Automobile body strength performance evaluation method based on collision test

Abstract

The invention discloses an automobile body strength performance evaluation method based on a collision test, and relates to the field of automobile safety, and the method comprises the following steps: collecting automobile body structure data of a target automobile, and constructing an automobile body model according to the collected automobile body structure data; the method comprises the following steps: selecting a collision scene, carrying out grid division on a vehicle body collision area of a target vehicle according to the collision scene to obtain corresponding grid areas, carrying out collision test on the target vehicle, and carrying out data acquisition on data change conditions of the corresponding grid areas to obtain corresponding real vehicle collision data and simulated collision data; performing data analysis on the collected simulated collision data, and performing performance evaluation on the vehicle body strength of the target vehicle according to an analysis result; constructing a corresponding automobile evaluation model according to the performance evaluation result, and obtaining an actual automobile body strength evaluation result of the target automobile according to the obtained automobile evaluation model and the actual collision data; according to the invention, the accuracy and efficiency of vehicle body strength performance evaluation are improved.

Description

Technical Field

[0001] The present invention relates to the field of automotive safety, and particularly to a method for evaluating the strength performance of an automotive body based on a collision test. Background Art

[0002] With the development of the automotive industry and the improvement of traffic safety awareness, the safety performance of automobiles has become the focus of attention of consumers, manufacturers, and regulatory agencies. Moreover, the body of an automobile includes a side door system, a rear door system, and a body-in-white system, and there are various strength performance requirements for the body system. For example, the strength performance requirements of the automotive side door system include performance such as sagging, over-opening, and slamming.

[0003] Compared with the prior art, traditional methods for evaluating the strength performance of automobiles usually rely on actual collision tests or simplified calculation models. However, these methods are costly and cannot reflect the body strength performance of a vehicle in different collision scenarios in real time, or mostly rely on empirical judgment and simple material mechanics analysis, making it difficult to accurately predict the performance of a vehicle in an actual collision, and the corresponding evaluation period is long. These are the problems we need to solve. Therefore, we provide a method for evaluating the strength performance of an automotive body based on a collision test. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for evaluating the strength performance of an automotive body based on a collision test.

[0005] The purpose of the present invention can be achieved by the following technical solutions: A method for evaluating the strength performance of an automotive body based on a collision test, comprising the following steps: Step 1: Collect the body structure data of the target automobile, and construct an automotive body model based on the collected body structure data; Step 2: Select a collision scenario, divide the grid of the body collision area of the target automobile according to the collision scenario to obtain the corresponding grid area, conduct a collision test on the target automobile, and collect the data change situation of the corresponding grid area to obtain the corresponding real vehicle collision data and simulated collision data; Step 3: Analyze the collected simulated collision data, and evaluate the strength performance of the body of the target automobile according to the analysis results; Step 4: Construct a corresponding automobile evaluation model according to the performance evaluation results, and obtain the actual body strength evaluation result of the target automobile based on the obtained automobile evaluation model and actual collision data.

[0006] Further, the process of collecting the body structure data of the target automobile and constructing an automotive body model based on the collected body structure data includes: Collect data on the body structure of the target vehicle to obtain corresponding body structure data. After the collection of the body structure data is completed, classify the collected body structure data according to the body structure of the target vehicle to obtain corresponding body component data, and construct a corresponding body component model based on the obtained body component data; Obtain the design structure of the target vehicle, and splice the obtained body component models according to the obtained design structure to obtain a corresponding vehicle body model.

[0007] Further, the process of selecting a collision scenario and conducting a vehicle collision test in combination with the obtained vehicle body model includes: Select a collision scenario, which includes but is not limited to frontal collision, side collision, vehicle rollover, and other collision methods; Determine the corresponding vehicle collision area according to the selected collision scenario, divide the obtained vehicle collision area by equal division to obtain several collision sub-areas. After the division is completed, conduct a standard judgment on the corresponding collision sub-areas according to the division standard. If the corresponding collision sub-areas meet the division standard, mark the collision sub-areas after the last division as the first grid area; if the corresponding collision sub-areas do not meet the division standard, continue to divide the corresponding vehicle collision area until it meets the division standard.

