Seat performance determination method, apparatus, and storage medium

Abstract

The application discloses a seat performance determination method and device and a storage medium, relates to the technical field of automobile seat design and testing, and comprises the following steps: acquiring a limit motion trajectory of an occupant, the limit motion trajectory being a motion path that causes the greatest risk of failure of a soft structure of a seat; performing simulation analysis and physical testing based on the limit motion trajectory, and obtaining simulation results and testing results; and determining seat performance based on the simulation results and the testing results. Through the limit motion trajectory as a unified reference, performance determination is performed in combination with simulation and physical testing results, the problem that evaluation scenarios do not match actual harsh scenarios is solved, and accurate determination of seat performance is realized.

Description

Technical Field

[0001] This application relates to the field of automotive seat design and testing technology, and in particular to seat performance determination methods, devices and storage media. Background Technology

[0002] Currently, in the development of automotive seats, comfort, durability, and reliability are the core evaluation indicators for seat performance.

[0003] Currently, the evaluation of seat performance for getting in and out of vehicles is mainly divided into two categories: virtual evaluation based on CAE simulation analysis and physical evaluation based on physical prototypes. However, in existing evaluation methods, the scenarios used in CAE simulation and physical evaluation do not match the actual usage scenarios, resulting in a large deviation between simulation results and actual test results, making it impossible to accurately predict the failure risk of the seat during actual long-term use. Summary of the Invention

[0004] The main objective of this application is to provide a method, apparatus, and storage medium for determining seat performance, aiming to solve the technical problem of low accuracy in current seat performance determination due to the mismatch between the current scenario and the actual scenario.

[0005] To achieve the above objectives, this application proposes a method for determining seat performance, the method comprising: The extreme motion trajectory of the occupant is obtained, which is the motion path that poses the greatest risk of failure to the soft structure of the vehicle seat; Based on the extreme motion trajectory, simulation analysis and physical testing were performed respectively to obtain simulation results and test results; The seat performance is determined based on the simulation results and the test results.

[0006] In one embodiment, the step of obtaining the occupant's extreme motion trajectory includes: Collect kinematic parameters from multiple occupants; Based on the aforementioned kinematic parameters, motion trajectories that result in the maximum stress or deformation of the seat's soft structure are selected. The aforementioned trajectory is taken as the extreme trajectory of motion.

[0007] In one embodiment, the step of collecting kinematic parameters of multiple occupants includes: Establish a three-dimensional coordinate system with the vertex of the seat back as the origin; The coordinates of the hip movement path, movement speed, compression angle, and continuous compression time of multiple occupants were collected in the three-dimensional coordinate system. The kinematic parameters of multiple occupants are determined based on the coordinates of the hip movement path, the movement speed, the compression angle, and the duration of continuous compression.

[0008] In one embodiment, the step of determining the seat performance based on the simulation results and the test results includes: Determine the deviation data between the simulation results and the test results. The deviation data includes the target compressive force deviation, the target deformation deviation, and the contact state deviation between the soft structure of the seat and the seat frame. Seat performance is determined based on the aforementioned deviation data.

[0009] In one embodiment, the step of determining seat performance based on the deviation data includes: The contact state deviation is compared with a preset contact threshold, and the rebound recovery rate of the seat soft structure under extreme motion trajectory is obtained; When the contact state deviation exceeds the preset contact threshold and the rebound recovery rate is lower than the preset recovery rate threshold, it is determined that the soft structure of the seat is at risk of being caught by the seat frame, and the seat performance is determined to be unqualified.

[0010] In one embodiment, after the step of comparing the contact state deviation with a preset contact threshold, the method further includes: When the contact state deviation does not exceed the preset contact threshold, the weighted combined error of the target extrusion pressure deviation and the target deformation deviation is calculated; When the weighted comprehensive error is within the preset error allowable range, it is determined that the accuracy of the simulation model meets the requirements, and the performance of the seat is confirmed to be qualified.

[0011] In one embodiment, after the step of calculating the weighted combined error of the target extrusion pressure deviation and the target deformation deviation when the contact state deviation does not exceed the preset contact threshold, the method further includes: When the weighted composite error exceeds the preset error allowable range, the simulation model is determined to be distorted, and the relative error between the first deformation in the simulation result and the second deformation in the test result is calculated. When the relative error exceeds a first preset range, the material parameters in the simulation analysis are corrected according to the test results to obtain a corrected simulation analysis model. The material parameters include the sponge's elastic modulus, Poisson's ratio, or contact friction coefficient. The seat structure was optimized based on the revised simulation analysis model.

