Automobile stone impact dynamic simulation and evaluation method, device, equipment, medium and product

Abstract

The application relates to the technical field of vehicle simulation, in particular to a vehicle stone impact dynamic simulation and evaluation method, device, equipment, medium and product, which comprises the following steps: acquiring vehicle data and road surface data, wherein the road surface data comprises stone particle data; establishing a multi-body dynamics model of the vehicle according to the vehicle data, establishing a discrete element model according to the road surface data, setting a generation rule of the stone particles in the discrete element model, and generating the stone particles based on the generation rule; connecting the multi-body dynamics model and the discrete element model to a coupling simulation interface, calling the multi-body dynamics model and the discrete element model to execute a simulation action through the coupling simulation interface, outputting tire motion data based on the multi-body dynamics model during the execution of the simulation action, and outputting the interaction force of the stone particles on the tire based on the discrete element model; and generating a vehicle stone impact evaluation result according to the vehicle load data during the execution of the simulation action. The problems of high test cost, long cycle and poor repeatability in the related art are solved.

Description

Technical Field

[0001] This application relates to the field of vehicle simulation technology, and in particular to a method, apparatus, equipment, medium and product for dynamic simulation and evaluation of automobile stone impact. Background Technology

[0002] When a vehicle is traveling at high speed, stones on the road can damage the surface coating of the metal parts under the vehicle, which has a very negative impact on the corrosion resistance of the metal parts. This is very easy to detect during use and will directly lower the brand's reputation, thereby affecting the trust of many potential consumers in the brand.

[0003] However, for discrete element method and fluid dynamics simulations of coatings, the relevant technologies usually require real impact tests during the physical test or the stone impact test of automobiles on a dedicated test bench, but cannot reflect the real aerodynamic environment of the whole vehicle in motion. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, medium, and product for dynamic simulation and evaluation of stone impact on automobiles, in order to solve the problems of high testing costs, long cycles, and poor repeatability in related technologies.

[0005] The first aspect of this application provides a method for dynamic simulation and evaluation of stone impact on a vehicle, comprising the following steps: acquiring vehicle data and road surface data, the road surface data including stone particle data; establishing a multibody dynamics model of the vehicle based on the vehicle data, establishing a discrete element model based on the road surface data, the discrete element model having rules for stone particle generation, and generating stone particles based on the generation rules; connecting the multibody dynamics model and the discrete element model to a coupled simulation interface, calling the multibody dynamics model and the discrete element model to execute simulation actions through the coupled simulation interface, outputting tire motion data based on the multibody dynamics model, and outputting the interaction force of stone particles on the tire based on the discrete element model; and generating a vehicle stone impact evaluation result based on vehicle load data during the execution of the simulation actions.

[0006] Optionally, a multibody dynamics model of the vehicle is established based on the vehicle data, including: extracting tire geometry data, suspension geometry data, and chassis geometry data from the vehicle data; establishing a vehicle model based on the tire geometry data, suspension geometry data, and chassis geometry data, and setting tire attributes and vehicle load states in the vehicle model; and establishing a multibody dynamics model based on the vehicle model, tire attributes, and load states.

[0007] Optionally, a discrete element model is established based on the road surface data, including: extracting gravel particle data, road surface geometry data, and interaction data from the road surface data; establishing a road surface model based on the gravel particle data and road surface geometry data; determining the contact model between the vehicle and the gravel particles based on the interaction data; and generating a discrete element model based on the road surface model and the contact model.

[0008] Optionally, the multibody dynamics model and the discrete element model are connected to the coupled simulation interface, including: activating the coupled simulation interface of the coupled communicator plugin; and enabling all moving parts in the multibody dynamics model to communicate with the discrete element model through the coupled simulation interface to achieve bidirectional data exchange between all moving parts and the discrete element model.

[0009] Optionally, simulation actions can be performed by calling the multibody dynamics model and the discrete element model through the coupled simulation interface, including: at the current simulation time step, inputting the tire motion data of the previous simulation time step and the interaction force of the discrete element model of the previous simulation time step into the multibody dynamics model, and calculating the tire motion data of all moving parts at the current simulation time step through the multibody dynamics model; sending the tire motion data of the current simulation time step to the discrete element model through the coupled simulation interface, and calculating the interaction force at the current simulation time step through the discrete element model; and stopping the simulation action until the current simulation time step reaches the stop time step.

[0010] Optionally, a vehicle stone impact assessment result is generated based on the vehicle load data during the simulation action execution, including: extracting the load data and time-domain curve of each moving part from the vehicle load data; calculating the impact force and wear amount of the vehicle impacting the stone particles based on the load data and time-domain curve of each moving part; and generating the vehicle stone impact assessment result based on the impact force and wear amount.

[0011] A second aspect of this application provides a vehicle stone impact dynamic simulation and evaluation device, comprising: an acquisition module for acquiring vehicle data and road surface data, the road surface data including stone particle data; an establishment module for establishing a multibody dynamics model of the vehicle based on the vehicle data and a discrete element model based on the road surface data, the discrete element model having stone particle generation rules set, and generating stone particles based on the generation rules; an output module for connecting the multibody dynamics model and the discrete element model to a coupled simulation interface, calling the multibody dynamics model and the discrete element model to execute simulation actions through the coupled simulation interface, outputting tire motion data based on the multibody dynamics model and outputting the interaction force of stone particles on the tire based on the discrete element model during the execution of the simulation actions; and a generation module for generating vehicle stone impact evaluation results based on vehicle load data during the execution of the simulation actions.

[0012] Optionally, the module is further used to: extract tire geometry data, suspension geometry data, and chassis geometry data from the vehicle data; build a vehicle model based on the tire geometry data, suspension geometry data, and chassis geometry data, and set the tire attributes and vehicle load states in the vehicle model; and build a multibody dynamics model based on the vehicle model, tire attributes, and load states.

[0013] Optionally, the module is further used to: extract gravel particle data, road surface geometry data, and interaction data from the road surface data; build a road surface model based on the gravel particle data and road surface geometry data; determine the contact model between the vehicle and the gravel particles based on the interaction data; and generate a discrete element model based on the road surface model and the contact model.

[0014] Optionally, the output module is further used to: activate the coupled simulation interface of the coupled communicator plugin; and enable all moving parts in the multibody dynamics model to communicate with the discrete element model through the coupled simulation interface, so as to realize bidirectional data exchange between all moving parts and the discrete element model.