[0008] Further, the process of conducting a collision test on the target vehicle and collecting data on the data change situation of the corresponding grid area includes: Set up acquisition nodes and deploy the acquisition nodes into the corresponding grid areas; Build an actual collision environment according to the selected collision scenario. After the construction is completed, conduct a real vehicle collision test, and collect data on the data change situation in the corresponding grid area through the acquisition nodes to obtain corresponding real vehicle collision data and store it; After the real vehicle collision test is completed, determine the corresponding collision key parameters according to the collected real vehicle collision data. The collision key parameters include but are not limited to collision speed, collision angle, and collision force; Use the same method to divide the body area at the same position as the vehicle collision area in the corresponding vehicle body model to obtain a corresponding second grid area; Conduct a simulated collision test based on the corresponding collision key parameters and the vehicle body model, and record the data change situation in the corresponding second grid area to obtain corresponding stress data, deformation data, and corresponding simulated collision data.

[0009] Further, the process of analyzing the collected simulated collision data and evaluating the body strength performance of the target vehicle according to the analysis results includes: Read the stress data collected within the corresponding second grid area, obtain the maximum value of the stress data within the corresponding second grid area during the corresponding simulated collision test, and record it as the maximum stress; Obtain the stress standard and deformation standard of the corresponding vehicle body according to industry specifications, regulations, and design guidelines; Compare the maximum stress with the corresponding stress standard, and obtain the stress score corresponding to the second grid area according to the stress range where the maximum stress is located; Furthermore, determine the first weight coefficient corresponding to the second grid area according to the type of vehicle body component to which the second grid area belongs; Read the deformation data within the corresponding second grid area i, compare the obtained deformation data with the corresponding deformation standard, and determine the second weight coefficient of the second grid area i according to the comparison result, Obtain the body strength score of the target vehicle according to the obtained first weight coefficient, second weight coefficient, and stress score; Set a strength threshold, compare the obtained body strength score with the strength threshold, and obtain the corresponding strength performance level according to the comparison result.

[0010] Furthermore, the process of constructing the corresponding vehicle evaluation model according to the performance evaluation result includes: Statistically analyze the simulated collision data, stress data, deformation data, body strength score, and strength performance level related to the corresponding simulated collision test to obtain the corresponding first data set; Using the same method, perform data analysis on the simulated collision tests under several different collision conditions to obtain the corresponding Nth data set; N is a natural number greater than 1; Build the corresponding initial vehicle evaluation model based on neural network technology, perform iterative training on the corresponding initial vehicle evaluation model based on the obtained N + 1 data sets, wait for the loss function score, and retain the corresponding model parameters; Obtain the historical actual vehicle collision data and the corresponding vehicle body strength evaluation data corresponding to the same type of vehicle as the target vehicle based on big data technology, and adjust the parameters of the initial vehicle evaluation model that has completed iterative training according to them. After the adjustment is completed, verify the accuracy of the corresponding initial vehicle evaluation model. If the verification passes, output it to obtain the corresponding vehicle evaluation model.

[0011] Furthermore, the process of obtaining the actual body strength evaluation result of the target vehicle according to the obtained vehicle evaluation model and actual collision data includes: Input the collected real vehicle collision data into the vehicle evaluation model to obtain corresponding output results. The output results include the actual body strength score of the target vehicle, the strength performance level, and the stress score corresponding to the corresponding first grid area. And feedback different safety warnings to the corresponding staff according to the corresponding strength performance level; Meanwhile, set different numerical intervals for the obtained stress scores. The numerical gaps between each numerical interval are the same. Set different color temperatures of colors for different numerical intervals. Each numerical interval is represented by a dedicated color. The higher the stress score, the higher the color temperature of the color. Then generate the corresponding body stress color temperature map and feedback it to the staff.

