Vehicle back door abnormal sound simulation method, device and equipment and storage medium

Abstract

The invention discloses a vehicle back door abnormal sound simulation method and device, equipment and a storage medium. The vehicle back door abnormal sound simulation method comprises the following steps: acquiring acceleration load data and spring displacement corresponding to a wheel center of a vehicle; the acceleration load data and the spring displacement are simulated, a simulation result of the back door of the vehicle is obtained, the simulation result comprises the fact that the position where each contact pair is located is an abnormal sound risk position or a normal position, and each contact pair represents a node pairing unit set established at a gap between the back door of the vehicle and a vehicle body of the vehicle. According to the scheme, the simulation efficiency of the back door can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobile simulation, in particular to a vehicle back door abnormal sound simulation method, device, equipment and storage medium. BACKGROUND

[0002] In the field of automobile technology, there is generally a gap between the outer trim of the back door of the vehicle and the sheet metal part of the vehicle body. During the whole vehicle fatigue durability test, due to the road excitation, the relative displacement between the outer trim and the sheet metal part of the vehicle body occurs. When the relative displacement value exceeds the assembly gap, the collision and friction phenomenon occurs, the back door produces abnormal sound, and the paint grinding problem occurs, which affects the quality of the vehicle. In the traditional prediction process of the paint grinding problem of the back door of the vehicle, sensors need to be arranged at multiple position points of the vehicle body to collect dynamic loads at multiple position points of the vehicle body to predict the abnormal sound position of the back door. However, this method will arrange more sensors, and the prediction process is time-consuming and the prediction accuracy is low, and the simulation efficiency is low.

[0003] Therefore, there is an urgent need for a back door abnormal sound simulation method. SUMMARY

[0004] The present application at least provides a vehicle back door abnormal sound simulation method, device, equipment and storage medium.

[0005] The present application provides a vehicle back door abnormal sound simulation method, comprising: obtaining acceleration load data corresponding to a wheel center of a vehicle and spring displacement; simulating the acceleration load data and the spring displacement to obtain a simulation result of a back door of the vehicle, the simulation result comprising each contact pair being at an abnormal sound risk position or a normal position, and each contact pair representing a node pairing unit group established at a gap between the back door of the vehicle and a vehicle body.

[0006] In some embodiments, simulating the acceleration load data and the spring displacement to obtain the simulation result of the back door of the vehicle comprises: determining target relative displacements of each contact pair based on the acceleration load data and the spring displacement; and analyzing each target relative displacement value to obtain the simulation result.

[0007] In some embodiments, determining the target relative displacement value of each contact pair based on the acceleration load data and the spring displacement comprises: inputting the acceleration load data and the spring displacement into a preset iterative model to obtain a target time domain displacement load of a preset attachment point of the vehicle output by the preset iterative model; and determining the target relative displacement value of each contact pair based on the target time domain displacement load.

[0008] In some embodiments, the acceleration load data and the spring displacement are input into the preset iterative model to obtain a target time-domain displacement load of a preset position of the vehicle output by the preset iterative model, including: performing initial iteration on the acceleration load data and the spring displacement to obtain an initial time-domain displacement load of a wheel center of the vehicle; and performing target iteration on the initial time-domain displacement load to obtain the target time-domain displacement load.

[0009] In some embodiments, based on the target time-domain displacement load, a target relative displacement value of each contact pair is determined, including: constructing a whole vehicle finite element model, the whole vehicle finite element model including each contact pair; and inputting the target time-domain displacement load into the whole vehicle finite element model to obtain the target relative displacement value of each contact pair output by the whole vehicle finite element model.

[0010] In some embodiments, the target relative displacement values are analyzed to obtain a simulation result, including: for each target relative displacement value, in response to the target relative displacement value being greater than a preset relative displacement value, determining a position of a contact pair corresponding to the target relative displacement value as a abnormal noise risk position; and for each target relative displacement value, in response to the target relative displacement value being less than or equal to the preset relative displacement value, determining a position of a contact pair corresponding to the target relative displacement value as a normal position.

[0011] In some embodiments, the vehicle back door abnormal noise simulation method further includes: for each contact pair, in response to the position of the contact pair being the abnormal noise risk position, taking the target relative displacement value of the contact pair as to-be-processed data; performing modal contribution analysis on each to-be-processed data to obtain a contribution analysis result, the contribution analysis result including a contribution sorting of a plurality of preset vibration modes; and taking a preset vibration mode in a preset ranking in the contribution sorting as a to-be-adjusted vibration mode.

[0012] The application provides a vehicle back door abnormal noise simulation device, including: an acquisition module and a simulation module; the acquisition module is used to acquire acceleration load data corresponding to a wheel center of a vehicle and a spring displacement; and the simulation module is used to simulate the acceleration load data and the spring displacement to obtain a simulation result of a back door of the vehicle, the simulation result including a position of at least one contact pair being an abnormal noise risk position or a normal position, the contact pair representing a node pairing unit group established at a gap between the back door of the vehicle and a vehicle body of the vehicle.

[0013] The application provides an electronic device including a memory and a processor, the processor being configured to execute program instructions stored in the memory to implement the vehicle back door abnormal noise simulation method.

