Accident vehicle damage prediction method based on finite element analysis, electronic equipment and medium

Abstract

The invention discloses an accident vehicle damage prediction method based on finite element analysis, electronic equipment and a medium. The method comprises the following steps: constructing a traffic accident actual scene based on vehicle auxiliary driving data; acquiring collision data at an accident occurrence moment; building a whole vehicle finite element model, and inputting the collision data into the whole vehicle finite element model; performing finite element simulation analysis on the whole vehicle finite element model to obtain an accident simulation dynamic graph and a vehicle stress-strain cloud graph; and according to the accident simulation dynamic picture and the vehicle stress-strain cloud picture, a vehicle damaged part list is determined. According to the invention, after the traffic accident of the vehicle occurs, the damage condition of the vehicle can be quickly and accurately determined at the first time, and a list of damaged parts of the vehicle is provided.

Description

Technical Field

[0001] The present invention relates to the field of vehicle damage prediction, and more specifically, to a method, electronic equipment and medium for predicting accident vehicle damage based on finite element analysis. Background Art

[0002] In a road traffic accident, vehicles are often damaged to varying degrees and need to be repaired or have damaged parts replaced. After a traffic accident, the owner needs a professional damage assessment agency to assess the damaged vehicle to determine the cost of repair and the amount of compensation. The main damage assessment methods currently adopted are accident photos and vehicle dismantling. Accident photos can only reflect the damage to the vehicle's exterior, and the extent of damage to the vehicle's internal structure cannot be directly obtained. Vehicle dismantling requires the accident vehicle to be consigned to a Zhixin repair shop, which delays the owner's use of the vehicle and affects the efficiency of insurance claims. Inaccurate vehicle damage assessment results can lead to disagreements between the owner and the insurance company.

[0003] Therefore, it is necessary to develop an accident vehicle damage prediction method, electronic equipment and medium based on finite element analysis.

[0004] The information disclosed in the background technology section of the present invention is only intended to deepen the understanding of the general background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0005] The present invention proposes a method, electronic equipment and medium for predicting damage to an accident vehicle based on finite element analysis, which can quickly and accurately determine the damage to the vehicle and provide a list of damaged vehicle parts in the first place after a traffic accident occurs.

[0006] In a first aspect, an embodiment of the present disclosure provides a method for predicting damage to an accident vehicle based on finite element analysis, comprising:

[0007] Construct actual traffic accident scenarios based on vehicle assisted driving data;

[0008] Obtain collision data at the time of the accident;

[0009] Building a finite element model of the whole vehicle, and inputting the collision data into the finite element model of the whole vehicle;

[0010] Performing finite element simulation analysis on the whole vehicle finite element model to obtain an accident simulation dynamic diagram and a vehicle stress-strain cloud diagram;

[0011] A list of damaged vehicle parts is determined based on the accident simulation animation and the vehicle stress-strain cloud map.

[0012] Preferably, based on the vehicle assisted driving data, constructing the actual scenario when the vehicle has a traffic accident includes:

[0013] Collect data from radar, cameras and global positioning systems, record the vehicle's speed, acceleration, position and information on surrounding obstacles in real time, determine the vehicle's driving status, surrounding environment and the relative position relationship of other traffic participants, combine the braking system, steering system and airbag status, restore the vehicle's dynamic driving process, and construct the actual scene of the traffic accident.

[0014] Preferably, the collision data includes the instantaneous speed, collision angle and relative position relationship of the vehicle when the collision occurs.

[0015] Preferably, obstacle information when a collision occurs is defined according to the constructed actual scenario, the collision data is written into a control parameter file of the whole vehicle finite element model, and output parameters of animation, cloud map and curve are set for the model.

[0016] Preferably, performing finite element simulation analysis on the whole vehicle finite element model includes:

[0017] LS-DYNA software is used to solve and calculate the finite element model of the whole vehicle, check whether the energy curve is conserved and whether there are any abnormalities in the mass increase, check whether the vehicle deformation and collision area damage in the result animation are abnormal, and adjust and correct all abnormal items.

[0018] Preferably, according to the finite element simulation analysis results, the accident simulation dynamic diagram and the stress-strain cloud diagram are generated by using post-processing software.

