correct the stiffness and damping parameters of the bushing and update the whole vehicle finite element model. For example, the range of the first parameter variable can be (0.8, 1.2), and the range of the second parameter variable can be (0.3, 1.0).

[0046] Step 203: Determine the test frequency response function of the N preset benchmark points of the whole vehicle.

[0047] In step 202 above, after N preset benchmark points have been determined, the test frequency response function of the N preset benchmark points of the sample vehicle can be obtained by conducting test tests on the sample vehicle.

[0048] Step 204: Based on the simulated frequency response function and the test frequency response function, and combined with the correlation objective function established between the simulated frequency response function and the test frequency response function, determine the optimized parameter variables corresponding to the parameters of each benchmark point when the correlation objective function is maximized;

[0049] The formula for calculating the objective function of the correlation between the simulated frequency response function and the test frequency response function is as follows:

[0050]

[0051] Where Correlation represents the correlation degree of the objective function, S represents the simulated frequency response function, T represents the test frequency response function, and i represents the frequency point. S represents i conjugate, T represents i . conjugate.

[0052] In the above correlation objective function, the variables are the parameter variables of the whole vehicle finite element model used to obtain the simulated frequency response function. When the parameter variables change within the preset parameter variable range, new model parameters can be determined, and then a new whole vehicle finite element model can be determined. Based on the new whole vehicle finite element model, the simulated frequency response function of N preset benchmark points can be re-simulated and calculated. Substituting the simulated frequency response function of the N preset benchmark points obtained by re-simulation and calculation into the above formula, the correlation between the simulated frequency response function and the test frequency response function can be calculated.

[0053] Therefore, according to the formula above, by continuously adjusting the value of the parameter variable within the preset parameter variable range, several correlation values ​​can be calculated. For example, by continuously adjusting the value of the parameter variable M times within the preset parameter variable range, M correlation values ​​are calculated. The maximum value is selected from the M correlation values, and the parameter variable corresponding to the maximum value in the current adjustment is selected as the optimized parameter variable.

[0054] Optionally, the maximum value of the correlation objective function can be determined under preset constraints to obtain the optimized parameter variables corresponding to each benchmark point; the expression of the constraints is as follows:

[0055]

[0056] in, f represents the peak frequency of the test frequency response function within the bandwidth range. L-H The peak frequency of the simulated frequency response function is represented within the bandwidth range, and Δf represents the maximum limit of the preset peak difference.

[0057] Under the constraints of the above formula, the parameter variables cannot be arbitrarily adjusted within the preset parameter variable range. Only when the peak frequency difference between the simulated frequency response function obtained after adjusting the parameter variables in this instance and the test frequency response function within the preset bandwidth range is less than or equal to the maximum limit Δf, can the simulated frequency response function obtained from this variable adjustment be substituted into the above formula for calculating the correlation degree objective function to obtain the correlation degree.

[0058] If the peak frequency difference between the simulated frequency response function obtained after adjusting the parameters is greater than the maximum limit Δf within the preset bandwidth, then it is not necessary to calculate the correlation based on the simulated frequency response function obtained from this adjustment; the next adjustment of the parameters can be performed directly.

[0059] Step 205: Based on the optimized parameter variables corresponding to each benchmark point and the preset weight coefficients of the optimized parameter variables, perform a weighted summation to determine the correction parameters of the whole vehicle finite element model, and obtain the parameter-corrected whole vehicle finite element model.

[0060] Specifically, the above weighted summation includes: the weighted sum of the optimized parameter variables of the stiffness parameters corresponding to each benchmark point and the preset weight coefficients, and the weighted sum of the optimized parameter variables of the damping parameters corresponding to each benchmark point and the preset weight coefficients. The calculation formulas are as follows:

[0061]

[0062]

[0063] Where, δ jN δ represents the weighted sum of the optimized parameter variables and preset weight coefficients for stiffness parameters. jl w represents the optimization parameter variable for the stiffness parameter corresponding to the l-th benchmark point. l This indicates the preset weighting coefficient. This represents the weighted sum of the optimized parameter variables of the damping parameters and the preset weight coefficients. This represents the optimized parameter variable corresponding to the damping parameter of the l-th benchmark point.