[0014] The application provides a computer-readable storage medium having program instructions stored thereon, the program instructions being configured to be executed by a processor to implement the vehicle back door abnormal noise simulation method.

[0015] Compared with the method of predicting the abnormal sound problem of the back door by arranging sensors to collect dynamic loads of multiple position points of the vehicle body, the method provided by the application has low accuracy in predicting the abnormal sound risk. The acceleration load data corresponding to the wheel center of the vehicle and the spring displacement are obtained, the acceleration load data and the spring displacement are simulated, and the simulation result of the back door of the vehicle is obtained. The simulation result includes whether each contact pair is located at an abnormal sound risk position or a normal position, which can improve the accuracy of the abnormal sound risk position and improve the simulation efficiency.

[0016] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, rather than limiting the application. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the application and, together with the description, serve to explain the principles of the application.

[0018] Figure 1 is a flowchart of an embodiment of the vehicle back door abnormal sound simulation method of the application Figure 1 ;

[0019] Figure 2 is a flowchart of an embodiment of the vehicle back door abnormal sound simulation method of the application Figure 2 ;

[0020] Figure 3 is a flowchart of an embodiment of the vehicle back door abnormal sound simulation method of the application Figure 3 ;

[0021] Figure 4 is a flowchart of an embodiment of the vehicle back door abnormal sound simulation method of the application Figure 4 ;

[0022] Figure 5 is a flowchart of an embodiment of the vehicle back door abnormal sound simulation method of the application Figure 5 ;

[0023] Figure 6 is a rear view of the vehicle in an embodiment of the vehicle back door abnormal sound simulation method of the application

[0024] Figure 7 is a structural schematic diagram of an embodiment of the vehicle back door abnormal sound simulation device of the application

[0025] Figure 8 is a structural schematic diagram of an embodiment of the electronic device of the application

[0026] Figure 9 is a structural schematic diagram of an embodiment of the computer readable storage medium of the application DETAILED DESCRIPTION

[0027] The scheme of the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0028] In the following description, specific details are set forth in order to provide a thorough understanding of the present application. The present application can be practiced without resorting to the details specific.

[0029] The term "and / or", only describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. In addition, the character " / " in this paper generally represents that the front and rear associated objects are a "or" relationship. In addition, "multiple" in this paper means two or more than two. In addition, the term "at least one" in this paper means any one of multiple or any combination of at least two of multiple, for example, including at least one of A, B and C, which can mean including any one or more elements selected from the set consisting of A, B and C.

[0030] The present application provides some vehicle back door abnormal sound simulation methods and vehicle back door abnormal sound simulation devices. The application scenarios of the vehicle back door abnormal sound simulation method include but are not limited to the simulation of the abnormal sound of the back door of the vehicle. The execution subject of the vehicle back door abnormal sound simulation method can be a vehicle back door abnormal sound simulation device. For example, the vehicle back door abnormal sound simulation device can be arranged in a terminal device or a server or other processing device, wherein the terminal device can be a device for simulating the abnormal sound of the back door of the vehicle, a user equipment (User Equipment, UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle-mounted device, etc. In some possible implementation ways, the vehicle back door abnormal sound simulation method can be realized by calling the computer readable instructions stored in the memory by the processor.

[0031] Please refer to Figure 1 , Figure 1 is the flowchart of an embodiment of the vehicle back door abnormal sound simulation method of the present application Figure 1 . Specifically, the vehicle back door abnormal sound simulation method can include the following steps:

[0032] Step S11: obtaining the acceleration load data corresponding to the wheel center of the vehicle and the spring displacement.

[0033] The vehicle is a vehicle to be simulated. The wheel hub of the vehicle is a core load-bearing component of the wheel system, located at the center of the wheel, responsible for connecting the axle and the wheel, and bearing the weight of the vehicle and transmitting power. The wheel hub of the vehicle can refer to the wheel hub of at least one wheel of the vehicle. The wheel hub acceleration load data refers to the acceleration value of the wheel hub of the vehicle during driving. The spring displacement represents the deformation displacement of the shock-absorbing spring corresponding to the wheel hub of the vehicle during driving.

[0034] In some application scenarios, the way to obtain the acceleration load data of the wheel hub of the vehicle can be to use the sensor corresponding to the wheel hub of the vehicle to collect the acceleration load data. In some application scenarios, the way to obtain the spring displacement can be to use the sensor corresponding to the shock-absorbing spring to collect the spring displacement. In other application scenarios, the above step S11 can be to use the sensor corresponding to the wheel of the vehicle to collect the acceleration load data of the wheel hub of the vehicle and the spring displacement.

[0035] Step S12: Simulate the acceleration load data and the spring displacement to obtain the simulation result of the back door of the vehicle.