[0012] Compared with the prior art, the beneficial effects of the present invention are: 1. By combining finite element analysis and real vehicle collision tests, it is possible to more comprehensively evaluate the strength performance of the vehicle body under different collision scenarios, reduce the number of real vehicle collision tests, and avoid the problems of high cost and long cycle of traditional real vehicle collision tests.

[0013] 2. Assign color temperatures to the corresponding first grid areas according to the stress scores to obtain the corresponding body color temperature map, effectively identify the weak links of the body structure, provide targeted improvement suggestions for vehicle design, and through continuous improvement, help improve the overall safety performance of the vehicle and reduce the injuries of occupants in collision accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is the schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] As Figure 1 shown, a method for evaluating the strength performance of a vehicle body based on collision tests includes the following steps: Step 1: Collect the body structure data of the target vehicle and construct a vehicle body model based on the collected body structure data; Step 2: Select a collision scenario, divide the grid of the body collision area of the target vehicle according to the collision scenario to obtain the corresponding grid area, conduct a collision test on the target vehicle, and collect the data change situation of the corresponding grid area to obtain the corresponding real vehicle collision data and simulated collision data; Step 3: Analyze the collected simulated collision data and evaluate the strength performance of the body of the target vehicle according to the analysis results; Step 4: Construct a corresponding vehicle evaluation model according to the performance evaluation results, and obtain the actual body strength evaluation result of the target vehicle according to the obtained vehicle evaluation model and actual collision data; It should be further noted that in the specific implementation process, the process of collecting the body structure data of the target vehicle and constructing a vehicle body model based on the collected body structure data includes: Collect data on the body structure of the target vehicle to obtain corresponding body structure data. Among them, the body structure includes, but is not limited to, the body frame, front and rear suspensions, wheel brackets, engine compartment, and passenger compartment. The body structure data includes, but is not limited to, body materials, material categories, body weight, body dimensions, and body shape; After the collection of the body structure data is completed, classify the collected body structure data according to the body structure of the target vehicle to obtain corresponding body component data; Construct corresponding body component models based on the obtained body component data. The body component models need to comply with body structure data such as body weight, body dimensions, and body shape, and at the same time, also need to combine data such as corresponding body materials and material categories to create the body component models of the target vehicle. Among them, the body component models need to accurately reflect the shape, structure, and performance of the vehicle body components; Obtain the design structure of the target vehicle, and splice the obtained body component models according to the obtained design structure to obtain the corresponding vehicle body model; among them, the design structure includes, but is not limited to, the shape of the structure, the positions of beams and supports, welding methods, and the number of welding points.