[0064] In one example, when the three selected benchmark points are: p1 is the rear suspension axle node, p2 is the point on the rear subframe, and p3 is the active side point of the rear trailing arm body connection point, then the preset weighting coefficient w l This includes: axle joint weighting coefficient of 0.5, rear trailing arm weighting coefficient of 0.3, and subframe weighting coefficient of 0.2.

[0065] After determining the weighted sum, the formulas for calculating the correction parameters of the whole vehicle finite element model are as follows:

[0066] K′ j =δ jN ×K j

[0067]

[0068] Wherein, K′ j K represents the stiffness parameter of the j-th bushing after correction. j δ represents the initial stiffness parameter of the j-th bushing. jN C′ represents the weighted sum of the optimized parameter variables and preset weight coefficients of the stiffness parameters corresponding to each benchmark point. j C represents the damping parameter of the j-th bushing after correction. j This represents the initial damping parameter of the j-th bushing. This represents the weighted sum of the optimized parameter variables and preset weight coefficients corresponding to the damping parameters of each benchmark point, where N represents the number of benchmark points and j represents the chassis bushing number.

[0069] Based on the above calculation formula, the correction parameters (stiffness parameter K′) of the whole vehicle finite element model are obtained. jand damping parameter C′ j After that, the final corrected parameters are written into the bushing connection parameter file to update the corrected whole vehicle finite element model.

[0070] The vehicle finite element model correction method in this embodiment has the following advantages:

[0071] (1) The test frequency response functions of N preset benchmark points are obtained by using the standardized whole vehicle finite element model. The test frequency response functions of the benchmark points are obtained by actual measurement. The correlation objective function established by combining the simulation frequency response function and the test frequency response function can determine the relatively optimal optimization parameter variables within the preset parameter variable range. Then, the correction parameters of the whole vehicle finite element model are determined, and the correction of the whole vehicle finite element model is realized. The corrected whole vehicle finite element model has high accuracy. It can improve the accuracy of the analysis when used for NVH analysis, greatly shorten the calibration time of vehicle structural parameters, and thus help improve vehicle quality.

[0072] (2) The constraints added when establishing the correlation objective function further improved the accuracy of the corrected whole vehicle finite element model.

[0073] (3) This method is particularly suitable for multi-level vibration isolation finite element models, and can correct multiple transfer functions in the model to improve the model accuracy.

[0074] See Figure 3 This is a flowchart illustrating a method for correcting a vehicle finite element model for NVH analysis, as provided in Embodiment 2 of the present invention. Figure 3 As shown, the model correction method may include the following steps:

[0075] Step 301: Determine the initial standardized finite element model of the whole vehicle.

[0076] Step 302: Adjust the parameter variables of the whole vehicle finite element model within the preset parameter variable range, and determine the simulation frequency response function of N preset benchmark points of the whole vehicle based on the simulation of the whole vehicle finite element model under the preset parameter variables, where N≥3.

[0077] Step 303: Determine the test frequency response function of the N preset benchmark points of the whole vehicle.

[0078] Step 304: Based on the simulated frequency response function and the test frequency response function, and combined with the correlation objective function established between the simulated frequency response function and the test frequency response function, determine the optimized parameter variables corresponding to the parameters of each benchmark point when the correlation objective function is maximized.

[0079] Step 305: Based on the optimized parameter variables corresponding to each benchmark point and the preset weight coefficients of the optimized parameter variables, perform a weighted summation to determine the correction parameters of the whole vehicle finite element model, and obtain the parameter-corrected whole vehicle finite element model.

[0080] Steps S301 to S305 are the same as steps S201 to S205 above, and can be referred to the description of steps S201 to S205, which will not be repeated here.