[0036] The simulation result includes positions of each contact pair as abnormal noise risk positions or normal positions. Each contact pair represents a node pairing unit group established at the gap between the back door of the vehicle and the vehicle body. The number of contact pairs can be one or more. The contact pair refers to a node pairing unit group used to describe the interaction between the back door and the vehicle body during simulation. The vehicle body can refer to the vehicle structure adjacent to the back door, and there is a gap between the vehicle body and the back door. The node pairing unit group of each contact pair corresponds to a position coordinate, which can be used to determine whether the position is an abnormal noise risk position or a normal position. The position of the contact pair represents the position coordinate corresponding to the node pairing unit group of the contact pair. Specifically, the node pairing unit group of the contact pair includes two virtual nodes, specifically a first virtual node and a second virtual node. The first virtual node is on the target surface of the back door, and the second virtual node is on the target surface of the vehicle body. The first virtual node and the second virtual node are oppositely arranged. The target surface of the back door and the target surface of the vehicle body are opposite surfaces. The position coordinate corresponding to the node pairing unit group of the contact pair includes a first position coordinate of the first virtual node on the back door coordinate system and a second position coordinate of the second virtual node on the vehicle body coordinate system. In some application scenarios, the back door coordinate system and the vehicle body coordinate system can be the same coordinate system or different coordinate systems. The abnormal noise risk position represents a higher risk of back door abnormal noise at the position coordinate corresponding to the node pairing unit group of the contact pair. The normal risk position represents a lower risk of back door abnormal noise at the position coordinate corresponding to the node pairing unit group of the contact pair.

[0037] In some application scenarios, step S12 may involve pre-establishing a simulation model, inputting the acceleration load data and spring displacement into the simulation model, and obtaining a simulation result output by the simulation model. The simulation model may include a pre-established preset iterative model and / or a vehicle finite element model. The simulation model is used to simulate the acceleration load data and spring displacement to obtain a simulation result for the vehicle's tailgate.

[0038] Considering that the relative displacement between the tailgate and the vehicle body is affected by the excitation force from the road surface during driving, wherein the excitation force from the road surface is transmitted through the ground to the wheel, then to the wheel hub bearing, and then through the vehicle body to the tailgate, this application only obtains the acceleration load data and spring displacement corresponding to the vehicle's wheel hub to simulate the abnormal noise of the vehicle's tailgate. Based on the acceleration load data and spring displacement, the dynamic response of the vehicle under different driving conditions is simulated. The simulation results are obtained through the relative motion between the tailgate and the vehicle body, which can improve the simulation efficiency and accuracy.

[0039] Compared with the above scheme that only collects dynamic loads at multiple positions of the vehicle body by arranging sensors to predict the abnormal noise problem of the tailgate, which results in lower accuracy in predicting the abnormal noise risk, the present application obtains the acceleration load data and spring displacement corresponding to the wheel center of the vehicle, simulates the acceleration load data and spring displacement, and obtains the simulation results of the tailgate of the vehicle. The simulation results include whether the position of each contact pair is an abnormal noise risk position or a normal position, which can improve the accuracy of the abnormal noise risk position and improve the simulation efficiency.

[0040] See also Figure 2 , Figure 2 This is a flow chart of an embodiment of the vehicle back door abnormal noise simulation method of the present application. Figure 2 .

[0041] In some embodiments, the above step S12 may include the following steps:

[0042] Step S21: Determine the target relative displacement of each contact pair based on the acceleration load data and the spring displacement. Step S22: Analyze each target relative displacement value to obtain a simulation result.

[0043] The target relative displacement of a contact pair represents the relative displacement between virtual nodes in the node pairing unit group of the contact pair. In some application scenarios, step S21 may be performed by inputting the acceleration load data and spring displacement into the full vehicle finite element model to obtain the target relative displacement of each contact pair output by the full vehicle finite element model.

[0044] See also Figure 3 , Figure 3 This is a flow chart of an embodiment of the vehicle back door abnormal noise simulation method of the present application. Figure 3 .

[0045] In some embodiments, the step S21 can include the following steps: a step S31 of inputting the acceleration load data and the spring displacement into a preset iterative model to obtain a target time-domain displacement load of a preset attachment point of the vehicle output by the preset iterative model. A step S32 of determining a target relative displacement value of each contact pair based on the target time-domain displacement load.

[0046] The preset iterative model is used to perform at least one round of iteration on the acceleration load data and the spring displacement corresponding to the wheel center of the vehicle to obtain the target time-domain displacement load of the preset attachment point of the vehicle. For example, the preset iterative model is a virtual iterative model of vehicle dynamics.

[0047] The preset attachment point of the vehicle is a body and chassis attachment point, and specifically includes at least one of a front and rear shock absorber mounting point, a subframe mounting point, and a trailing arm mounting point. The target time-domain displacement load represents the displacement load of all hard points at which the chassis suspension is connected to the vehicle body.

[0048] In some application scenarios, before the step S31, the vehicle back door abnormal sound simulation method further includes constructing a preset iterative model. The construction of the preset iterative model includes: establishing a virtual iterative model of vehicle dynamics, in which the suspension, the steering and the vehicle body are all rigid bodies, the stabilizer bar body is a linear beam flexible body, and a six-component force and motion driving is used. The mass of the front and rear axles of the virtual iterative model of vehicle dynamics has an error of about 15 N with the test load, and the simulation model has accurate mass.

[0049] In some application scenarios, the step S31 can be one round of iteration or multiple rounds of iteration on the acceleration load data and the spring displacement corresponding to the wheel center of the vehicle to obtain the target time-domain displacement load of the preset attachment point of the vehicle.

[0050] Please refer to Figure 4 , Figure 4 is a flowchart of an embodiment of the vehicle back door abnormal sound simulation method of the present application Figure 4 .