[0015] Optionally, the output module is further configured to: input the tire motion data from the previous simulation time step and the interaction forces from the discrete element model of the previous simulation time step into the multibody dynamics model at the current simulation time step, and calculate the tire motion data of all moving parts at the current simulation time step through the multibody dynamics model; send the tire motion data of the current simulation time step to the discrete element model through the coupled simulation interface, and calculate the interaction forces at the current simulation time step through the discrete element model; and stop the simulation action until the current simulation time step reaches the stop time step.

[0016] Optionally, the generation module is further used to: extract load data and time-domain curves of each moving part from the vehicle load data; calculate the impact force and wear amount of the vehicle impacting the stone particles based on the load data and time-domain curves of each moving part; and generate vehicle stone impact assessment results based on the impact force and wear amount.

[0017] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the vehicle stone impact dynamic simulation and evaluation method as described in the above embodiments.

[0018] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the vehicle stone impact dynamic simulation and evaluation method as described in the above embodiments.

[0019] The fifth aspect of this application provides a computer program that, when executed, is used to implement the vehicle stone impact dynamic simulation and evaluation method as described in the above embodiments.

[0020] Therefore, this application has the following beneficial effects: This application's embodiments collect vehicle data and road surface data containing gravel particles. A multi-body dynamics model of the vehicle is constructed based on the vehicle data, and a discrete element model is built using the road surface data. Gravel particle generation rules are set to generate gravel particles. The multi-body dynamics model and the discrete element model are connected to a coupled simulation interface. Through this interface, a collaborative simulation is performed between the multi-body dynamics model and the discrete element model. During the simulation, the multi-body dynamics model outputs tire motion data, and the discrete element model outputs the interaction force between the gravel particles and the tire. Finally, based on the vehicle load data generated during the simulation, a gravel impact assessment result is generated. This accurately recreates the dynamic interaction process between the tire and gravel particles, capturing the correlation between tire motion and gravel force. The generated gravel impact assessment result comprehensively reflects the stress and wear characteristics and anti-gravel impact performance of various vehicle components under gravel impact conditions. It enables flexible adjustment of vehicle parameters and road gravel distribution simulations when the vehicle is driving on gravel-covered roads. Repeated simulation analysis significantly reduces R&D costs, shortens the R&D cycle, improves testing efficiency and accuracy, and ensures vehicle driving safety and reliability. Therefore, it solves the problems of high testing costs, long cycles, and poor repeatability in related technologies.

[0021] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0022] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a dynamic simulation and evaluation method for automobile stone impact provided according to an embodiment of this application; Figure 2 This is a flowchart illustrating a dynamic simulation and evaluation method for automobile stone impact according to an embodiment of this application. Figure 3 This is a schematic diagram of a vehicle stone impact dynamic simulation and evaluation device provided according to an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0023] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0024] The following description, with reference to the accompanying drawings, describes a method, apparatus, equipment, medium, and product for dynamic simulation and evaluation of vehicle stone impact according to embodiments of this application. Addressing the problems of high testing costs, long cycles, and poor repeatability in related technologies mentioned in the background section, this application provides a method for dynamic simulation and evaluation of vehicle stone impact. In this method, vehicle data and road surface data containing stone particle data are collected. A multi-body dynamics model of the vehicle is constructed based on the vehicle data. A discrete element model is built by combining the road surface data, and stone particle generation rules are set to generate stone particles. The multi-body dynamics model and the discrete element model are connected to a coupled simulation interface. Co-simulation is performed by calling the multi-body dynamics model and the discrete element model through the interface. During the simulation, the multi-body dynamics model outputs tire motion data, and the discrete element model outputs... The model outputs the interaction force between the stone particles and the tire, and finally generates a stone impact assessment result based on the vehicle load data generated during the simulation. It can realistically reproduce the dynamic interaction process between the tire and the stone particles, capturing the correlation between the tire's motion state and the stone impact force. The generated stone impact assessment result can comprehensively reflect the stress and wear characteristics and stone impact resistance performance of various vehicle components under stone impact conditions. It enables flexible adjustment of vehicle parameters and road stone distribution simulations when the vehicle is driving on stone-covered roads. Repeated simulation analysis significantly reduces R&D costs, shortens the R&D cycle, improves testing efficiency and accuracy, and ensures vehicle driving safety and reliability. Therefore, it solves the problems of high testing costs, long cycles, and poor repeatability in related technologies.

[0025] Specifically, Figure 1 A flowchart illustrating a dynamic simulation and evaluation method for stone impact on a car, provided as an embodiment of this application.

[0026] like Figure 1 As shown, the dynamic simulation and evaluation method for automobile stone impact includes the following steps: In step S101, vehicle data and road surface data are acquired, including gravel particle data.

[0027] Understandably, vehicle data is a set of parameters describing the vehicle's structure, dynamics, and aerodynamic characteristics; road surface data is a set of parameters describing the physical characteristics, geometry, and environmental conditions of the road surface on which the vehicle travels. Vehicle data can include vehicle speed, suspension characteristics, tire type, and the coefficient of friction and recovery coefficient between gravel and tire / chassis; gravel particle data describes the characteristics of gravel interacting with the coating. Vehicle data can include vehicle speed, suspension characteristics, tire type, and the coefficient of friction and recovery coefficient between gravel and tire / chassis.

[0028] Specifically, the system motion parameters, such as vehicle speed range, suspension stiffness / damping and tire model, are retrieved first, and dynamic change data of vehicle speed are calibrated in conjunction with actual vehicle tests. Then, gravel samples from different road surfaces are collected, the gravel particle size distribution is measured and the gravel material density is tested. Finally, through indoor contact tests, the contact scenarios between gravel and tires / chassis are simulated, and the friction coefficient and recovery coefficient between gravel and tires / chassis are calculated.

[0029] In step S102, a multibody dynamics model of the vehicle is established based on the vehicle data, and a discrete element model is established based on the road surface data. The discrete element model has rules for the generation of gravel particles, and gravel particles are generated based on the rules.

[0030] Among them, the multibody dynamics model is used to simulate the motion characteristics and interactions of the whole vehicle and its components, and to realistically reflect the dynamic response brought about by system motion parameters such as vehicle speed and suspension characteristics; the discrete element model is used to digitally model the road surface morphology and gravel particles, and to construct the basic model of gravel particles by setting relevant parameters; the generation rule is the rule used in the discrete element model to regulate the generation of gravel particles.

[0031] It is understood that the embodiments of this application construct a multibody dynamics model reflecting the motion characteristics of various vehicle components and system motion parameters based on vehicle data. At the same time, it relies on road surface data to restore the road surface morphology and adapts a discrete element model for simulating gravel particles. In the discrete element model, reasonable generation rules are preset based on the actual characteristics of gravel particles. Then, according to the rules, gravel particles that conform to the actual vehicle road surface scenario are generated, thus constructing a multibody dynamics model of the vehicle and a discrete element model of the road surface that fit the actual vehicle working conditions. The generated gravel particles can realistically restore the distribution, physical and geometric characteristics of actual road gravel, realizing the digital simulation of vehicle motion and road gravel particles.