[0081] Step S306: The parameter-corrected finite element model of the vehicle is tested and judged. If the judgment result meets the preset conditions, the parameter-corrected finite element model of the vehicle is used for NVH analysis.

[0082] Step S307: If the judgment result is that the preset conditions are not met, the preset parameter variable range and / or the preset weight coefficient are adjusted, and the whole vehicle finite element model is revised again until a whole vehicle finite element model that meets the preset conditions is obtained.

[0083] Specifically, the detection and judgment of the parameter-corrected finite element model of the whole vehicle includes:

[0084] Based on the parameter-corrected multi-level vibration isolation finite element model, a multi-level out-of-point frequency response function is simulated and calculated, i.e., the simulated multi-level out-of-point frequency response function; the multi-level out-of-point frequency response function detected when testing the sample vehicle is obtained; the detected multi-level out-of-point frequency response function curve is compared with the simulated multi-level out-of-point frequency response function curve. If the comparison result is consistent, it is determined that the preset condition is met; if the comparison result is inconsistent, it is determined that the preset condition is not met.

[0085] In one example, the method to determine whether the comparison results are consistent can be as follows: substitute the simulated multi-level outlier frequency response function and the detected multi-level outlier frequency response function into the calculation formula of the correlation objective function above, and calculate the correlation. When the calculated correlation is greater than the set threshold, the comparison results are considered consistent; when the calculated correlation is not greater than the set threshold, the comparison files are considered inconsistent.

[0086] The vehicle finite element model correction method in this embodiment, in addition to having the advantages of the vehicle finite element model correction method in Embodiment 1, can also perform accuracy verification on the corrected vehicle finite element model. That is, it uses the comparison results between the multi-level out-of-point frequency response function curve and the simulated multi-level out-of-point frequency response function to determine whether the accuracy verification has passed.

[0087] Corresponding to the method in the above embodiments, Figure 4A structural block diagram of a vehicle finite element model correction device for NVH analysis provided in Embodiment 3 of the present invention is shown. This model correction device is applied to a computer device, which connects to a target database through a preset application programming interface (API). When the target database is driven to run and perform corresponding tasks, corresponding task logs are generated, which can be collected via the API. For ease of explanation, only the parts relevant to the embodiments of the present invention are shown.

[0088] See Figure 4 The model correction device includes:

[0089] Model standardization module 41 is used to determine the initial standardized finite element model of the whole vehicle;

[0090] The simulation frequency response function determination module 42 is used to adjust the parameter variables of the whole vehicle finite element model within a preset parameter variable range, and determine the simulation frequency response function of N preset benchmark points of the whole vehicle based on the simulation of the whole vehicle finite element model under the parameter variables, where N≥3;

[0091] The test frequency response function determination module 43 is used to determine the test frequency response function of the N preset benchmark points of the vehicle.

[0092] The optimization parameter variable calculation module 44 is used to determine the optimized parameter variables of the corresponding parameters of each benchmark point when the correlation objective function is maximized, based on the simulation frequency response function and the test frequency response function, combined with the correlation objective function established between the simulation frequency response function and the test frequency response function;

[0093] The parameter correction determination module 45 is used to determine the correction parameters of the whole vehicle finite element model by performing a weighted summation based on the optimized parameter variables corresponding to each benchmark point and the preset weight coefficients of the optimized parameter variables, thereby obtaining the parameter-corrected whole vehicle finite element model.

[0094] Optionally, the above model standardization module 41 includes:

[0095] The finite element submodule model and super-element submodule model of each component are used to realize the connection between the components using fixed coding rules.

[0096] Optionally, in the above-mentioned simulation frequency response function determination module 42, the parameter variables of the whole vehicle finite element model include a first parameter variable and a second parameter variable. The first parameter variable is the weighting coefficient of the stiffness parameter of the chassis bushing, and the second parameter variable is the weighting coefficient of the damping parameter of the chassis bushing. The preset parameter variable range includes the range of the first parameter variable and the range of the second parameter variable.