[0012] In one embodiment, the step of performing simulation analysis and physical testing based on the extreme motion trajectory to obtain simulation results and test results includes: A finite element simulation model of the seat is constructed, and the kinematic parameters of the extreme motion trajectory are input into the finite element simulation model as boundary conditions for dynamic explicit solution. The stress cloud map, strain cloud map and contact force data between the soft structure of the seat and the seat frame during the motion process are output. The stress cloud diagram, the strain cloud diagram, and the contact force data between the soft structure of the seat and the seat frame are used as simulation results; A physical testing platform was built, and a robotic arm or a simulated dummy was controlled to perform repetitive movements on the physical testing platform according to the extreme motion trajectory, and real-time pressure distribution data and surface deformation data of the soft structure of the seat were collected. The pressure distribution data and the surface deformation data are used as test results.

[0013] Furthermore, to achieve the above objectives, this application also proposes a seat performance determination device, which includes: The acquisition module is used to acquire the extreme motion trajectory of the occupant, which is the motion path that poses the greatest risk of failure to the soft structure of the vehicle seat; The testing module is used to perform simulation analysis and physical testing based on the extreme motion trajectory to obtain simulation results and test results. The determination module is used to determine the seat performance based on the simulation results and the test results.

[0014] In addition, to achieve the above objectives, this application also proposes a seat performance determination device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the seat performance determination method as described above.

[0015] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and which, when executed by a processor, implements the steps of the seat performance determination method described above.

[0016] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the seat performance determination method described above.

[0017] This application proposes one or more technical solutions to obtain the occupant's extreme motion trajectory, which is the motion path that poses the greatest risk of failure to the soft structure of the seat. Based on the extreme motion trajectory, simulation analysis and physical testing are performed to obtain simulation results and test results. The seat performance is determined based on the simulation results and the test results. By using the extreme motion trajectory as a unified benchmark and combining simulation and physical test results for performance judgment, the problem of mismatch between the evaluation scenario and actual harsh scenarios is solved, and the accurate determination of seat performance is achieved. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating an embodiment of the method for determining seat performance in this application. Figure 2 This is a flowchart illustrating Embodiment 2 of the method for determining seat performance in this application. Figure 3 This is a flowchart illustrating Embodiment 3 of the method for determining seat performance in this application. Figure 4 A simplified flowchart is provided for one embodiment of the seat performance determination method of this application; Figure 5 This is a schematic diagram of the module structure of the seat performance determination device according to an embodiment of this application; Figure 6 This is a schematic diagram of the device structure of the hardware operating environment involved in the seat performance determination method in this application embodiment.

[0021] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0024] The main solution of this application embodiment is: to obtain the extreme motion trajectory of the occupant, which is the motion path that poses the greatest risk of failure to the soft structure of the vehicle seat; to perform simulation analysis and physical testing based on the extreme motion trajectory, and to obtain simulation results and test results; and to determine the seat performance based on the simulation results and the test results.

[0025] Due to the lack of clear understanding of the extreme vehicle trajectory during the seat structure design stage, existing technologies cannot accurately determine the stress limit and deformation risk of the seat back side wings, resulting in unreasonable structural designs, such as insufficient foam thickness and improper frame position design. Problems such as the seat foam being squeezed to the frame and unable to rebound are only discovered in the subsequent physical verification stage, requiring repeated modifications to the seat structure, which not only prolongs the development cycle but also significantly increases development costs.

[0026] This application provides a solution that identifies the driver's extreme motion trajectory and uses it as a unified evaluation standard for simulation and physical performance determination. Then, simulation analysis verifies the rationality of the seat structure design, and physical prototype evaluation verifies the seat's performance in actual use. The results are compared with the simulation results, and the simulation model and seat structure are adjusted based on the comparison results to form a closed-loop optimization, ensuring that the seat can still meet the usage requirements under the most extreme scenarios.

[0027] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or seat performance determination device capable of performing the above functions. The following description uses a seat performance determination device as an example to illustrate this embodiment and the subsequent embodiments.