[0032] Specifically, the collected vehicle data is processed and calibrated to select parameters such as vehicle speed, suspension characteristics, and tire model. Using multibody dynamics simulation software, a multibody dynamics model of the vehicle is built, and the digital modeling of components such as the body, suspension, and tires is completed in sequence. The constraint relationships and motion parameters between each component are defined to simulate the dynamic response of the vehicle during driving.

[0033] Subsequently, the gravel particle data in the road surface data was sorted out, and a discrete element model was constructed based on discrete element simulation software to restore the macroscopic geometry and microscopic surface characteristics of the road surface. At the same time, combined with parameters such as gravel particle size distribution, material density, and geometric shape, reasonable gravel particle generation rules were preset in the discrete element model to clarify the region, quantity, particle size range, and distribution law of particle generation.

[0034] Finally, the simulation program is started. Based on the preset generation rules, the required stone particles are automatically generated in the discrete element road surface model. After generation, the particle parameters and model adaptability are checked and calibrated.

[0035] Furthermore, in the embodiments of this application, establishing a multibody dynamics model of a vehicle based on vehicle data includes: extracting tire geometry data, suspension geometry data, and chassis geometry data from the vehicle data; establishing a vehicle model based on the tire geometry data, suspension geometry data, and chassis geometry data, and setting tire attributes and vehicle load states in the vehicle model; and establishing a multibody dynamics model based on the vehicle model, tire attributes, and load states.

[0036] Among them, tire geometry data is data extracted from vehicle data that describes the shape and structural dimensions of the tire; suspension geometry data is geometric parameters used to reconstruct the structural form of the suspension and support its motion characteristics; chassis geometry data is a set of geometric parameters related to the vehicle chassis; the vehicle model is a digital model of the entire vehicle built based on the extracted tire, suspension, and chassis geometry data; tire attributes are attributes used to simulate the elastic deformation, force feedback, and interaction with the road surface of the tire during driving; and vehicle load state is used to simulate the force state of the vehicle during actual driving.

[0037] It is understood that the embodiments of this application extract geometric data related to tires, suspension, and chassis from vehicle data, and build a vehicle model that restores the spatial layout and connection relationship of the vehicle structure based on this data. Then, tire attributes related to the physical characteristics of the tires and vehicle load states that conform to the actual driving conditions are set for the vehicle model. Finally, by combining the built vehicle model, the set tire attributes and load states, a multibody dynamics model that can reflect the actual motion characteristics of the vehicle is constructed. A multibody dynamics model of the vehicle that conforms to the actual vehicle structure and working conditions is successfully constructed, restoring the geometric shape of the tires, suspension, and chassis, as well as the force and motion state of the vehicle, thus ensuring the accuracy and reliability of the multibody dynamics model.

[0038] Specifically, tire geometry, suspension geometry, and chassis geometry are extracted from the collected vehicle data. Based on this, a geometric model containing components such as tires, suspension, and chassis is constructed using CATIA (Computer-graphics Aided Three-dimensional Interactive Application) software. After the CATIA geometric model is completed, it is imported into a multibody dynamics simulation software for geometric processing, simplifying and optimizing the model. Subsequently, in the multibody dynamics software, according to the actual structural characteristics and stress conditions of each component of the vehicle, the corresponding geometric bodies are defined as rigid bodies or flexible bodies. Then, by setting appropriate connection methods such as hinge pairs, constraints, springs, and damping units, the kinematic relationships and constraints between the components are clarified, and a complete and realistic multibody system model of the vehicle is built. To ensure the accuracy of the simulation calculation, the MF tire attribute file is selected to import the model, and the tire-related attributes are set to match the physical characteristics of the real vehicle tires.

[0039] After modeling is completed, the entire multibody dynamics model is fully debugged, load parameters are adjusted to ensure that the vehicle model is in the preset load or full load state, and the connection relationship of each component, constraint conditions and tire attribute settings are checked. The model is repeatedly debugged and optimized until it can reflect the actual structure and stress state of the car, and finally the multibody dynamics model of the car is established.

[0040] Furthermore, in the embodiments of this application, establishing a discrete element model based on road surface data includes: extracting gravel particle data, road surface geometry data, and interaction data from the road surface data; establishing a road surface model based on the gravel particle data and road surface geometry data; determining the contact model between the vehicle and the gravel particles based on the interaction data; and generating a discrete element model based on the road surface model and the contact model.

[0041] Among them, the contact model is a mechanical calculation model constructed based on the extracted interaction data to define and quantify the contact behavior and mechanical response relationship between automotive parts and stone particles.

[0042] It is understood that the embodiments of this application first extract gravel particle data, road surface geometry data, and interaction data from road surface data. Based on the gravel particle data and road surface geometry data, a road surface model that restores the macroscopic morphology of the road surface and the distribution of gravel particles is built. Then, based on the interaction data, a contact model that quantifies the contact behavior and mechanical response between vehicle components and gravel particles is constructed. Finally, by combining the built road surface model and the determined contact model, a discrete element model that closely matches the actual vehicle road surface conditions is successfully constructed. This model can realistically restore the road surface geometry and gravel particle distribution characteristics, ensuring a high degree of matching between the model and the actual scene. It achieves the simulation of road surface and particle contact through digital modeling without conducting a large number of actual vehicle road surface tests, significantly reducing test costs, shortening the modeling cycle, and allowing for flexible adjustment of various data parameters to adapt to the simulation needs of different road surface conditions, thereby improving modeling efficiency and simulation controllability.

[0043] Specifically, the process begins by creating a gravel material. Based on extracted gravel particle data, the intrinsic properties of the gravel, such as density, Poisson's ratio, and shear modulus, are accurately set to ensure that the material properties are consistent with those of actual gravel. Next, the Oka wear model is selected as the contact model. Combined with extracted interaction data, the contact model is calibrated, and the coefficients of restitution, static friction, and dynamic friction are set between gravel particles and between gravel particles and vehicle components to clarify the rules of mechanical transmission during the contact process. Then, based on road surface geometry data, a road surface geometry model is constructed in the software. Depending on the simulation requirements, the geometry model is defined as a fixed plane or a complex curved surface that conforms to reality. In the road surface area in front of the tire, the gravel generation rules are defined in detail using gravel particle data. These rules include parameters such as generation rate, particle size distribution range, and initial velocity. Subsequently, a discrete element model is run separately to complete particle generation, filling the road surface with gravel that matches the actual vehicle scenario. After generation, the discrete element model is exported, resulting in a discrete element model with a gravel road in its initial state.