[0097] Optionally, the above-mentioned optimization parameter variable calculation module 44 includes:

[0098] The correlation calculation module is used to calculate the correlation between the simulated frequency response function and the test frequency response function. The calculation model of the correlation calculation module is as follows:

[0099]

[0100] Where Correlation represents the correlation degree of the objective function, S represents the simulated frequency response function, T represents the test frequency response function, and i represents the frequency point. S represents i conjugate, T represents i . conjugate.

[0101] Optionally, the above-mentioned correction parameter determination module 45 includes:

[0102] The stiffness parameter calculation module is used to calculate the stiffness parameter of the j-th bushing after correction. The calculation model is as follows:

[0103] K′ j =δ jN ×K j

[0104] Wherein, K′ j K represents the stiffness parameter of the j-th bushing after correction. j δ represents the initial stiffness parameter of the j-th bushing. jN This represents the weighted sum of the optimized parameter variables and preset weight coefficients of the stiffness parameters corresponding to each benchmark point, where N represents the number of benchmark points and j represents the chassis bushing number.

[0105] The damping parameter calculation module is used to calculate the damping parameters of the j-th bushing after correction. The calculation model is as follows:

[0106]

[0107] Among them, C′ j C represents the damping parameter of the j-th bushing after correction. j This represents the initial damping parameter of the j-th bushing. This represents the weighted sum of the optimized parameter variables and preset weight coefficients corresponding to the damping parameters of each benchmark point, where N represents the number of benchmark points and j represents the chassis bushing number.

[0108] Optionally, the above-mentioned correction parameter determination module 45 also includes:

[0109] The weighted sum calculation module is used to calculate the weighted sum of the optimized parameter variables of the stiffness parameters corresponding to each benchmark point and the preset weight coefficients, and the weighted sum of the optimized parameter variables of the damping parameters corresponding to each benchmark point and the preset weight coefficients. The calculation formulas are as follows:

[0110]

[0111]

[0112] Where, δ jN δ represents the weighted sum of the optimized parameter variables and preset weight coefficients for stiffness parameters. jl w represents the optimization parameter variable for the stiffness parameter corresponding to the l-th benchmark point. l This indicates the preset weighting coefficient. This represents the weighted sum of the optimized parameter variables of the damping parameters and the preset weight coefficients. This represents the optimized parameter variable corresponding to the damping parameter of the l-th benchmark point.

[0113] Optionally, the optimization parameter variable calculation module 44 also includes:

[0114] The constraint module is used to determine the maximum value of the correlation objective function under preset constraints, so as to obtain the optimized parameter variables corresponding to each benchmark point; the expression of the constraint conditions is as follows:

[0115]

[0116] in, f represents the peak frequency of the test frequency response function within the bandwidth range. L-H The peak frequency of the simulated frequency response function is represented within the bandwidth range, and Δf represents the maximum limit of the preset peak difference.

[0117] Optionally, the above-mentioned model correction device further includes:

[0118] The inspection module is used to inspect and judge the whole vehicle finite element model after parameter correction. If the judgment result is that the preset conditions are met, NVH analysis is performed using the whole vehicle finite element model after parameter correction.

[0119] If the judgment result is that the preset conditions are not met, the preset parameter variable range and / or the preset weight coefficient are adjusted, and the whole vehicle finite element model is revised again until a whole vehicle finite element model that meets the preset conditions is obtained.

[0120] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of the present invention. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0121] Figure 5 This is a schematic diagram of the structure of a computer device provided in Embodiment 4 of the present invention. Figure 5 As shown, the computer device of this embodiment includes: at least one processor ( Figure 5 Only one is shown in the diagram), a memory, and a computer program stored in the memory that can run on at least one processor. When the processor executes the computer program, it implements the steps in any of the above embodiments of the whole vehicle finite element model correction method.