[0028] Based on this, embodiments of this application provide a method for determining seat performance, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the seat performance determination method of this application.

[0029] In this embodiment, the method for determining seat performance includes steps S10 to S30: Step S10: Obtain the occupant's extreme motion trajectory, which is the motion path that poses the greatest risk of failure to the soft structure of the vehicle seat.

[0030] It should be noted that extreme motion trajectories refer to motion scenarios in which occupants exert maximum pressure, shearing, or stretching on multiple parts of the seat during getting on and off the vehicle, causing the seat foam to fail to rebound and become dented. The risk of failure of the soft structure of the vehicle seat is greatest in these scenarios, i.e., the seat foam fails to rebound and becomes dented.

[0031] It's important to understand that conventional vehicle entry and exit assessments often use standard, universal trajectories, which may not cover the extreme conditions that lead to seat damage in real-world use. This step, by identifying the "extreme motion trajectory" with the highest failure risk, ensures that the assessment scenario truly reflects the worst-case conditions the seat might face in actual use. For example, for the seat back wing, the extreme motion trajectory typically corresponds to the path where the occupant's buttocks exert maximum pressure or snagging on the wing during entry and exit. By using this extreme trajectory as a unified benchmark, potential failure risks that cannot be detected under conventional trajectories can be exposed, thereby improving the relevance and effectiveness of the assessment.

[0032] Step S20: Based on the extreme motion trajectory, perform simulation analysis and physical testing respectively to obtain simulation results and test results.

[0033] It should be noted that by employing a parallel testing strategy, the same extreme motion trajectory is input into both a virtual simulation environment and a physical testing environment. On the simulation analysis side, computer-aided engineering (CAE) software is used to simulate the stress and deformation response of the seat's soft structure under this trajectory; on the physical testing side, a robotic arm or simulated dummy is used to reproduce the trajectory, collecting physical response data from a real seat. This "virtual-real parallel" approach leverages the efficiency of simulation analysis for prediction while utilizing the realism of physical testing for verification, providing a comparable data foundation for subsequent model correction.

[0034] In one feasible implementation, step S20 may include steps A11 to A14: Step A11: Construct a finite element simulation model of the seat, input the kinematic parameters of the extreme motion trajectory as boundary conditions into the finite element simulation model for dynamic explicit solution, and output the stress cloud map, strain cloud map and contact force data between the soft structure of the seat and the seat frame during the motion process. It should be noted that the finite element simulation model of the seat is a digital twin of the seat. The core lies in the mesh generation and material property definition of the seat's soft structures, such as foam and filling materials. In practice, Abaqus software can be used to create a 3D simulation model of the seat, with the foam's elastic modulus at 0.3 MPa, Poisson's ratio at 0.4, resilience at 88%, and contact friction coefficients at 0.3 (buttocks and skin) and 0.2 (foam and frame). The kinematic parameters from the extreme motion trajectory are input for simulation, and the output includes stress contour maps, strain contour maps, and contact force data between the seat's soft structures and the seat frame.

[0035] Specifically, the motion of the simulated human body is defined as a displacement boundary condition. Its spatial trajectory is set according to the motion path coordinates, its loading rate is set according to the motion velocity, its cutting direction is set according to the compression angle, and the duration of the load step is set according to the continuous compression time. The dynamic explicit solution employs an explicit integration algorithm, and the time step must meet a stability condition (typically 0.01s to 0.05s) to ensure the stability of the calculation under large deformation and complex contact conditions. During the solution process, the simulation software calculates the displacement, velocity, and acceleration of each node within each time increment step, thereby deriving the strain and stress of the element, and using a contact algorithm to determine the contact state and contact force of each contact pair.

[0036] The stress cloud map visually displays the stress distribution in different regions of the seat's soft structure under extreme motion trajectories. Stress concentration areas are typically located at the root of the side wings and in areas adjacent to the frame; these areas are critical locations for potential failure. The strain cloud map reflects the degree of deformation of the soft structure, with the maximum strain area corresponding to the maximum deformation node, providing spatial location data for subsequent deformation deviation calculations. Contact force data records the time history curve of the contact force between the seat's soft structure and the seat frame, including the peak value, duration, and trend of the contact force. This data is the core basis for determining contact state deviations. Using the stress cloud map, strain cloud map, and contact force data as simulation results provides a complete virtual prediction dataset for subsequent deviation comparison with physical test results. For example, the final output shows a maximum compressive force of 470N, a maximum deformation of 27mm, and slight contact between the sponge and the frame at the maximum deformation node, with no risk of snagging.