[0044] If the number of generated particles is too large, the dynamic domain function can be used to generate particles by building a box area that matches the shape of the road surface. Within this area, stone particles can be generated in batches quickly, effectively improving the efficiency of modeling and subsequent simulation.

[0045] Finally, based on the simulation accuracy and efficiency requirements, the time step for solving the discrete element model is set, and the mesh size is adjusted to ensure that the mesh size is adapted to the particle size and simulation requirements, thus completing the establishment of the discrete element model.

[0046] Therefore, this application embodiment constructs a multibody dynamics model reflecting the motion characteristics of various vehicle components and system motion parameters based on vehicle data. At the same time, it relies on road surface data to restore the road surface morphology and adapts a discrete element model for simulating gravel particles. In the discrete element model, reasonable generation rules are preset based on the actual characteristics of gravel particles. Then, according to the rules, gravel particles that conform to the actual vehicle road surface scenario are generated, thus constructing a multibody dynamics model of the vehicle and a discrete element model of the road surface that fit the actual vehicle working conditions. The generated gravel particles can realistically restore the distribution, physical and geometric characteristics of actual road gravel, realizing the digital simulation of vehicle motion and road gravel particles.

[0047] In step S103, the multibody dynamics model and the discrete element model are connected to the coupled simulation interface. The multibody dynamics model and the discrete element model are called through the coupled simulation interface to execute simulation actions. During the execution of the simulation actions, the tire motion data is output based on the multibody dynamics model, and the interaction force of the stone particles on the tire is output based on the discrete element model.

[0048] Among them, the coupling simulation interface is the docking channel for data interaction and collaborative calculation between the multibody dynamics model and the discrete element model; the simulation action is driven by the coupling interface to run the dynamics model and the discrete element model synchronously, simulating the complete dynamic action process of continuous contact, collision and friction between the tire and the road surface stone particles during vehicle driving; the tire motion data is the tire motion state information output in real time by the multibody dynamics model in the simulation.

[0049] Understandably, by jointly calling and executing the multibody dynamics model and the discrete element model through a coupled simulation interface, the multibody dynamics model outputs tire motion-related data, while the discrete element model outputs interaction data between the stone particles and the tire. This achieves a refined joint simulation of the interaction behavior between the tire and the particle road surface, which can realistically reflect the dynamic coupling relationship between tire motion and particle force, effectively improving the accuracy and completeness of the simulation results.

[0050] Specifically, the preprocessing of the multibody dynamics model and the discrete element model is first completed to clarify the physical parameters, contact characteristics, and simulation boundary conditions of the tire and the gravel. The two models are then connected to a preset coupled simulation interface to complete parameter matching and data communication protocol adaptation between the interface and the model. Subsequently, simulation commands are initiated through the coupled simulation interface to simultaneously call the multibody dynamics model and the discrete element model to start the simulation action. During the simulation, the coupled simulation interface establishes a data interaction channel between the two models in real time to achieve bidirectional data transmission and synchronous updates. The multibody dynamics model calculates and outputs motion data such as the tire's rotational speed, displacement, and acceleration in real time according to the preset simulation conditions, and synchronously feeds it back to the coupled simulation interface. The discrete element model synchronously simulates the motion state of the gravel, calculates and outputs interaction force data such as the squeezing force and friction force during the contact process between the gravel and the tire in real time, and also feeds it back to the coupled simulation interface.

[0051] The coupled simulation interface receives, integrates, and synchronously calibrates the data output from the two models in real time, ensuring the temporal consistency of tire motion data and particle force data, and guaranteeing the continuous execution of simulation actions until the entire simulation process under the preset working conditions is completed.

[0052] Furthermore, in the embodiments of this application, the multibody dynamics model and the discrete element model are connected to the coupled simulation interface, including: activating the coupled simulation interface of the coupled communicator plug-in; and enabling all moving parts in the multibody dynamics model to communicate with the discrete element model through the coupled simulation interface to realize bidirectional data exchange between all moving parts and the discrete element model.

[0053] Among them, the coupling communicator plugin is a dedicated functional plugin used to realize data interconnection between the multibody dynamics model and the discrete element model; bidirectional data exchange allows the multibody dynamics model to transmit the motion state data of moving parts to the discrete element model in real time, while the discrete element model can also transmit data such as the interaction forces between particles and parts back to the multibody dynamics model.

[0054] It is understood that, in this embodiment of the application, by activating the coupling simulation interface of the coupling communicator plug-in, all moving parts of the multibody dynamics model and the discrete element model are connected, realizing bidirectional data interaction between the multibody dynamics model and the discrete element model, thereby completing the joint simulation access of the multibody dynamics and discrete element models. This allows the two models to transmit motion state and contact force information in real time during the simulation, ensuring the synchronization and interactive authenticity of the simulation data, and effectively improving the accuracy and reliability of multiphysics joint simulation.

[0055] Specifically, the geometric parameters, physical properties, and simulation conditions required for the simulation of the multibody dynamics model and the discrete element model are defined. The interface activation operation is initiated to activate the coupling communicator plugin in the discrete element model, thus establishing the basic communication prerequisite between the multibody dynamics model and the discrete element model.

[0056] Subsequently, a discrete element model (DEM) subsystem is created within the multibody dynamics model. All moving parts in the DEM subsystem are transmitted to the DEM in real time through the activated coupled simulation interface. In the DEM, the transmitted geometry is defined as the coupled geometry, and the position and attitude of the coupled geometry at each moment are driven by the multibody dynamics model in real time. At the same time, the specific content of the bidirectional data exchange is defined. The multibody dynamics model mainly sends the translational displacement, velocity, acceleration, rotational Euler angle, angular velocity, angular acceleration, and other motion state data of each coupled geometry in the global coordinate system to the DEM. At each calculation time step, the DEM detects all particles in contact with the coupled geometry in real time, calculates the total force and torque exerted by the particles on the coupled geometry, and feeds back the resultant force vector and resultant torque vector to the corresponding moving parts in the multibody dynamics model in real time through the coupling interface, thus completing the parameter definition for bidirectional data exchange.

[0057] Finally, time step synchronization is set. The multibody dynamics model is used as the master solver, with a larger time step such as 1e-3 seconds. The discrete element model is used as the slave solver, with a smaller time step such as 1e-5 seconds. A reasonable multiple relationship is established between the time steps of the two.