[0019] The accident simulation animation can show the process of vehicle collision, predict the contact between various components, and clarify the response characteristics of the vehicle structure;

[0020] The stress-strain cloud map can view the stress-strain distribution of the vehicle during the stress process of the collision accident, analyze the stress state and deformation degree of each component, and thus determine the degree of damage to the vehicle in the accident.

[0021] Preferably, determining the list of damaged vehicle parts includes:

[0022] By using a pre-established vehicle parts database, the damaged parts analyzed according to the accident simulation dynamic diagram and the vehicle stress-strain cloud diagram are matched with the parts information in the database, and a vehicle damaged parts list is automatically generated according to the matching results.

[0023] In a second aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0024] A memory storing executable instructions;

[0025] A processor runs the executable instructions in the memory to implement the accident vehicle damage prediction method based on finite element analysis.

[0026] In a third aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the accident vehicle damage prediction method based on finite element analysis is implemented.

[0027] The methods and apparatus of the present invention have other features and advantages that will be apparent from, or will be described in detail in, the accompanying drawings and subsequent detailed descriptions incorporated herein, which together serve to explain the specific principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present invention.

[0029] Figure 1 A flowchart showing the steps of a method for predicting damage of an accident vehicle based on finite element analysis according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0031] To facilitate understanding of the solutions and effects of the embodiments of the present invention, three specific application examples are given below. Those skilled in the art should understand that the examples are only for facilitating understanding of the present invention, and any specific details thereof are not intended to limit the present invention in any way.

[0032] Example 1

[0033] Figure 1 A flowchart showing the steps of a method for predicting damage of an accident vehicle based on finite element analysis according to an embodiment of the present invention.

[0034] like Figure 1 As shown, the accident vehicle damage prediction method based on finite element analysis includes:

[0035] Step 101, constructing an actual traffic accident scenario based on vehicle assisted driving data;

[0036] Step 102, obtaining collision data at the time of the accident;

[0037] Step 103, building a finite element model of the whole vehicle, and inputting the collision data into the finite element model of the whole vehicle;

[0038] Step 104, performing finite element simulation analysis on the whole vehicle finite element model to obtain an accident simulation dynamic diagram and a vehicle stress-strain cloud diagram;

[0039] Step 105, determining a list of damaged vehicle parts based on the accident simulation animation and the vehicle stress-strain cloud map.

[0040] In one example, based on vehicle assisted driving data, constructing an actual scenario when a vehicle has a traffic accident includes:

[0041] Collect data from radar, cameras and global positioning systems, record the vehicle's speed, acceleration, position and surrounding obstacle information in real time, determine the vehicle's driving status, surrounding environment and the relative position relationship of other traffic participants, combine the braking system, steering system and airbag status to restore the vehicle's dynamic driving process and construct the actual traffic accident scene.

[0042] In one example, the collision data includes the instantaneous speed, collision angle, and relative position relationship of the vehicle when the collision occurs.

[0043] In one example, obstacle information when a collision occurs is defined according to the actual constructed scenario, the collision data is written into a control parameter file of a finite element model of the entire vehicle, and output parameters of animation, cloud map, and curve are set for the model.

[0044] In one example, the finite element simulation analysis for the whole vehicle finite element model includes:

[0045] Use LS-DYNA software to solve and calculate the finite element model of the whole vehicle, check whether the energy curve is conserved and whether there are any abnormalities in the mass increase, check whether the vehicle deformation and collision area damage in the result animation are abnormal, and adjust and correct all abnormal items.

[0046] In one example, based on the finite element simulation analysis results, post-processing software was used to generate accident simulation animations and stress-strain cloud maps.

[0047] Among them, the accident simulation animation can show the process of vehicle collision, predict the mutual contact between various components, and clarify the response characteristics of the vehicle structure;

[0048] The stress-strain cloud map can view the stress-strain distribution of the vehicle during the force process of a collision accident, analyze the stress state and deformation degree of each component, and thus determine the degree of damage to the vehicle in the accident.

[0049] In one example, determining a list of damaged vehicle parts includes:

[0050] Using the pre-established vehicle parts database, the damaged parts analyzed based on the accident simulation animation and vehicle stress-strain cloud map are matched with the parts information in the database, and a list of damaged vehicle parts is automatically generated based on the matching results.