[0037] Step A12: Use the stress cloud diagram, the strain cloud diagram, and the contact force data between the soft structure of the seat and the seat frame as simulation results; In practice, the stress cloud diagram, stress-calibration cloud diagram, and contact force data can be combined to form the final simulation result.

[0038] Step A13: Build a physical testing platform, control a robotic arm or a simulated dummy to perform repetitive movements on the physical testing platform according to the extreme motion trajectory, and collect real-time pressure distribution data and surface deformation data of the soft structure of the seat; In practice, the physical testing platform mainly consists of four components: a test bench, a robotic arm or dummy, a sensor system, and a data acquisition unit. The test bench is used to fix the seat under test and must have sufficient rigidity and stability to prevent vibration or displacement of the bench itself from interfering with the measurement results during testing. The test bench is equipped with a seat mounting interface to adapt to the seat structures of different vehicle models, ensuring that the seat's installation posture during testing is consistent with its actual usage posture in the vehicle.

[0039] Robotic arms or mannequins are the actuators used in physical testing. Robotic arms must possess multi-degree-of-freedom motion control capabilities (at least three-axis linkage) to accurately reproduce the spatial path, velocity, and acceleration characteristics of extreme motion trajectories. The shape and size of the robotic arm's end effector must simulate the geometry of the human buttocks to ensure that the area and distribution of the squeezing action are consistent with actual human contact. Mannequins, on the other hand, use standard human models, whose buttock area's hardness and geometry are closer to the real human body, enabling a more realistic reproduction of the mechanical interactions during getting on and off a vehicle. It should be understood that both robotic arms and mannequins have their advantages: robotic arms offer higher trajectory reproduction accuracy and are suitable for testing scenarios requiring precise control of motion parameters; mannequins provide more realistic mechanical interactions and are suitable for testing scenarios requiring simulation of real human contact behavior. In practical applications, the appropriate actuator can be selected based on the testing objective, or a combination of both can be used.

[0040] In this embodiment, the kinematic parameters of the extreme motion trajectory are converted into a motion control program for the robotic arm or simulated dummy. The control unit drives the actuator to move according to the set parameters. The motion is repeated at least 10 times to ensure the statistical reliability of the test data and eliminate the influence of random factors that may exist in a single test. An appropriate interval time, such as 30 to 60 seconds, needs to be set between each test to allow the soft structure of the seat to fully rebound and recover, avoiding the influence of residual deformation from the previous test on the results of subsequent tests.

[0041] Pressure distribution data is collected through an array of pressure sensors laid on the seat surface. This sensor array can record the pressure distribution in different areas of the seat surface in real time and its changes over time, providing a measured benchmark for subsequent calculation of extrusion force deviation. Surface deformation data is collected through displacement sensors or an optical measurement system, recording the amount of surface deformation and its spatial distribution of the seat's soft structure during the extrusion process. Displacement sensors are suitable for high-precision point measurements and can be installed at key locations on the seat's side wings, such as nodes with the maximum deformation. Optical measurement systems are suitable for full-field deformation measurement and can capture the overall deformation morphology of the seat surface.

[0042] Step A14: Use the pressure distribution data and the surface deformation data as test results.

[0043] Using the aforementioned pressure distribution data and surface deformation data as test results provides a complete set of measured data for subsequent comparison of deviations with simulation results.

[0044] The simulation analysis side obtained predicted data on stress, strain, and contact force in a virtual environment through finite element modeling, boundary condition input, and dynamic explicit solution. The physical testing side obtained measured data on pressure distribution and surface deformation in a real environment through platform construction, trajectory reproduction, and data acquisition. Both used the same extreme motion trajectory as the input benchmark, ensuring the comparability between simulation and test results and laying a solid data foundation for subsequent performance evaluation based on deviation data.

[0045] Step S30: Determine the seat performance based on the simulation results and the test results.