[0058] Furthermore, in the embodiments of this application, the simulation actions are performed by calling the multibody dynamics model and the discrete element model through the coupled simulation interface, including: at the current simulation time step, inputting the tire motion data of the previous simulation time step and the interaction force of the discrete element model of the previous simulation time step into the multibody dynamics model, and calculating the tire motion data of all moving parts at the current simulation time step through the multibody dynamics model; sending the tire motion data of the current simulation time step to the discrete element model through the coupled simulation interface, and calculating the interaction force at the current simulation time step through the discrete element model; and stopping the simulation action until the current simulation time step reaches the stop time step.

[0059] It is understood that the embodiments of this application use a coupled simulation interface to collaboratively call the multibody dynamics model and the discrete element model. In each simulation time step, the tire motion data and particle interaction force of the previous step are used as input. The multibody dynamics model calculates the tire motion data of the current step, and then transmits the data to the discrete element model to calculate the interaction force of the particles on the tire in the current step. The iterative logic continues to advance until the set stop step length is reached to complete the simulation. This can realistically reproduce the physical process of dynamic coupling between the tire and the particle medium, realize the synchronization of the two models in time and the closed-loop interaction of data, effectively improve the accuracy and consistency of the simulation results, and ensure the stability and convergence of the simulation calculation.

[0060] Specifically, the preliminary setup for collaborative simulation in the multibody dynamics model is completed, corresponding simulation events are established, a simulation road surface that meets the simulation requirements is built, the total simulation duration and the time step of the multibody dynamics model are clearly defined, and after all parameter configurations are completed, the simulation events are run to formally start the collaborative simulation process of the multibody dynamics model and the discrete element model.

[0061] At each time step, the multibody dynamics model takes the system's motion state at the previous moment and the particle forces received from the discrete element model as input conditions. The multibody dynamics software solves the multibody dynamics equations to accurately calculate the new position and velocity data of all moving parts at the time step set by the multibody dynamics model.

[0062] Subsequently, the coupled simulation interface sends the new position and velocity data of the moving parts calculated by the multibody dynamics model to the discrete element model in real time, completing the transfer of motion data between the two models. After receiving the updated geometric position of the moving parts, the discrete element model performs detailed calculations on the particle motion state within a smaller time step. During this process, the position of the moving parts changes in real time within the discrete element model through linear interpolation, ensuring that the interaction behaviors such as collisions and contact between particles and moving parts can be simulated.

[0063] Afterwards, the discrete element model completes the calculations for the previous simulation time step, statistically calculates the cumulative impact force and torque generated by all particles on each coupled geometry, and then feeds these force and torque data back to the multibody dynamics model in real time through the coupled simulation interface. After receiving the particle force and torque data from the discrete element model, the multibody dynamics model uses it as an external load and applies it to the solution of the multibody dynamics equations at the current simulation time step. Then it enters the next iteration loop, repeating all the above operations to continuously advance the simulation process.

[0064] Therefore, according to the embodiments of this application, the multibody dynamics model and the discrete element model are jointly invoked and executed through a coupled simulation interface. During the simulation, the multibody dynamics model outputs tire motion-related data, and the discrete element model outputs the interaction data between the stone particles and the tire. This achieves a refined joint simulation of the interaction behavior between the tire and the particle road surface, which can realistically reflect the dynamic coupling relationship between tire motion and particle force, and effectively improve the accuracy and completeness of the simulation results.

[0065] In step S104, the vehicle stone impact assessment result is generated based on the vehicle load data during the simulation action execution.

[0066] Among them, the vehicle load data is the motion data related to the stone impact of the vehicle collected in real time during the co-simulation of the multibody dynamics model and the discrete element model; the vehicle stone impact assessment result is a comprehensive conclusion drawn from the vehicle load data collected during the simulation, combined with the assessment and analysis model, after data analysis and judgment.

[0067] It is understood that, in the process of co-simulation execution of the multibody dynamics model and the discrete element model, the embodiments of this application collect vehicle load data in real time, combine it with the preset analysis model, analyze and judge the collected load data, and finally generate the vehicle stone impact assessment result. The force and motion response of the vehicle components under the stone impact condition are obtained, realizing a fine assessment of the vehicle stone impact condition. It truly reflects the actual force state and stone impact resistance performance of the vehicle components under the stone impact scenario, which greatly reduces the test cost and shortens the evaluation cycle. At the same time, the simulation conditions can be flexibly adjusted and the evaluation analysis can be repeated to provide a reliable evaluation basis for the structural design optimization of vehicle tires and related components, and ensure the safety and reliability of vehicle driving.

[0068] Specifically, during the collaborative simulation of the multibody dynamics model and the discrete element model, various vehicle load data are collected in real time. The interaction forces and torques between the stone particles, vehicle tires, and related moving parts output by the discrete element model are obtained. Simultaneously, the motion state data such as displacement, velocity, and acceleration of the tires and vehicle body moving parts output by the multibody dynamics model are collected. Invalid data and abnormal data are removed from all collected load data. Then, the processed vehicle load data is substituted into the analysis model. Combined with the simulation parameters of the stone impact condition, the rationality of the force on the vehicle parts and the structural stone impact resistance are quantitatively analyzed and comprehensively judged. Finally, the analysis results are integrated to generate the vehicle stone impact assessment result.

[0069] Furthermore, in the embodiments of this application, generating a car stone impact assessment result based on the car load data during the execution of the simulated action includes: extracting the load data and time-domain curve of each moving part from the car load data; calculating the impact force and wear amount of the car impacting the stone particles based on the load data and time-domain curve of each moving part; and generating the car stone impact assessment result based on the impact force and wear amount.

[0070] Among them, the load data are various mechanical and kinematic data related to the car hitting the stone during the simulation process; the time domain curve is a curve showing the change of the load data of each moving part with the simulation time; the impact force is the instantaneous force generated when the moving parts of the car collide with the stone particles in the simulation; and the wear amount is the amount of material loss on the surface of the parts due to wear after long-term contact, collision and friction between the moving parts of the car and the stone particles.

[0071] It is understood that the embodiments of this application rely on the vehicle load data obtained during the collaborative simulation process to extract the load data and time-domain variation curves corresponding to each moving part. Then, based on these data, the impact force and wear of the parts generated by the vehicle hitting the stone particles are calculated. Finally, the impact force and wear are combined to form a complete vehicle stone impact assessment result, which can quantify the force characteristics and wear of each part of the vehicle under stone impact conditions, reflect the force change law and wear degree of the parts under continuous impact, realize the evaluation of the impact of stone impact, and effectively improve the objectivity and accuracy of the assessment results.