[0016] It should be further noted that in the specific implementation process, the process of selecting a collision scenario and dividing the body collision area of the target vehicle into grid areas according to the collision scenario to obtain corresponding grid areas includes: Select a collision scenario, which includes, but is not limited to, frontal collision, side collision, vehicle rollover, and other collision methods; Determine the corresponding vehicle collision area according to the selected collision scenario, divide the obtained vehicle collision area by equal division to obtain several collision sub-areas. After the division is completed, judge the corresponding collision sub-areas according to the division standard. If the corresponding collision sub-areas meet the division standard, mark the collision sub-areas after the last division as the first grid area; if the corresponding collision sub-areas do not meet the division standard, continue to divide the corresponding vehicle collision area until it meets the division standard; It should be further noted that in the specific implementation process, the division standard refers to whether the obtained first grid area can cover the corresponding vehicle collision area and only one acquisition node can be set in each first grid area; It should be further noted that in the specific implementation process, the process of conducting a collision test on the target vehicle and collecting data on the data change situation of the corresponding grid area includes: Set up acquisition nodes, which are used to collect data changes during the car collision process to obtain corresponding collision data, and deploy the acquisition nodes into corresponding grid areas; Build an actual collision environment according to the selected collision scenario. After the construction is completed, conduct a real vehicle collision test, and collect data changes in the corresponding grid area through the acquisition nodes to obtain corresponding real vehicle collision data and store it; After the real vehicle collision test is completed, determine corresponding collision key parameters based on the collected real vehicle collision data. The collision key parameters include but are not limited to collision speed, collision angle, and collision force; Use the same method to divide the grid of the body area at the same position as the car collision area in the corresponding car body model to obtain a corresponding second grid area; Input the corresponding collision key parameters and the car body model into finite element analysis software for simulated collision testing, and record the data changes in the corresponding second grid area to obtain corresponding stress data, deformation data, and corresponding simulated collision data. Among them, the deformation data refers to the deformation distance of the corresponding second grid area before and after the corresponding model collision test; It should be further noted that in the specific implementation process, when conducting simulated collision testing, various load conditions that the body of the target car is subjected to during actual use are also required to ensure the accuracy of the corresponding simulated collision. The load conditions include static loads (such as vehicle self-weight, passengers, goods, etc.), dynamic loads (such as bumps, steering, acceleration, braking, etc. during driving), and external environmental factors (such as temperature, humidity, etc.); It should be further noted that in the specific implementation process, the simulated collision testing is not limited to collision scenarios, collision speeds, collision angles, and other collision conditions.

[0017] It should be further noted that in the specific implementation process, the process of analyzing the collected simulated collision data and evaluating the performance of the body strength of the target car based on the analysis results includes: Due to different collision conditions, there are different differences in the corresponding collision results. Therefore, the present invention takes any one simulated collision test as an example; Number the corresponding second grid area, denoted as i, where i = 1, 2,..., n, n > 0 and n is an integer; Read the stress data collected in the corresponding second grid area i, obtain the maximum value of the stress data in the corresponding second grid area i during the corresponding simulated collision test, and record it as the maximum stress; Obtain the stress standard and deformation standard of the corresponding automobile body according to industry specifications, regulations, and design guidelines; the deformation standard refers to the maximum deformation distance allowed for the corresponding automobile body during the collision test, and the stress standard refers to the safe stress range, dangerous stress range, and corresponding danger scores of the corresponding automobile body during the collision test; Compare the maximum stress with the corresponding stress standard, and obtain the stress score corresponding to the second grid area i according to the stress range where the maximum stress is located; for example, when the maximum stress is within the safe stress range, the stress score in the second grid area i is zero, and if the maximum stress score is within the dangerous stress score range, the stress score in the second grid area i is Mi, where M = 1, 2,..., 10, where 1 is the lowest risk and 10 is the highest risk; Furthermore, determine the first weight coefficient corresponding to the second grid area i according to the type of body component to which the second grid area belongs, and mark it as Yi; for example: the body steel frame is the main support part of the body structure, bearing important strength and rigidity functions, so the weight of the body steel frame is relatively higher than that of other body components; Read the deformation data in the second grid area i, compare the obtained deformation data with the corresponding deformation standard, and determine the second weight coefficient of the second grid area i according to the comparison result, and record it as Ei. For example, the lower the deformation data of the second area i, the lower its corresponding weight; Obtain the body strength score of the target vehicle according to the obtained first weight coefficient, second weight coefficient, and stress score, and record it as CS, where,

[0018] Set a strength threshold, compare the obtained body strength score with the strength threshold, and obtain the corresponding strength performance level according to the comparison result. The strength performance level includes first-level strength, second-level strength, and third-level strength. Among them, the safety ranking of the corresponding strength performance levels is: first-level strength > second-level strength > third-level strength.