[0046] In practical implementation, after obtaining simulation results and physical test results, the seat performance can be judged based on the deviation data between the two. Unlike existing technologies that only focus on model correction, this embodiment establishes a systematic logic from deviation data to performance judgment: first, it determines whether there is a risk of snagging by checking the contact state deviation and rebound recovery rate. If there is no risk, it further verifies the simulation accuracy by weighted comprehensive error. If the error exceeds the range, it diagnoses model distortion and corrects material parameters to optimize the structure. This hierarchical judgment logic makes the determination of seat performance no longer a simple binary judgment of qualified or unqualified, but a closed-loop mechanism that can accurately identify failure causes, quantify judgment criteria, and trigger model correction and structural optimization when necessary.

[0047] This embodiment provides a method for determining seat performance. It obtains the occupant's extreme motion trajectory, which is the movement path that poses the greatest risk of failure to the seat's soft structure. Based on this extreme motion trajectory, simulation analysis and physical testing are performed to obtain simulation results and test results. Seat performance is determined based on these simulation and test results. By using the extreme motion trajectory as a unified benchmark and combining simulation and physical test results for performance judgment, the method solves the problem of mismatch between the evaluation scenario and actual harsh scenarios, achieving accurate determination of seat performance.

[0048] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 Step S10 includes steps S101 to S103: Step S101: Collect kinematic parameters of multiple occupants.

[0049] In practice, the system first uses motion capture systems, pressure sensors, and other equipment to record a large amount of behavioral data on occupants of different body types and driving habits during their actual vehicle entry and exit. The kinematic parameters include motion path, motion speed, and compressive force. The motion path reflects the change in the contact position between the human body and the seat, the motion speed reflects the rate at which the human body applies load to the seat, and the compressive force directly reflects the load borne by the seat's soft structure.

[0050] In one feasible implementation, step S101 may include steps B11 to B13: Step B11: Establish a three-dimensional coordinate system with the vertex of the seat back as the origin; It should be noted that, regarding the establishment of the three-dimensional coordinate system, this embodiment uses the vertex of the seat back as the origin. Since the vertex of the seat back is the starting reference point for the contact between the buttocks and the side wings during the passenger's getting on and off the vehicle, the coordinate system established with this as the origin can intuitively describe the movement trajectory of the buttocks relative to the seat.

[0051] Step B12: Collect the hip movement path coordinates, movement speed, compression angle, and continuous compression time of multiple occupants in the three-dimensional coordinate system; In this coordinate system, the range of motion in the X-axis direction is typically 50mm to 200mm, the range of motion in the Y-axis direction is 100mm to 300mm, and the range of motion in the Z-axis direction is 150mm to 400mm.

[0052] This coordinate range defines the spatial area where the occupant's hips interact violently with the seat side wing. It should be understood that the above coordinate range is merely exemplary, and the coordinate range may vary for different vehicle models and seat structures, as long as it covers the typical "compression-slip" process that leads to side wing failure.

[0053] It should be noted that the movement speed is typically between 0.3 m / s and 0.8 m / s, preferably set to 0.5 m / s. This parameter range has a clear physical significance: if the movement speed is below 0.3 m / s, the loading process of the human body onto the seat is too slow, closer to static compression, and cannot accurately reflect the inertial effect and material strain rate effect brought about by dynamic compression during getting in and out of the vehicle; if the movement speed is above 0.8 m / s, the effect of the human body on the seat is more inclined to be an instantaneous impact rather than the continuous compression and slippage during getting in and out of the vehicle, which will change the failure mode and cause the determined results to deviate from the actual usage scenario.

[0054] The extrusion angle is usually the angle between 30° and 60° with the side wings of the seat back. This angle range reflects the typical posture of the human hip cutting into the seat side wings. If the angle is too small, the human body mainly slides along the surface of the side wings, and the normal extrusion force component is insufficient, making it difficult to induce the failure mode of the side wings being hooked by the skeleton; if the angle is too large, the human body mainly compresses the side wings in the vertical direction. Although the pressure is large, there is a lack of shear effect brought by lateral sliding, and the most severe failure condition cannot be reproduced either.

[0055] The continuous extrusion time is usually 1 s to 3 s. This time range simulates the process of the occupant's hip staying on the seat side wings and adjusting the sitting posture. If the time is too short, the plastic deformation energy of the sponge cannot be accumulated sufficiently; if the time is too long, it is closer to creep behavior, which does not conform to the transient characteristics of the boarding and alighting actions.