[0051] In some embodiments, the step S31 can include the following steps: a step S41 of performing initial iteration on the acceleration load data and the spring displacement to obtain an initial time-domain displacement load of the wheel center of the vehicle. A step S42 of performing target iteration on the initial time-domain displacement load to obtain the target time-domain displacement load.

[0052] The initial time-domain displacement load represents the vertical driving time-domain displacement of the wheel center of the vehicle. The initial iteration can be the first round of iteration in the preset iterative model. The target iteration can be an iteration after the first round of iteration in the healing iterative model.

[0053] In some application scenarios, the step S41 can be to first inversely solve an initial external excitation according to a preset parameter. For example, the initial external excitation can be a vertical driving time-domain displacement of the wheel center, which is set in advance as an input of an initial iteration module in a preset iteration model. Then, the initial external excitation is simulated and compared with the test, the inversely solved initial external excitation is input into the initial iteration module of the preset iteration model, and a simulation response signal is calculated. The simulation response signal can be a simulation spring displacement and / or a simulation wheel center acceleration load data. The simulation response signal is compared with a response signal measured by the test, an error is calculated and used as a first target error. The response signal measured by the test is an acceleration load data and a spring displacement input into the preset iteration model. Then, the initial external excitation is iteratively adjusted according to the first target error, a final initial external excitation is obtained, and the final initial external excitation is used as an initial time-domain displacement load of the wheel center of the vehicle obtained by the initial iteration. Specifically, the initial external excitation is iteratively adjusted according to the first target error to obtain the final initial external excitation, which includes: according to the first target error, parameters are adjusted constantly so that the error between the simulation response signal and the experimental response signal is minimized. When the first target error between the simulation signal and the test signal reaches a preset convergence standard, the iteration process is ended, and the final external excitation obtained is the inversely solved wheel center external excitation, that is, the final initial external excitation.

[0054] In some application scenarios, the step S42 can be loading the initial time-domain displacement load into the dynamic virtual iterative model to obtain the time-domain displacement load of the vehicle body and the chassis attachment point through target iteration. Specifically, an advanced external excitation is first inversely solved according to preset parameters. The advanced external excitation can be a preset time-domain displacement load of the vehicle body and the chassis attachment point, which is input into the target iteration module of the preset iterative model. Then, the advanced external excitation is simulated and compared with the experimental measurement, the inverse-solved advanced external excitation is input into the target iteration module of the preset iterative model, and a simulation response signal is calculated. The simulation response signal can be a simulation initial time-domain displacement load. The simulation response signal is compared with the response signal measured by the experiment, an error is calculated and used as a second target error. The response signal measured by the experiment is the initial time-domain displacement load. Then, the advanced external excitation is iteratively adjusted according to the second target error to obtain a final advanced external excitation, and the final advanced external excitation is used as the time-domain displacement load of the vehicle body and the chassis attachment point obtained through target iteration. Specifically, the final advanced external excitation is obtained by iteratively adjusting the advanced external excitation according to the second target error, including: adjusting the parameters according to the second target error to minimize the error between the simulation response signal and the experimental response signal. When the second target error between the simulation signal and the experimental signal reaches a preset convergence standard, the iteration process ends, and the final external excitation obtained is the inversely-solved time-domain displacement load of the vehicle body and the chassis attachment point, that is, the final advanced external excitation.

[0055] It can be considered that the target time-domain displacement load obtained through multiple iterations has high accuracy. In addition, multiple iterations can inversely solve the external excitation with high precision, and can also reduce the dependence on complex tests to a certain extent and reduce the test cost.

[0056] In some application scenarios, the step S32 can be obtaining a plurality of preset relative displacement values. The preset relative displacement value matched with the target time-domain displacement load is determined from the plurality of preset relative displacement values as the target relative displacement value of each contact pair.

[0057] It can be considered that by inputting the acceleration load data and the spring displacement into the preset iterative model, the behavior of the vehicle under various dynamic conditions can be more accurately predicted, the accuracy of determining the target relative displacement value of each contact pair based on the target time-domain displacement load is high, and the accuracy of the simulation result obtained based on the target time-domain displacement load can be improved.

[0058] Please refer to Figure 5 , Figure 5 is a flowchart of an embodiment of the vehicle back door abnormal noise simulation method of the present application Figure 5 .

[0059] In some embodiments, the step S32 can include the following steps: step S51: constructing a whole vehicle finite element model; and step S52: inputting the target time-domain displacement load into the whole vehicle finite element model to obtain the target relative displacement values of each contact pair output by the whole vehicle finite element model.