[0072] Specifically, after the co-simulation of the multibody dynamics model and the discrete element model is completed, the results of the multibody dynamics model are analyzed. The load-time domain curves corresponding to each component are extracted from the coupled data fed back from the discrete element model to the multibody dynamics model. The maximum load value of each component is identified through curve analysis. Simultaneously, the static load borne by each component under full load conditions in a stationary vehicle state is calculated using dimensionless parameters. The calculation expression for the dimensionless parameters is as follows: K=F / Fw, Where K represents a dimensionless parameter, F represents the maximum load on the component under the stone impact condition, and Fw represents the reference static load borne by the component when the vehicle is stationary and fully loaded.

[0073] Subsequently, in the discrete element model post-processing module, the surface model of each moving part of the car is divided into a uniform grid. The absolute wear distribution of each grid cell is presented through visualization processing, and a wear location distribution cloud map is generated to identify the weak areas of each part that are most susceptible to stone impact wear. At the same time, the total wear of each part is calculated over the entire simulation time. The wear of different parts such as the oil pan, fuel tank and control arm is compared, and the stone impact wear risk level of each part is ranked.

[0074] Finally, the instantaneous vehicle speed and suspension travel data output by the multibody dynamics model, and the instantaneous impact force and wear data output by the discrete element model are extracted. These data are aligned and integrated on the same time axis to plot the correlation curve between vehicle state and impact. Thus, in this embodiment, during the collaborative simulation execution of the multibody dynamics model and the discrete element model, vehicle load data is collected in real time. Combined with a preset analysis model, the collected load data is analyzed and judged, ultimately generating a vehicle stone impact assessment result. This obtains the force and motion response of vehicle components under stone impact conditions, achieving a precise assessment of vehicle stone impact conditions. It realistically reflects the actual force state and stone impact resistance performance of vehicle components in stone impact scenarios, significantly reducing test costs and shortening the evaluation cycle. Furthermore, the simulation conditions can be flexibly adjusted, and repeated evaluation and analysis can provide a reliable evaluation basis for optimizing the structural design of vehicle tires and related components, ensuring the safety and reliability of vehicle operation.

[0075] To better understand the solution of this application, the following specific embodiment describes the vehicle stone impact dynamic simulation and evaluation method or execution process of this application, as follows: Figure 2 As shown: Phase 1: Preliminary preparation and problem definition.

[0076] System motion parameters include vehicle speed, suspension characteristics, and tire type; particle parameters include gravel size distribution, material density, and geometry; interaction parameters include the coefficient of friction and coefficient of restitution between the gravel and the tire / chassis.

[0077] Phase Two: Independent Model Building

[0078] This stage requires the creation of independent, runnable simulation models in MotionSolve (multibody dynamics model) and EDEM (discrete element model).

[0079] MotionSolve multibody dynamics model establishment: (1) Geometric processing: Import the CATIA model containing key components such as tires, suspension, and chassis.

[0080] (2) Multibody system definition: Define the geometry as a rigid body or a flexible body, and establish a complete vehicle multibody system model through the connection of hinge pairs, constraints, spring-damping units, etc.

[0081] (3) Select MF (Magic Formula) tire in the tire property file to ensure that the calculation is correct.

[0082] (4) After modeling is completed, the model is debugged to ensure that the vehicle is in a loaded or fully loaded state.

[0083] Establishment of EDEM discrete element model: (1) Material and Contact Model Definition: Create a stone material and define intrinsic properties such as density, Poisson's ratio, and shear modulus. Select and calibrate the Oka wear model contact model, and set the coefficient of restitution and static / dynamic friction coefficients for stone-stone and stone-steel components.

[0084] (2) Particle Factory and Static Geometry Definition: Set the road surface geometry as a fixed plane or complex curved surface. Set up a particle factory on the road surface in front of the tires, defining stone generation rules such as rate, particle size distribution, and initial velocity. Run the EDEM separately to quickly generate particles, filling the road surface with gravel. After generation, export the EDEM model without retaining time, obtaining an EDEM discrete element model with a gravel road in the initial state. If the number of particles is too large, use a dynamic domain for particle generation. Create a box for the road surface model, with the shape of the box being the road surface shape. Quickly generate particles within this area to improve simulation speed.

[0085] (3) Simulation parameter settings: Set the EDEM solution time step, which is 20% of the Ruili time step, and the mesh size, etc.

[0086] Phase 3: Coupling interface configuration.

[0087] (1) Interface activation: First activate the EDEM coupling communicator plugin to receive MotionSolve messages.

[0088] (2) Geometry and Data Mapping: MotionSolve Mapping to EDEM: In MotionSolve, select to create an EDEM subsystem, and transmit all moving parts in the MotionSolve model to the EDEM in real time through the coupling interface. In the EDEM, these geometries are no longer massless virtual walls, but are defined as "coupled geometries". The position and orientation of the "coupled geometries" at each moment will be driven by MotionSolve.

[0089] (3) Data exchange variable definition: The data sent by MotionSolve: the translational displacement, velocity, and acceleration of each coupled geometry in the global coordinate system, as well as the rotational Euler angle, angular velocity, and angular acceleration.

[0090] (4) Data sent by EDEM: At each calculation time step, EDEM detects all particles in contact with the "coupled geometry", calculates the total force and torque exerted on the geometry, and feeds back the resultant force vector and resultant torque vector to the corresponding component in MotionSolve in real time through the interface.

[0091] (5) Time Step Synchronization Setting: This is crucial for ensuring simulation stability and accuracy. A master-slave solver setup is required. Typically, MotionSolve is the master solver with a relatively large time step (e.g., 1e-3 seconds). EDEM acts as the slave solver, with its smaller time step (e.g., 1e-5 seconds, typically 20% of the time step) establishing a multiple relationship with MotionSolve's larger time step. The coupling interface is responsible for collecting the average or cumulative force calculated by EDEM within each MotionSolve step and applying it to the next solution step of MotionSolve, while simultaneously sending the new position calculated by MotionSolve to EDEM. This process repeats continuously.

[0092] Phase 4: Collaborative solution computation.

[0093] MotionSolve creates simulation events, simulates road surfaces, sets simulation duration and time steps, and then starts co-simulation by running the event.

[0094] (1) Iterative solution loop: Step A: At time step t, MotionSolve solves the multibody dynamics equations based on the system's state at the previous moment and the particle forces received from the EDEM (initial time is 0), and calculates the new positions and velocities of all components at time t+Δt_m (MotionSolve step size).

[0095] Step B: The coupling interface sends the new position / velocity data of the moving parts calculated by MotionSolve to EDEM.