[0056] Step B13: Determine the kinematic parameters of multiple occupants according to the hip movement path coordinates, the movement speed, the extrusion angle, and the continuous extrusion time.

[0057] Through the acquisition and determination of the above parameters, the abstract "limit movement trajectory" is transformed into specific and quantifiable kinematic indicators, providing an accurate input benchmark for subsequent simulation analysis and physical testing, and ensuring the consistency and comparability of the determination results.

[0058] Step S102: Based on the kinematic parameters, screen out the movement trajectories that cause the maximum force or the maximum deformation of the soft structure of the seat.

[0059] Step S103: Take the movement trajectory as the limit movement trajectory.

[0060] It can be understood that the reason for choosing the trajectory with the maximum force or the maximum deformation is that the failure of the soft structure of the seat, such as polyurethane sponge, is usually directly related to overload or excessive deformation. By statistically analyzing a large amount of occupant data and finding the most extreme working conditions, it can ensure that the determination benchmark covers the "worst scenarios" in actual use, thus avoiding the problem of being qualified under normal working conditions but failing under extreme working conditions. The maximum extrusion force of the side wing under this trajectory is 480 N, the maximum deformation is 28 mm, and the contact probability between the sponge and the skeleton is 80%. ​​​​​​​Based on the first embodiment of this application, in the third embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 Step S30 includes steps S301 to S302: Step S301: Determine the deviation data between the simulation results and the test results. The deviation data includes the target extrusion pressure deviation, the target deformation deviation, and the contact state deviation between the seat soft structure and the seat frame.

[0064] It should be noted that the data in the simulation results and test results can be calculated to obtain the deviation between the simulation results and the test results.

[0065] The target compression force deviation reflects the accuracy of the simulation model in simulating the load transfer path. During the compression process of getting in and out of the vehicle, the human load is transferred through the seat surface to the interior of the foam, and then to the frame. If the load transfer path in the simulation does not match the actual path, it will lead to a significant difference between the calculated contact force and the measured value. The target deformation deviation directly reflects the accuracy of the simulation model in simulating the material stiffness characteristics. The soft structure of the seat has significant nonlinear stiffness characteristics. If the stress-strain curve setting in the simulation model is incorrect, it will lead to inconsistencies between the simulated deformation and the measured deformation under the same load. The contact state deviation is a dimension of particular concern in this embodiment, which characterizes whether the soft structure of the seat and the seat frame are in contact simultaneously in the simulation results and the test results. For example, if the foam is squeezed into contact with the frame in the actual test, but the simulation results show that the foam is not in contact with the frame, then the contact state is determined to be inconsistent. This dimension is crucial for identifying the failure cause of "foam snagging on the frame".

[0066] Step S302: Determine seat performance based on the deviation data.

[0067] In practice, the performance of the seat can be determined based on the relationship between the deviation value and the set threshold.

[0068] In one feasible implementation, step S302 may include steps C11-C12: Step C11: Compare the contact state deviation with a preset contact threshold and obtain the rebound recovery rate of the seat soft structure under extreme motion trajectory; It should be noted that this step is the first layer of logic in performance assessment, namely, the assessment of hooking risks.

[0069] If the contact state deviation exceeds the preset contact threshold, it means that there is a significant difference between the simulation and the actual measurement regarding the critical state of whether the soft structure is in contact with the skeleton. This usually indicates that the soft structure was indeed compressed to the point of contact with the skeleton in the actual measurement. At this point, the rebound recovery rate is further obtained, which is the proportion of the seat's soft structure that recovers to its designed shape after the extreme motion trajectory compression ends.

[0070] Step C12: When the contact state deviation exceeds the preset contact threshold and the rebound recovery rate is lower than the preset recovery rate threshold, it is determined that the soft structure of the seat is at risk of being caught by the seat frame, and the seat performance is determined to be unqualified.

[0071] If the rebound recovery rate is lower than the preset recovery rate threshold, such as 95%, it indicates that the soft structure has undergone plastic deformation after contacting the frame and cannot fully rebound, posing a risk of being caught on the frame. Accurately identifying the superposition of the "rigid frame obstruction" and the "plastic deformation" manifestation is a typical failure mode of the soft seat structure during vehicle entry and exit.