[0060] The whole vehicle finite element model can be a TrimBody body finite element analysis model of the inner and outer trim panels of the back door. Each contact pair is included in the whole vehicle finite element model. In some application scenarios, the step S51 can be to construct a whole vehicle finite element model that does not include a chassis suspension, and the whole vehicle finite element model includes at least one of a body-in-white, a battery pack, four doors and two covers, a steering system, a seat skeleton, electronic and electrical information, and interior and exterior trim weight information, and vehicle body accessories. In the whole vehicle finite element model, a node pairing unit group is established at the gap between the back door and the vehicle body, the node pairing unit group is composed of RBE3, CBUSH spring element and local coordinate system, and the CBUSH spring element is given a 0 stiffness value. The Z-axis direction in the local coordinate system is the direction at the gap between the back door and the vehicle body. The CBUSH spring element is directly associated with the above local coordinate system. For each node pairing unit group of the contact pair, the target time-domain displacement load of the contact pair is taken as an input condition in the whole vehicle finite element model, the relative displacement of the two end points of the CBUSH spring element in the local coordinate system is calculated, and the relative displacement in the local coordinate system is taken as the target relative displacement value of the contact pair. For any node pairing unit group, the two end points of the CBUSH spring element are respectively arranged corresponding to the center points of RBE3 on the vehicle body and RBE3 on the back door.

[0061] It can be considered that the target relative displacement values of each contact pair output by the whole vehicle finite element model have high accuracy. In addition, the simulation analysis model only needs the TrimBody finite element body model, and does not need the chassis suspension part in the whole vehicle model, which reduces the modeling steps of the chassis suspension and the influence caused by the modeling accuracy, and further improves the simulation model accuracy.

[0062] Step S22: analyzing the target relative displacement values to obtain a simulation result.

[0063] The simulation result includes simulation sub-results of each contact pair, and each simulation sub-result of each contact pair indicates whether the position of the contact pair is an abnormal noise risk position or a normal position.

[0064] The analysis on the target relative displacement values can be determining, for each contact pair, a simulation sub-result of the contact pair based on a difference between the target relative displacement and a preset relative displacement value. In response to the difference being greater than a preset difference, the simulation sub-result of the contact pair is determined as the position of the contact pair being a risk position of abnormal sound. In response to the difference being less than or equal to the preset difference, the simulation sub-result of the contact pair is determined as the position of the contact pair being a normal position. In some application scenarios, the preset relative displacement value is a preset value.

[0065] It can be considered that, in combination with the acceleration load data and the spring displacement, the dynamic behavior of the tailgate in actual use can be simulated more accurately, which helps to improve the accuracy and reliability of the simulation result, thereby reducing the demand and cost of physical testing. In addition, by analyzing the target relative displacement values, the polishing state and abnormal sound of the tailgate can be comprehensively evaluated. In addition, the present application can be adjusted according to different vehicle models and design requirements, and can be applied to various complex simulation scenarios.

[0066] In some embodiments, the above step S22 can include the following steps, including: for each target relative displacement value, in response to the target relative displacement value being greater than a preset relative displacement value, determining the position of the contact pair corresponding to the target relative displacement value as a risk position of abnormal sound. For each target relative displacement value, in response to the target relative displacement value being less than or equal to the preset relative displacement value, determining the position of the contact pair corresponding to the target relative displacement value as a normal position.

[0067] In some application scenarios, the preset relative displacement value is the actual gap of the position of the contact pair in the static state of the vehicle measured in advance without wear. The preset relative displacement values compared by the target relative displacements of different contact pairs can be different. The preset relative displacement values of different contact pairs can be different.

[0068] The above step S22 can perform the following steps on each contact pair: in the case that the target relative displacement value of the contact pair is greater than the preset relative displacement value of the contact pair, determining the position of the contact pair corresponding to the target relative displacement value as a risk position of abnormal sound. In the case that the target relative displacement value of the contact pair is less than or equal to the preset relative displacement value of the contact pair, determining the position of the contact pair corresponding to the target relative displacement value as a normal position.

[0069] It can be considered that, by comparing the target relative displacement value with the threshold value, the high-risk positions that can cause abnormal sound can be quickly identified, the accuracy of the simulation is improved, and the cost and time of subsequent physical testing are significantly reduced. At the same time, the normal position and the risk position of abnormal sound are clearly distinguished, which helps designers to more intuitively understand the simulation result and improve the product development efficiency.

[0070] In some embodiments, the vehicle back door abnormal noise simulation method further comprises: for each contact pair, in response to the position of the contact pair being an abnormal noise risk position, taking the target relative displacement value of the contact pair as the to-be-processed data. The modal contribution analysis is performed on each to-be-processed data to obtain a contribution analysis result, and the contribution analysis result includes a contribution ranking of a plurality of preset modes. The preset mode in the contribution ranking is a preset ranking is taken as the to-be-adjusted mode.

[0071] The to-be-processed data represents the target relative displacement value of the contact pair in any one simulation result of the abnormal noise risk position. In other application scenarios, the back door outer panel and the vehicle body sheet metal part have a plurality of gaps, each gap establishes a plurality of contact pairs, and each contact pair generates a target relative displacement value at any time under the time domain load displacement. Therefore, statistical processing needs to be performed on the analysis result. Here, the relative displacement is sorted in descending order of amplitude (ignoring time sequence), and the average value of the preset proportion of the positive result is taken as the target relative displacement value output of one contact pair and as the to-be-processed data. The preset proportion is 20%.