[0019] It should be further noted that in the specific implementation process, the process of constructing the corresponding vehicle evaluation model according to the performance evaluation results and obtaining the actual body strength evaluation result of the target vehicle according to the obtained vehicle evaluation model and actual collision data includes: Statistical simulation collision data, stress data, deformation data, body strength scores, and strength performance levels related to the corresponding simulation collision test to obtain the corresponding first data set; Using the same method, perform data analysis on the simulation collision tests under several different collision conditions to obtain the corresponding Nth data set; N is a natural number greater than 1; Build a corresponding initial vehicle evaluation model based on neural network technology, and perform iterative training on the corresponding initial vehicle evaluation model based on the obtained N+1 data sets. Wait for the loss function score and retain the corresponding model parameters; Obtain the historical actual vehicle collision data and the corresponding vehicle body strength evaluation data of the same type of vehicle as the target vehicle based on big data technology, and adjust the parameters of the initial vehicle evaluation model completed by iterative training according to them to make it more suitable for the actual scenario. After the adjustment is completed, verify the accuracy of the corresponding initial vehicle evaluation model. If the verification fails, continue to perform iterative training and parameter adjustment on the corresponding initial evaluation model; if the verification passes, output it to obtain the corresponding vehicle evaluation model; Input the collected actual vehicle collision data into the vehicle evaluation model to obtain the corresponding output results, where the output results include the actual body strength score of the target vehicle, the strength performance level, and the stress score corresponding to the corresponding first grid area; and feedback different safety warnings to the corresponding staff according to the corresponding strength performance level; At the same time, set different numerical intervals for the obtained stress scores, with the same numerical difference between each numerical interval. Set different color temperatures of colors for different numerical intervals, and represent each numerical interval with a specific color. The higher the stress score, the higher the color temperature of the color, and then generate the corresponding body stress color temperature map and feedback it to the staff for viewing; so that the staff can view the corresponding high-stress areas and optimize and improve them.

[0020] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for evaluating the strength performance of an automobile body based on a collision test, characterized in that: The following steps are involved: Step 1: Collect the body structure data of the target car, and build a car body model based on the collected body structure data; Step 2: Select a collision scene, divide the collision area of ​​the target car into grids according to the collision scene, obtain the corresponding grid area, perform a collision test on the target car, and collect data changes in the corresponding grid area to obtain the corresponding real car collision data and simulated collision data; Step 3: Analyze the collected simulated collision data, and perform performance evaluation on the body strength of the target vehicle based on the analysis results; Step 4: Construct a corresponding vehicle evaluation model based on the performance evaluation results, and obtain the actual body strength evaluation results of the target vehicle based on the obtained vehicle evaluation model and actual collision data.

2. The method for evaluating the strength performance of an automobile body based on a collision test according to claim 1, characterized in that: The process of collecting the body structure data of the target vehicle and constructing the vehicle body model based on the collected body structure data includes: Collecting data on the body structure of the target vehicle to obtain corresponding body structure data, and after the body structure data collection is completed, classifying the collected body structure data according to the body structure of the target vehicle to obtain corresponding body component data, and constructing a corresponding body component model according to the obtained body component data; The design structure of the target car is obtained, and the obtained body component models are spliced ​​according to the obtained design structure to obtain a corresponding car body model.

3. The method for evaluating the strength performance of an automobile body based on a collision test according to claim 2, characterized in that: The process of selecting a collision scene and performing a car collision test in combination with the obtained car body model includes: A collision scene is selected, and a corresponding automobile collision area is determined according to the selected collision scene. The obtained automobile collision area is divided into regions in an equal manner to obtain a number of collision sub-regions. After the division is completed, a standard judgment is made on the corresponding collision sub-region according to the division standard. If the corresponding collision sub-region meets the division standard, the collision sub-region after the last division is marked as the first grid area; if the corresponding collision sub-region does not meet the division standard, the corresponding automobile collision area continues to be divided until it meets the division standard.

4. The method for evaluating automobile body strength performance based on collision test according to claim 3, characterized in that: The division standard refers to whether the obtained first grid area can cover the corresponding car collision area and whether each first grid area meets the deployment requirements of the collection node.