[0096] Step C: After receiving the updated geometric position, the EDEM performs particle calculations within it for a duration of Δt_m with a smaller step size Δt_d. During this period, the position of the moving parts changes linearly within the EDEM, and particles collide with the moving parts.

[0097] Step D: EDEM calculates the cumulative impact force and torque of all particles on each coupled geometry within the time period Δt_m.

[0098] Step E: The coupling interface sends the force / torque data calculated by EDEM back to MotionSolve.

[0099] Step F: MotionSolve uses the received particle force as an external load and applies it to the dynamic calculation at time t+Δt_m, starting the next loop, i.e., returning to step A.

[0100] (2) The simulation running time is controlled by the time setting of MotionSolve, and the simulation ends when the set time is reached.

[0101] Phase 5: Post-processing and Result Analysis MotionSolve Result Analysis: From the coupled data fed back to MotionSolve by EDEM, the time-domain curve of the load for each component is extracted, and its maximum value F is identified. A reference static force is defined. When the vehicle is stationary, the static load of this component under full load is Fw. The dimensionless K=F / Fw is used to quantify the severity of the impact load relative to the static load.

[0102] EDEM Result Analysis: Wear Location Distribution Cloud Map: In EDEM post-processing, the component surface model is divided into meshes. The absolute wear distribution of each mesh element is visualized and statistically analyzed, directly identifying the weakest areas most susceptible to stone impacts. Risk Ranking of Wear Components During Simulation: By comparing the wear amounts of components such as the oil pan, oil tank, and control arm, the risk levels are ranked to provide a basis for protection priorities. Vehicle condition and impact correlation curve: The instantaneous vehicle speed v and suspension travel s output by MotionSolve are aligned and analyzed with the instantaneous impact force F and wear amount output by EDEM on the same time axis. This reveals whether stronger stone impact damage is accompanied by specific vehicle speeds or large suspension movements, providing an auxiliary evaluation. In summary, the vehicle stone impact dynamic simulation and evaluation method proposed in this application collects vehicle data and road surface data containing stone particle data. Based on the vehicle data, a multi-body dynamics model of the vehicle is constructed. A discrete element model is built using the road surface data, and stone particle generation rules are set to generate stone particles. The multi-body dynamics model and the discrete element model are connected to a coupled simulation interface. Through the interface, the multi-body dynamics model and the discrete element model are called to perform collaborative simulation. During the simulation, the multi-body dynamics model outputs tire motion data, and the discrete element model outputs the interaction force of stone particles on the tire. Finally, based on the vehicle load data generated during the simulation, a vehicle stone impact evaluation result is generated. This method can realistically reproduce the dynamic interaction process between the tire and stone particles, capture the correlation between tire motion state and stone force, and comprehensively reflect the stress and wear characteristics and stone impact resistance performance of various vehicle components under stone impact conditions. It enables flexible adjustment of vehicle parameters and road stone distribution simulation when the vehicle is driving on a road containing stone particles. Repeated simulation analysis significantly reduces R&D costs, shortens the R&D cycle, improves testing efficiency and accuracy, and ensures vehicle driving safety and reliability.

[0103] Next, with reference to the accompanying drawings, the vehicle stone impact dynamic simulation and evaluation device proposed according to the embodiments of this application is described.

[0104] Figure 3 This is a block diagram of the vehicle stone impact dynamic simulation and evaluation device according to an embodiment of this application.

[0105] like Figure 3 As shown, the vehicle stone impact dynamic simulation and evaluation device includes: acquisition module 301, establishment module 302, output module 303 and generation module 304.

[0106] The system comprises the following modules: Acquisition module 301, which acquires vehicle data and road surface data, including gravel particle data; Establishment module 302, which establishes a multibody dynamics model of the vehicle based on the vehicle data and a discrete element model based on the road surface data, wherein the discrete element model has rules for generating gravel particles and generates gravel particles based on these rules; Output module 303, which connects the multibody dynamics model and the discrete element model to a coupled simulation interface, and executes simulation actions by calling the multibody dynamics model and the discrete element model through the coupled simulation interface, outputting tire motion data based on the multibody dynamics model and outputting the interaction force of gravel particles on the tire based on the discrete element model; and Generation module 304, which generates a vehicle stone impact assessment result based on vehicle load data during the execution of the simulation actions.

[0107] Furthermore, module 302 is used to: extract tire geometry data, suspension geometry data, and chassis geometry data from the vehicle data; build a vehicle model based on the tire geometry data, suspension geometry data, and chassis geometry data; set tire attributes and vehicle load states in the vehicle model; and build a multibody dynamics model based on the vehicle model, tire attributes, and load states.

[0108] Furthermore, module 302 is used to: extract gravel particle data, road surface geometry data, and interaction data from the road surface data; establish a road surface model based on the gravel particle data and road surface geometry data; determine the contact model between the vehicle and the gravel particles based on the interaction data; and generate a discrete element model based on the road surface model and the contact model.

[0109] Furthermore, the output module 303 is used to: activate the coupling simulation interface of the coupling communicator plug-in; and enable all moving parts in the multibody dynamics model to communicate with the discrete element model through the coupling simulation interface, so as to realize bidirectional data exchange between all moving parts and the discrete element model.

[0110] Furthermore, the output module 303 is used to: input the tire motion data of the previous simulation time step and the interaction force of the discrete element model of the previous simulation time step into the multibody dynamics model at the current simulation time step, and calculate the tire motion data of all moving parts at the current simulation time step through the multibody dynamics model; send the tire motion data of the current simulation time step to the discrete element model through the coupling simulation interface, and calculate the interaction force of the current simulation time step through the discrete element model; and stop the simulation action until the current simulation time step reaches the stop time step.

[0111] Furthermore, the generation module 304 is used to: extract the load data and time-domain curve of each moving part from the vehicle load data; calculate the impact force and wear amount of the vehicle impacting the stone particles based on the load data and time-domain curve of each moving part; and generate the vehicle stone impact assessment result based on the impact force and wear amount.

[0112] It should be noted that the foregoing explanation of the embodiment of the dynamic simulation and evaluation method for automobile stone impact also applies to the dynamic simulation and evaluation device for automobile stone impact in this embodiment, and will not be repeated here.