[0072] The modal contribution analysis is used to calculate the proportion of a preset mode corresponding to a certain order mode in the total response of the system (such as all preset modes). The contribution analysis result includes a contribution ranking of a plurality of preset modes. Each preset mode represents the shape of the vibration of any order mode of the automobile. The modal contribution analysis can be a plurality of order modal contribution analyses. The plurality of orders can mean at least one order. Specifically, the process of the modal contribution analysis can refer to formula (1):

[0073]

[0074] Wherein, U(t) represents the system response in the physical coordinates, and the system response is the target relative displacement value. represents the modal shape of the i-th order mode. Qi(t) is the modal coordinate response of the i-th order mode, and the response is the target relative displacement value. n is the total number of modal shapes. For example, the modal shape is the above-mentioned preset mode.

[0075] In response to the number of contact pairs in the abnormal noise risk position in the simulation result being at least one, the step of performing modal contribution analysis on each to-be-processed data to obtain a contribution analysis result is performed on at least one to-be-processed data.

[0076] The preset ranking can be a preset number of top rankings. For example, the preset number can be 3. The to-be-adjusted mode is the top three order modal shapes with the largest contribution in the contribution analysis result.

[0077] It can be considered that by taking the target relative displacement value of the contact pair as the to-be-processed data and performing modal contribution analysis, the key mode which has a significant influence on the vibration noise can be accurately identified.

[0078] In some embodiments, after the preset mode shape in the preset ranking in the contribution amount ranking is taken as the to-be-adjusted mode shape, the vehicle back door abnormal sound simulation method further comprises: obtaining a preset adjustment strategy corresponding to each of the preset mode shapes. The preset adjustment strategies corresponding to different preset mode shapes are different. The preset adjustment strategy in the preset adjustment strategies that matches the to-be-adjusted mode shape is taken as a target adjustment strategy so as to output the target adjustment strategy to adjust the to-be-adjusted mode shape.

[0079] Please refer to Figure 6 , Figure 6 is a rear view of a vehicle in an embodiment of the vehicle back door abnormal sound simulation method of the present application.

[0080] As Figure 6 shown in the rear view of the vehicle, a represents a vehicle body adjacent to a back door of the vehicle. b represents the back door of the vehicle. c represents a tire of the vehicle. Among them, the back door can be one door or multiple doors. According to different vehicle models, the specific structure and opening mode of the back door are not the same, which is not limited here. Any one contact pair is a node pairing unit between the second virtual node in the vehicle body a and the first virtual node in the back door b.

[0081] The present application takes into account the engineering practice that the visible paint grinding phenomenon occurs at the gap between the back door and the vehicle body sheet metal before the mass production of new vehicles in the road test stage. The engineer makes a single solution to rectify the problem by experience, and then drives the vehicle for 5000-8000 kilometers on high ring combined road or structural endurance road to determine whether the back door has the paint grinding problem. It is time-consuming and laborious. The present application obtains the simulation result of the back door of the vehicle by simulating the acceleration load data and the spring displacement. The simulation result includes whether the position of each contact pair is an abnormal sound risk position or a normal position, which can improve the accuracy of the abnormal sound risk position, quantify the paint grinding problem, and improve the simulation efficiency.

[0082] Exemplarily, the durability road load is collected, and the measured spring displacement and wheel core acceleration load data are obtained by collecting the test field intensive bad road load of the front and rear four wheels. And the acceleration load data and the spring displacement are taken as the virtual iteration reference data in the preset iteration model.

[0083] In some application scenarios, the preset iteration model is a dynamics virtual iteration model, and before step S31, the vehicle back door abnormal sound simulation method further comprises constructing the preset iteration model. Wherein, the way of constructing the preset iteration model includes: establishing a whole vehicle dynamics virtual iteration model, the suspension, the steering and the vehicle body are all rigid bodies, the stabilizer bar body is a linear beam flexible body, and the six-component force and motion are driven. The mass of the whole vehicle dynamics virtual iteration model is about 15N different from the test load, and the simulation model has accurate mass.

[0084] Considering that the displacement load signal of the wheel center of the vehicle cannot be directly collected, the acceleration signal needs to be iteratively back calculated to obtain the initial time-domain displacement load of the wheel center of the vehicle. After the preset iteration model is constructed, the measured spring displacement and the vertical acceleration of the wheel center are taken as the target signals to iteratively back calculate the vertical driving time-domain displacement of the wheel center, and the measured vertical force of the wheel center is taken as the monitoring signal to ensure the iteration accuracy to obtain the final initial external excitation and serve as the initial time-domain displacement load of the wheel center of the vehicle. After the initial time-domain displacement loads of the wheel centers of the four wheels are back calculated, the hard point position displacement loads (i.e., the target time-domain displacement loads) of all the chassis suspensions and the vehicle body are calculated by reloading the initial time-domain displacement loads of the wheel centers into the dynamic virtual iteration model.

[0085] After the target time-domain displacement loads are obtained, in some application scenarios, the above step S51 can be to build a whole vehicle finite element model not containing the chassis suspension, and the whole vehicle finite element model includes at least one of the following: the body-in-white, the battery pack, the four doors and two hoods, the steering system, the seat skeleton, the electronic and electrical information and the interior and exterior trim weight information, and the vehicle body accessories. A node pairing unit group is established at the gap between the back door and the vehicle body in the whole vehicle finite element model, the node pairing unit group is composed of RBE3, CBUSH spring unit and local coordinate system, and the CBUSH spring unit is given a 0 stiffness value. The Z-axis direction in the local coordinate system is the direction at the gap between the back door and the vehicle body. The CBUSH spring unit is directly associated with the above local coordinate system. For each contact pair node pairing unit group, the target time-domain displacement load of the contact pair is taken as the input condition in the whole vehicle finite element model, the relative displacement of the two endpoints of the CBUSH spring unit in the local coordinate system is calculated, and the relative displacement in the local coordinate system is taken as the target relative displacement value of the contact pair. For any node pairing unit group, the two endpoints of the CBUSH spring unit are respectively set corresponding to the center points of RBE3 on the vehicle body and RBE3 on the back door.