[0051] Specifically, based on the vehicle assisted driving data, the actual scene of the vehicle in the event of a traffic accident is constructed. The vehicle assisted driving sensor data, including radar, camera and global positioning system (GPS), etc., are collected. These sensors can record the vehicle's speed, acceleration, position and surrounding obstacle information in real time, and are used to determine the vehicle's driving status, the surrounding environment and the relative position relationship of other traffic participants. Combined with the braking system, steering system and airbag status, the dynamic driving process of the vehicle is restored to construct the actual scene of the traffic accident.

[0052] Identify the triggering moment of the accident collision and extract the instantaneous speed, collision angle and relative position relationship of the vehicle when the collision occurs. Fuse the data recorded by each sensor to ensure that the time history of all data is consistent, form a unified perception of the vehicle's surrounding environment, identify the triggering moment of the accident collision by monitoring the abnormal driving state of the vehicle, and extract the instantaneous speed, collision angle and relative position relationship of the vehicle when the collision occurs.

[0053] Build a finite element model of the whole vehicle. The finite element model of the whole vehicle adopts a modular approach, dividing the whole vehicle model into multiple assemblies for modeling. The whole vehicle model needs to include the body-in-white assembly, opening and closing assembly, suspension system, power system, high-voltage system, interior assembly, exterior assembly, electrical system, steering system, cooling system and control parameter files.

[0054] The vehicle geometry data takes into account the characteristics of engineering design and manufacturing process, and will have subtle features such as chamfers, fillets, grooves, bosses and process holes. These features are mainly used for manufacturing and assembly in product design, have little effect on mechanical properties, and affect the quality of mesh division. These features can be ignored and simplified during model building, giving priority to ensuring the quality of generated meshes, reducing the number of meshes, and improving simulation solution efficiency. Throughout the simplification process, it is necessary to always maintain a keen insight into the mechanical properties of the model to ensure that the ignored features do not have a significant impact on key stress distribution, deformation mode or overall structural strength.

[0055] According to the reasonable mesh size, the simplified geometric data is meshed. The unit type is mainly quadrilateral units, which have good stability and accuracy in numerical analysis and can simulate physical phenomena more accurately. In the transition part of geometric features such as variable cross-sections and complex surfaces, it is difficult to completely use quadrilateral units due to the complex shape. The transition part allows triangular units to be used for meshing, but the proportion of the number of triangular units in the model must be strictly controlled. After the meshing is completed, the quality of the mesh needs to be checked. This includes checking the maximum and minimum size, maximum and minimum angle, aspect ratio, warpage, Jacobian and other quality indicators of the mesh to ensure that they meet the analysis requirements. If it is found that the mesh quality does not meet the requirements, it needs to be adjusted and optimized, and at the same time, the penetration of the mesh between the components and the phenomenon of single-sided quadrilateral mesh can be avoided. Through adjustment and optimization, the quality of the mesh can be improved, and problems such as energy anomalies, mesh distortion and calculation errors can be avoided, thereby improving the stability and calculation efficiency of the analysis, and preparing for the automatic identification of damaged parts in subsequent analysis results.

[0056] During the vehicle assembly process, in order to ensure the structural strength, safety and functionality of the vehicle, various connection methods such as spot welding, seam welding, riveting, bolting, gluing and hinging are used. The model is simulated according to the actual connection method to ensure that the connection method in the model is consistent with the real vehicle, thereby improving the accuracy of the model.

[0057] According to the actual scene of the vehicle traffic accident constructed according to the vehicle sensor data, the obstacle information at the time of collision is defined, the extracted parameters such as the instantaneous speed, collision angle and relative position relationship of the vehicle at the time of collision are written into the control parameter file, and the output parameters of the animation, cloud map and curve are set for the model.

[0058] Finite element simulation analysis. Use LS-DYNA software to solve and calculate the model, check whether the energy curve is conserved and whether there are any abnormalities in the mass increase, check whether the vehicle deformation and collision area damage in the result animation are abnormal, and adjust and correct all abnormal items.

[0059] Based on the results of finite element simulation analysis, the post-processing software is used to generate accident simulation animations, which can intuitively show the process of vehicle collision, predict the mutual contact between various components, and clarify the response characteristics of the vehicle structure. At the same time, the post-processing software is used to generate the vehicle's stress-strain cloud map to view the stress-strain distribution of the vehicle during the collision accident, analyze the stress state and deformation degree of each component, and thus determine the degree of damage to the vehicle in the accident.