[0113] The vehicle stone impact dynamic simulation and evaluation device proposed in this application collects vehicle data and road surface data containing stone particle data. Based on the vehicle data, a multi-body dynamics model of the vehicle is constructed. A discrete element model is built by combining the road surface data, and stone particle generation rules are set to generate stone particles. The multi-body dynamics model and the discrete element model are connected to a coupled simulation interface. Through the interface, the multi-body dynamics model and the discrete element model are called to perform collaborative simulation. During the simulation, the multi-body dynamics model outputs tire motion data, and the discrete element model outputs the interaction force of stone particles on the tire. Finally, based on the vehicle load data generated during the simulation, a vehicle stone impact evaluation result is generated. This device can realistically reproduce the dynamic interaction process between the tire and stone particles, capture the correlation between the tire motion state and the stone force, and comprehensively reflect the stress and wear characteristics and stone impact resistance performance of various vehicle components under stone impact conditions. It enables flexible adjustment of vehicle parameters and road stone distribution simulation when the vehicle is driving on a road containing stone particles. Repeated simulation analysis significantly reduces R&D costs, shortens the R&D cycle, improves testing efficiency and accuracy, and ensures vehicle driving safety and reliability.

[0114] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 401, the processor 402, and the computer program stored on the memory 401 and capable of running on the processor 402.

[0115] When the processor 402 executes the program, it implements the electronic device stone impact dynamic simulation and evaluation method provided in the above embodiments.

[0116] Furthermore, electronic devices also include: Communication interface 403 is used for communication between memory 401 and processor 402.

[0117] The memory 401 is used to store computer programs that can run on the processor 402.

[0118] The memory 401 may include high-speed RAM (Random Access Memory) memory, and may also include non-volatile memory, such as at least one disk storage.

[0119] If the memory 401, processor 402, and communication interface 403 are implemented independently, then the communication interface 403, memory 401, and processor 402 can be interconnected via a bus to complete communication between them. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0120] Optionally, in a specific implementation, if the memory 401, processor 402, and communication interface 403 are integrated on a single chip, then the memory 401, processor 402, and communication interface 403 can communicate with each other through an internal interface.

[0121] Processor 402 may be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of this application.

[0122] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for dynamic simulation and evaluation of vehicle stone impact.

[0123] This application also provides a computer program product, including a computer program or instructions, characterized in that, when the computer program or instructions are executed, the above-mentioned method for dynamic simulation and evaluation of car stone impact is implemented.

[0124] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0125] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0126] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0127] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (FPGAs), field-programmable gate arrays (FPGAs), etc.

[0128] Those skilled in the art will understand that all or part of the steps of the methods implementing the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0129] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for dynamic simulation and evaluation of stone impact on automobiles, characterized in that, Includes the following steps: Acquire vehicle data and road surface data, wherein the road surface data includes gravel particle data; A multibody dynamics model of the vehicle is established based on the vehicle data, and a discrete element model is established based on the road surface data. The discrete element model is equipped with a generation rule for gravel particles, and gravel particles are generated based on the generation rule. The multibody dynamics model and the discrete element model are connected to a coupled simulation interface. The multibody dynamics model and the discrete element model are called through the coupled simulation interface to perform simulation actions. During the execution of the simulation actions, tire motion data is output based on the multibody dynamics model, and the interaction force of the stone particles on the tire is output based on the discrete element model. The vehicle stone impact assessment result is generated based on the vehicle load data during the execution of the simulation action.

2. The method for dynamic simulation and evaluation of automobile stone impact according to claim 1, characterized in that, The step of establishing a multibody dynamics model of the vehicle based on the vehicle data includes: Extract tire geometry data, suspension geometry data, and chassis geometry data from the vehicle data; A vehicle model is established based on the tire geometry data, the suspension geometry data, and the chassis geometry data, and the tire attributes and vehicle load status in the vehicle model are set. A multibody dynamics model is established based on the vehicle model, the tire properties, and the load state.

3. The method for dynamic simulation and evaluation of automobile stone impact according to claim 1, characterized in that, The step of establishing a discrete element model based on the road surface data includes: Extract the gravel particle data, road geometry data, and interaction data from the road surface data; The road surface model is established based on the aggregate particle data and the road surface geometry data; A contact model between the car and the stone particles was determined based on the interaction data. The discrete element model is generated based on the road surface model and the contact model.

4. The method for dynamic simulation and evaluation of stone impact on automobiles according to claim 1, characterized in that, The step of connecting the multibody dynamics model and the discrete element model to the coupled simulation interface includes: Activate the coupling simulation interface of the coupling communicator plugin; All moving parts in the multibody dynamics model communicate with the discrete element model through the coupled simulation interface to achieve bidirectional data exchange between all moving parts and the discrete element model.

5. The method for dynamic simulation and evaluation of stone impact on automobiles according to claim 1, characterized in that, The step of calling the multibody dynamics model and the discrete element model through the coupled simulation interface to perform simulation actions includes: At the current simulation time step, the tire motion data from the previous simulation time step and the interaction forces of the discrete element model from the previous simulation time step are input into the multibody dynamics model, and the tire motion data of all moving parts at the current simulation time step are calculated through the multibody dynamics model. The tire motion data of the current simulation time step is sent to the discrete element model through the coupled simulation interface, and the interaction force of the current simulation time step is calculated through the discrete element model. The simulation continues until the current simulation time step reaches the stop time step, at which point the simulation action stops.

6. The method for dynamic simulation and evaluation of automobile stone impact according to claim 1, characterized in that, The step of generating a vehicle stone impact assessment result based on vehicle load data during the simulation execution includes: Extract the load data and time-domain curves of each moving component from the vehicle load data; Based on the load data and time-domain curves of each moving component, the impact force and wear amount of the vehicle impacting the stone particles are calculated. The vehicle stone impact assessment results are generated based on the impact force and wear amount.

7. A dynamic simulation and evaluation device for automobile stone impact, characterized in that, include: The acquisition module is used to acquire vehicle data and road surface data, wherein the road surface data includes gravel particle data; A module is established to build a multibody dynamics model of the vehicle based on the vehicle data and a discrete element model based on the road surface data. The discrete element model is configured with rules for the generation of gravel particles, and gravel particles are generated based on the rules. The output module is used to connect the multibody dynamics model and the discrete element model to the coupled simulation interface, and call the multibody dynamics model and the discrete element model to perform simulation actions through the coupled simulation interface. During the execution of the simulation actions, the tire motion data is output based on the multibody dynamics model, and the interaction force of the stone particles on the tire is output based on the discrete element model. The generation module is used to generate a vehicle stone impact assessment result based on the vehicle load data during the execution of the simulation action.

8. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the vehicle stone impact dynamic simulation and evaluation method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed, they implement the dynamic simulation and evaluation method for automobile stone impact as described in any one of claims 1-6.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed, they implement the dynamic simulation and evaluation method for automobile stone impact as described in any one of claims 1-6.

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