[0086] In some application scenarios, after the target relative displacement values of the contact pairs are obtained, step S22 is performed to perform the paint grinding risk assessment on the back door of the vehicle to obtain the simulation result. The actual gap at the paint grinding position in the static state of the vehicle without wear is measured, and the actual gap is taken as the preset relative displacement value. For each contact pair, it is judged whether the target relative displacement value of the contact pair is greater than the actual measured gap value (i.e., the preset relative displacement value). If the relative displacement is greater than the actual measured gap value, it is judged that the position of the contact pair is the paint grinding risk position, i.e., the abnormal sound risk position.

[0087] In some application scenarios, after obtaining the simulation sub-results of the contact pairs, the positions of the contact pairs at which the contact pairs are located are selected as the to-be-processed data from the simulation sub-results of the contact pairs at which the contact pairs are located. The modal contribution analysis is performed on the at least one to-be-processed data to obtain a contribution analysis result. For example, the modal contribution analysis can be the modal contribution analysis on the contact pairs corresponding to the maximum relative displacement at the scuffing risk position, and the first three orders of modes corresponding to the maximum contribution and the mode shape animation can help engineers to judge the structural problems and provide clues for further optimization. Exemplarily, if the first three orders of modes corresponding to the maximum contribution are found to be the vibration mode corresponding to 27 Hz, the vibration mode is taken as the to-be-adjusted vibration mode. A preset adjustment strategy corresponding to the to-be-adjusted vibration mode is taken as the target adjustment strategy. For example, after it is determined that the to-be-adjusted vibration mode is the back door torsion mode 27 Hz which is the root cause of the scuffing problem, the target adjustment strategy can include: increasing the buffer block or the limiting block on both sides of the back door through the CAE simulation, and continuously adjusting and optimizing the stiffness parameter of the buffer block so as to reduce the high risk of the back door scuffing to a low risk.

[0088] Compared with the method of predicting the scuffing problem of the back door by arranging sensors to collect dynamic loads at multiple position points of the vehicle body, the method has low accuracy in predicting the scuffing risk. In the method, the acceleration load data corresponding to the wheel center of the vehicle and the spring displacement are obtained, the acceleration load data and the spring displacement are simulated, the simulation result of the back door of the vehicle is obtained, and the simulation result includes the positions of the contact pairs at which the contact pairs are located are the scuffing risk positions or the normal positions. Therefore, the accuracy of the scuffing risk positions can be improved, and the simulation efficiency can be improved.

[0089] Referring to Figure 7 , Figure 7 is a structural schematic diagram of an embodiment of a vehicle back door scuffing simulation device. The vehicle back door scuffing simulation device 70 includes an obtaining module 71 and a simulation module 72. The obtaining module 71 is configured to obtain acceleration load data corresponding to the wheel center of the vehicle and spring displacement. The simulation module 72 is configured to simulate the acceleration load data and the spring displacement, and obtain a simulation result of the back door of the vehicle. The simulation result includes positions of at least one contact pair at which the contact pair is located are the scuffing risk positions or the normal positions. The contact pair represents a node pairing unit group established at a gap between the back door of the vehicle and the vehicle body.

[0090] Compared with the method of predicting the abnormal sound problem of the back door by arranging sensors to collect dynamic loads of multiple position points of the vehicle body, the method has low accuracy in predicting the abnormal sound risk. The acceleration load data corresponding to the wheel center of the vehicle and the spring displacement are obtained, the acceleration load data and the spring displacement are simulated, the simulation result of the back door of the vehicle is obtained, and the simulation result includes the positions of each contact pair as the abnormal sound risk position or the normal position. The accuracy of the abnormal sound risk position is improved, and the simulation efficiency is improved.

[0091] The functions of the modules are described in the vehicle back door abnormal sound simulation method, which will not be repeated here.

[0092] Please refer to Figure 8 , Figure 8 is a structural schematic diagram of an embodiment of the electronic device. The electronic device 80 includes a memory 81 and a processor 82. The processor 82 is configured to execute program instructions stored in the memory 81 to implement the steps in the above-mentioned vehicle back door abnormal sound simulation method embodiment. In a specific implementation scenario, the electronic device 80 can include but is not limited to a microcomputer, a server, and in addition, the electronic device 80 can also include a notebook computer, a tablet computer, and other mobile devices, which are not limited here.

[0093] Specifically, the processor 82 is configured to control itself and the memory 81 to implement the steps in the above-mentioned vehicle back door abnormal sound simulation method embodiment. The processor 82 can also be referred to as a CPU (Central Processing Unit). The processor 82 can be an integrated circuit chip with signal processing capability. The processor 82 can also be a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. In addition, the processor 82 can be implemented by an integrated circuit chip together.