5. The method for evaluating automobile body strength performance based on collision test according to claim 3, characterized in that: The process of performing a collision test on a target car and collecting data changes in the corresponding grid area includes: Setting up collection nodes, and deploying the collection nodes in corresponding grid areas; According to the selected collision scenario, an actual collision environment is constructed, and after the construction is completed, a real vehicle collision test is performed, and data change conditions in the corresponding grid area are collected through the collection node to obtain and store corresponding real vehicle collision data; After the actual vehicle collision test is completed, the corresponding collision key parameters are determined based on the collected actual vehicle collision data; Using the same method, meshing the body area at the same position as the collision area of ​​the vehicle in the corresponding vehicle body model to obtain a corresponding second mesh area; A simulated collision test is performed based on the corresponding key collision parameters and the automobile body model, and the data changes in the corresponding second grid area are recorded to obtain corresponding stress data, deformation data and corresponding simulated collision data.

6. The method for evaluating automobile body strength performance based on collision test according to claim 5, characterized in that: The process of analyzing the collected simulated collision data and evaluating the performance of the target vehicle's body strength based on the analysis results includes: Read the stress data collected in the corresponding second grid area, obtain the maximum value of the stress data in the corresponding second grid area during the corresponding simulated collision test, and record it as the maximum stress; Obtain the corresponding stress and deformation standards of the automobile body according to industry standards, regulations and design criteria; Compare the maximum stress with the corresponding stress standard, and obtain the stress score corresponding to the corresponding second grid area according to the stress range where the corresponding maximum stress is located; Determining a first weight coefficient corresponding to the corresponding second grid area according to the type of vehicle body component to which the corresponding second grid area belongs; reading deformation data in the corresponding second grid area, comparing the obtained deformation data with the corresponding deformation standard, and determining a second weight coefficient of the second grid area according to the comparison result, Obtaining a body strength score of the target vehicle according to the obtained first weight coefficient, second weight coefficient and stress score; Set a strength threshold, compare the obtained vehicle body strength score with the strength threshold, and obtain the corresponding strength performance level based on the comparison result.

7. The method for evaluating automobile body strength performance based on collision test according to claim 6, characterized in that: The process of building a corresponding vehicle evaluation model based on the performance evaluation results includes: Collecting data related to the corresponding simulated collision test, including simulated collision data, stress data, deformation data, vehicle body strength score, and strength performance grade, to obtain a corresponding first data set; Using the same method, data analysis is performed on several simulated collision tests under different collision conditions to obtain a corresponding Nth data set; Building a corresponding initial automobile evaluation model based on neural network technology, iteratively training the corresponding initial automobile evaluation model based on the obtained N+1 data sets, waiting for the loss function to score, and retaining the corresponding model parameters; Based on big data technology, historical real vehicle collision data corresponding to the same type of vehicles as the target vehicle is obtained, and parameters of the initial vehicle evaluation model completed by iterative training are adjusted according to the obtained historical real vehicle collision data. After the adjustment is completed, the accuracy of the corresponding initial vehicle evaluation model is verified. If the verification passes, the model is output to obtain the corresponding vehicle evaluation model.

8. According to the method for evaluating automobile body strength performance based on collision test in claim 7, the process of obtaining the actual body strength evaluation result of the target automobile based on the obtained automobile evaluation model and actual collision data comprises: Inputting the collected real vehicle collision data into the vehicle evaluation model to obtain corresponding output results, wherein the output results include the actual vehicle body strength score, the strength performance grade, and the stress score corresponding to the corresponding first grid area of ​​the target vehicle; And provide different safety warnings to corresponding staff according to the corresponding strength performance level; At the same time, different numerical ranges are set for the obtained stress scores. The numerical differences between each numerical range are the same. Different color temperatures are set for different numerical ranges. One numerical range is represented by a special color. The higher the stress score, the higher the color temperature. The corresponding vehicle body stress color temperature map is then generated and fed back to the staff.

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