[0060] Automatically generate a list of damaged vehicle parts. Using the pre-established vehicle parts database, the analyzed damaged parts are matched with the parts information in the database, and a list of damaged vehicle parts is automatically generated based on the matching results. The list contains relevant information about the parts, such as name, model, etc., and also indicates the degree of damage and replacement or repair suggestions. The generated list of damaged vehicle parts will serve as an important basis for vehicle maintenance, insurance claims and accident investigations, providing clear and accurate information support for all parties involved. This process not only improves the efficiency of accident handling, but also ensures the accuracy of maintenance work, bringing greater convenience and protection to car owners and insurance companies.

[0061] Example 2

[0062] The present disclosure provides an electronic device, which includes: a memory storing executable instructions; a processor running the executable instructions in the memory to implement the above-mentioned accident vehicle damage prediction method based on finite element analysis.

[0063] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0064] The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0065] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory.

[0066] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0067] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0068] Example 3

[0069] An embodiment of the present disclosure provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the accident vehicle damage prediction method based on finite element analysis is implemented.

[0070] According to the computer-readable storage medium of the embodiment of the present disclosure, non-transitory computer-readable instructions are stored thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the method of each embodiment of the present disclosure are executed.

[0071] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0072] Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to exemplarily illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any given examples.

[0073] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for predicting accident vehicle damage based on finite element analysis, characterized in that: include: Construct actual traffic accident scenarios based on vehicle assisted driving data; Obtain collision data at the time of the accident; Building a finite element model of the whole vehicle, and inputting the collision data into the finite element model of the whole vehicle; Performing finite element simulation analysis on the whole vehicle finite element model to obtain an accident simulation dynamic diagram and a vehicle stress-strain cloud diagram; A list of damaged vehicle parts is determined based on the accident simulation animation and the vehicle stress-strain cloud map.

2. The accident vehicle damage prediction method based on finite element analysis according to claim 1, wherein: Based on the vehicle assisted driving data, the actual scenario of a traffic accident is constructed, including: Collect data from radar, cameras and global positioning systems, record the vehicle's speed, acceleration, position and information on surrounding obstacles in real time, determine the vehicle's driving status, surrounding environment and the relative position relationship of other traffic participants, combine the braking system, steering system and airbag status, restore the vehicle's dynamic driving process, and construct the actual scene of the traffic accident.

3. The accident vehicle damage prediction method based on finite element analysis according to claim 1, wherein: The collision data includes the instantaneous speed, collision angle and relative position relationship of the vehicles when the collision occurs.

4. The accident vehicle damage prediction method based on finite element analysis according to claim 1, wherein: The obstacle information when a collision occurs is defined according to the constructed actual scenario, the collision data is written into the control parameter file of the whole vehicle finite element model, and the output parameters of the animation, cloud map and curve are set for the model.

5. The accident vehicle damage prediction method based on finite element analysis according to claim 1, wherein: The finite element simulation analysis for the whole vehicle finite element model includes: LS-DYNA software is used to solve and calculate the finite element model of the whole vehicle, check whether the energy curve is conserved and whether there are any abnormalities in the mass increase, check whether the vehicle deformation and collision area damage in the result animation are abnormal, and adjust and correct all abnormal items.

6. The accident vehicle damage prediction method based on finite element analysis according to claim 1, wherein: According to the finite element simulation analysis results, the accident simulation dynamic diagram and the stress-strain cloud diagram are generated by using post-processing software. The accident simulation animation can show the process of vehicle collision, predict the contact between various components, and clarify the response characteristics of the vehicle structure; The stress-strain cloud map can view the stress-strain distribution of the vehicle during the stress process of the collision accident, analyze the stress state and deformation degree of each component, and thus determine the degree of damage to the vehicle in the accident.

7. The accident vehicle damage prediction method based on finite element analysis according to claim 1, wherein: The list of damaged vehicle parts includes: By using a pre-established vehicle parts database, the damaged parts analyzed according to the accident simulation dynamic diagram and the vehicle stress-strain cloud diagram are matched with the parts information in the database, and a vehicle damaged parts list is automatically generated according to the matching results.

8. An electronic device, characterized in that: The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the accident vehicle damage prediction method based on finite element analysis as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the accident vehicle damage prediction method based on finite element analysis described in any one of claims 1 to 7 is implemented.

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