[0094] Compared with the method of predicting the abnormal sound problem of the back door by arranging sensors to collect dynamic loads of multiple position points of the vehicle body, the method provided in the application can improve the accuracy of the abnormal sound risk position and improve the simulation efficiency.

[0095] Please refer to Figure 9 , Figure 9 is a structural schematic diagram of an embodiment of the computer readable storage medium of the application. The computer readable storage medium 90 stores program instructions 901 thereon, and the program instructions 901 are executed by a processor to implement the steps in any of the vehicle back door abnormal sound simulation method embodiments described above.

[0096] Compared with the method of predicting the abnormal sound problem of the back door by arranging sensors to collect dynamic loads of multiple position points of the vehicle body, the method provided in the application can improve the accuracy of the abnormal sound risk position and improve the simulation efficiency.

[0097] In some embodiments, the system provided by the embodiments of the present disclosure has functions or includes modules that can be used to perform the methods described in the above method embodiments, and the specific implementation can refer to the description of the above method embodiments. For the sake of brevity, it will not be repeated here.

[0098] The above description of each embodiment tends to emphasize the differences between each embodiment, and the same or similar parts can be mutually referred to. For the sake of brevity, it will not be repeated here.

[0099] In several embodiments provided in the present application, it should be understood that the disclosed method and device can be implemented in other ways. For example, the above-described device implementation is only schematic, for example, the division of modules or units is only a logical function division, and actual implementation can have another division manner, for example, a unit or component can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed mutual ones can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0100] In addition, each of the functional units in the various embodiments of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0101] If the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such an understanding, the technical solutions of the present application, essentially or in other words, the part of the prior art that contributes to the present application, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the methods in the various embodiments of the present application. The aforementioned storage medium includes various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk.

Claims

1. A method for simulating abnormal noise of a vehicle back door, characterized in that: The method comprises: Obtain the acceleration load data and spring displacement corresponding to the vehicle's wheel center; The acceleration load data and the spring displacement are simulated to obtain a simulation result of the tailgate of the vehicle, wherein the simulation result includes at least one contact pair being located at a noise risk position or a normal position, and the contact pair represents a node pairing unit group established at a gap between the tailgate of the vehicle and the body of the vehicle.

2. The method according to claim 1, characterized in that The simulating the acceleration load data and the spring displacement to obtain a simulation result of the tailgate of the vehicle includes: determining a target relative displacement value of each of the contact pairs based on the acceleration load data and the spring displacement; The target relative displacement values ​​are analyzed to obtain the simulation results.

3. The method according to claim 2, characterized in that Determining the target relative displacement value of each contact pair based on the acceleration load data and the spring displacement includes: Inputting the acceleration load data and the spring displacement into a preset iterative model to obtain a target time-domain displacement load of a preset attachment point of the vehicle output by the preset iterative model; Based on the target time-domain displacement load, a target relative displacement value of each of the contact pairs is determined.

4. The method according to claim 3, characterized in that Inputting the acceleration load data and the spring displacement into a preset iterative model to obtain a target time-domain displacement load of a preset attachment point of the vehicle output by the preset iterative model includes: Performing initial iteration on the acceleration load data and the spring displacement to obtain an initial time-domain displacement load of the wheel center of the vehicle; Perform target iteration on the initial time-domain displacement load to obtain the target time-domain displacement load.

5. The method according to claim 3, characterized in that Determining the target relative displacement value of each contact pair based on the target time-domain displacement load includes: Constructing a finite element model of the entire vehicle, wherein the finite element model of the entire vehicle includes each of the contact pairs; The target time-domain displacement load is input into the whole vehicle finite element model to obtain the target relative displacement value of each contact pair output by the whole vehicle finite element model.

6. The method according to claim 2, characterized in that The analyzing the relative displacement values ​​of the targets to obtain the simulation results includes: For each of the target relative displacement values, in response to the target relative displacement value being greater than a preset relative displacement value, determining the position of the contact pair corresponding to the target relative displacement value as an abnormal sound risk position; For each of the target relative displacement values, in response to the target relative displacement value being less than or equal to a preset relative displacement value, the position of the contact pair corresponding to the target relative displacement value is determined as a normal position.

7. The method according to claim 1, characterized in that The method further comprises: For each of the contact pairs, in response to the position of the contact pair being a position at risk of abnormal sound, taking the target relative displacement value of the contact pair as data to be processed; Performing modal contribution analysis on each of the to-be-processed data to obtain contribution analysis results, wherein the contribution analysis results include contribution rankings of a plurality of preset vibration modes; The preset vibration mode in the preset ranking in the contribution amount ranking is used as the vibration mode to be adjusted.

8. A vehicle back door abnormal noise simulation device, characterized in that: include: An acquisition module is used to obtain acceleration load data and spring displacement corresponding to the wheel center of the vehicle; A simulation module is used to simulate the acceleration load data and the spring displacement to obtain a simulation result of the tailgate of the vehicle, wherein the simulation result includes at least one contact pair being located at a noise risk position or a normal position, and the contact pair represents a node pairing unit group established at the gap between the tailgate of the vehicle and the body of the vehicle.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores program instructions, and the processor calls the program instructions from the memory to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 7.

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