[0122] This computer device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that... Figure 5 The examples of computer devices are merely examples and do not constitute a limitation on computer devices. Computer devices may include more or fewer components than shown in the illustration, or combinations of certain components, or different components, such as network interfaces, displays, and input devices.

[0123] The processor referred to can be a CPU, but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0124] Memory includes readable storage media, internal memory, etc., wherein internal memory can be the RAM of a computer device, providing an environment for the operation of the operating system and computer-readable instructions stored in the readable storage media. The readable storage media can be the hard drive of a computer device, or in other embodiments, it can be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, memory can include both internal storage units and external storage devices of a computer device. Memory is used to store the operating system, applications, bootloader, data, and other programs, such as program code for computer programs. Memory can also be used to temporarily store data that has been output or will be output.

[0125] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the functions described above can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this invention. The specific working process of the units and modules in the above device can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the processes in the methods of the above embodiments by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium can include at least: any entity or device capable of carrying computer program code, a recording medium, a computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0126] The present invention can implement all or part of the processes in the methods of the above embodiments, or it can be accomplished by a computer program product. When the computer program product is run on a computer device, the computer device executes the steps in the above method embodiments.

[0127] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0128] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0129] In the embodiments provided by this invention, it should be understood that the disclosed apparatus / computer devices and methods can be implemented in other ways. For example, the apparatus / computer device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0130] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0131] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for correcting a whole vehicle finite element model for NVH analysis, characterized in that, Includes the following steps: Determine the initial standardized finite element model of the whole vehicle; Adjust the parameter variables of the whole vehicle finite element model within the preset parameter variable range, and determine the simulation frequency response function of N preset benchmark points of the whole vehicle based on the simulation of the whole vehicle finite element model under the preset parameter variables, where N≥3; Determine the test frequency response function of the N preset benchmark points of the vehicle; Based on the simulated frequency response function and the test frequency response function, and combined with the correlation objective function established between the simulated frequency response function and the test frequency response function, the optimized parameter variables corresponding to the parameters of each benchmark point are determined when the correlation objective function is maximized; The corrected parameters of the whole vehicle finite element model are determined by weighted summation based on the optimized parameter variables corresponding to each of the benchmark points and the preset weight coefficients of the optimized parameter variables, and the corrected whole vehicle finite element model is obtained. The parameter variables of the whole vehicle finite element model include a first parameter variable and a second parameter variable. The first parameter variable is the weighting coefficient of the stiffness parameter of the chassis bushing, and the second parameter variable is the weighting coefficient of the damping parameter of the chassis bushing. The preset parameter variable range includes the range of the first parameter variable and the range of the second parameter variable. The formulas for calculating the weighted sum of the optimized parameter variables and preset weight coefficients for the stiffness parameters corresponding to each benchmark point, and the weighted sum of the optimized parameter variables and preset weight coefficients for the damping parameters corresponding to each benchmark point are as follows: in, This represents the weighted sum of the optimized parameter variables for stiffness and the preset weight coefficients. Indicates the first l The optimization parameter variables for the stiffness parameters corresponding to each benchmark point. This indicates the preset weighting coefficient. This represents the weighted sum of the optimized parameter variables of the damping parameters and the preset weight coefficients. Indicates the first l The optimization parameter variables corresponding to the damping parameters of each benchmark point.

2. The method for correcting the finite element model of a vehicle according to claim 1, characterized in that, The initial standardized finite element model of the whole vehicle includes finite element sub-module models and super-element sub-module models of each component, and the connection between the components is realized by using fixed coding rules.

3. The method for correcting the finite element model of a whole vehicle according to claim 1, characterized in that, The formula for calculating the objective function of the correlation between the simulated frequency response function and the test frequency response function is as follows: Where Correlation represents the correlation degree of the objective function, S represents the simulated frequency response function, T represents the test frequency response function, and i represents the frequency point. express conjugate, express . conjugate.

4. The method for correcting the finite element model of a whole vehicle according to claim 1, characterized in that, The calculation formulas for the correction parameters of the whole vehicle finite element model are as follows: in, This represents the stiffness parameter of the j-th bushing after correction. This represents the initial stiffness parameter of the j-th bushing. This represents the weighted sum of the optimized parameter variables and preset weight coefficients for the stiffness parameters corresponding to each benchmark point. This represents the damping parameter of the j-th bushing after correction. This represents the initial damping parameter of the j-th bushing. This represents the weighted sum of the optimized parameter variables and preset weight coefficients corresponding to the damping parameters of each benchmark point, where N represents the number of benchmark points and j represents the chassis bushing number.

5. The method for correcting the finite element model of a vehicle according to claim 1, characterized in that, The correction method further includes: Under preset constraints, the maximum value of the correlation objective function is determined to obtain the optimized parameter variables corresponding to each benchmark point; the expression of the constraints is as follows: in, This represents the peak frequency of the test frequency response function within the bandwidth range. This represents the peak frequency of the simulated frequency response function within the bandwidth range. This indicates the maximum limit of the preset peak difference.

6. The method for correcting the finite element model of a whole vehicle according to claim 1, characterized in that, After obtaining the parameter-corrected finite element model of the whole vehicle, the following steps are also included: The vehicle finite element model after parameter correction is tested and judged. If the judgment result is that the preset conditions are met, NVH analysis is performed using the vehicle finite element model after parameter correction. If the judgment result is that the preset conditions are not met, the preset parameter variable range and / or the preset weight coefficient are adjusted, and the whole vehicle finite element model is revised again until a whole vehicle finite element model that meets the preset conditions is obtained.

7. A device for correcting a whole vehicle finite element model for NVH analysis, characterized in that, The device includes: The model standardization module is used to determine the initial standardized finite element model of the whole vehicle; The simulation frequency response function determination module is used to adjust the parameter variables of the whole vehicle finite element model within a preset parameter variable range, and determine the simulation frequency response function of N preset benchmark points of the whole vehicle based on the simulation of the whole vehicle finite element model under the preset parameter variables, where N≥3; The test frequency response function determination module is used to determine the test frequency response function of the N preset benchmark points of the vehicle; The optimized parameter variable calculation module is used to determine the optimized parameter variables corresponding to the parameters of each benchmark point when the correlation objective function is maximized, based on the simulated frequency response function and the test frequency response function, combined with the correlation objective function established between the simulated frequency response function and the test frequency response function; The parameter correction determination module is used to determine the correction parameters of the whole vehicle finite element model by performing a weighted summation based on the optimized parameter variables corresponding to each of the benchmark points and the preset weight coefficients of the optimized parameter variables, so as to obtain the whole vehicle finite element model after parameter correction. The parameter variables of the whole vehicle finite element model include a first parameter variable and a second parameter variable. The first parameter variable is the weighting coefficient of the stiffness parameter of the chassis bushing, and the second parameter variable is the weighting coefficient of the damping parameter of the chassis bushing. The preset parameter variable range includes the range of the first parameter variable and the range of the second parameter variable. The formulas for calculating the weighted sum of the optimized parameter variables and preset weight coefficients for the stiffness parameters corresponding to each benchmark point, and the weighted sum of the optimized parameter variables and preset weight coefficients for the damping parameters corresponding to each benchmark point are as follows: in, This represents the weighted sum of the optimized parameter variables for stiffness and the preset weight coefficients. Indicates the first l The optimization parameter variables for the stiffness parameters corresponding to each benchmark point. This indicates the preset weighting coefficient. This represents the weighted sum of the optimized parameter variables of the damping parameters and the preset weight coefficients. Indicates the first l The optimization parameter variables corresponding to the damping parameters of each benchmark point.

8. A computer device, characterized in that, The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the whole vehicle finite element model correction method as described in any one of claims 1 to 6.

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