[0072] It should be understood that if only the contact state deviation exceeds the threshold without insufficient rebound rate (e.g., rapid rebound after brief compression), it may simply be a prediction error in the simulation model regarding contact behavior, rather than an actual failure. Conversely, if only the rebound rate is insufficient without the contact state deviation exceeding the threshold, it may indicate other failure modes such as material fatigue. Only when both conditions are met simultaneously can a performance failure be determined as caused by snagging risk.

[0073] In one feasible implementation, after step C11, the method further includes: when the contact state deviation does not exceed the preset contact threshold, calculating the weighted comprehensive error of the target extrusion pressure deviation and the target deformation deviation; when the weighted comprehensive error is within the preset error allowable range, determining that the accuracy of the simulation model meets the requirements and confirming that the seat performance is qualified.

[0074] This step is the second layer of logic in performance evaluation, namely accuracy verification. When the contact state deviation does not exceed the preset contact threshold, it indicates that there is no risk of snagging. At this point, it is necessary to further evaluate the overall accuracy of the simulation model.

[0075] The weighted composite error combines the target compressive pressure deviation and the target deformation deviation according to preset weights. For example, the weight of the compressive pressure deviation can be set to 0.4, and the weight of the deformation deviation can be set to 0.6, because deformation has a greater impact on failure determination. When the weighted composite error is within the preset error allowable range, such as within 5%, it indicates that the simulation model can predict the mechanical response of the seat under extreme working conditions well, and the seat performance is confirmed to be qualified. This hierarchical judgment logic first eliminates the most serious risk of snagging, and then verifies the simulation accuracy, avoiding the one-sidedness of a single-dimensional judgment.

[0076] Understandably, if the weighted comprehensive error exceeds the preset error allowable range, it indicates that the simulation model cannot accurately predict the mechanical response of the seat under extreme working conditions. Therefore, when the weighted comprehensive error exceeds the preset error allowable range, the simulation model is determined to be distorted, and the relative error between the first deformation in the simulation result and the second deformation in the test result is calculated. When the relative error exceeds the first preset range, the material parameters in the simulation analysis are corrected according to the test results to obtain a corrected simulation analysis model. The material parameters include the elastic modulus of the sponge, Poisson's ratio, or contact friction coefficient. Based on the corrected simulation analysis model, the seat structure is optimized.

[0077] When the weighted composite error exceeds the preset error allowable range, it indicates a significant deviation between the simulation model and the actual state, resulting in model distortion. In this case, the relative error between the first deformation amount in the simulation results and the second deformation amount in the test results is further calculated to diagnose the degree and direction of the distortion. If the relative error exceeds the first preset range, for example, 10%, the material parameters in the simulation analysis need to be corrected based on the test results.

[0078] Material parameters specifically include the sponge's elastic modulus, Poisson's ratio, or contact friction coefficient. Adjusting the elastic modulus can correct the stiffness response of the simulation model, adjusting the Poisson's ratio can correct the volumetric deformation characteristics of the material under complex stress states, and adjusting the contact friction coefficient can correct the shear force transmission and relative motion trends between interfaces.

[0079] It should be understood that the above material parameters are merely illustrative, and one or more parameters may be adjusted depending on the specific type and direction of the deviation. The revised simulation analysis model can more accurately predict the performance of the seat under extreme conditions. Based on this model, the seat structure can be optimized, such as adjusting the foam thickness, optimizing the frame shape, adjusting the foam density distribution, or adding side support structures. This reduces reliance on physical prototypes in subsequent development processes, shortens the development cycle, and lowers costs.

[0080] By linking risk assessment, accuracy verification, model correction, and structural optimization, a complete closed-loop system for performance determination has been constructed. This makes the determination of seat performance no longer a simple binary judgment, but a systematic process that can accurately identify failure causes, quantify judgment criteria, and trigger model correction and structural optimization when necessary.

[0081] This embodiment determines the deviation data between the simulation results and the test results. The deviation data includes the target compressive force deviation, the target deformation deviation, and the contact state deviation between the soft structure of the seat and the seat frame. Based on the deviation data, the seat performance is determined. By introducing a comprehensive consideration of three dimensions—target compressive force deviation, target deformation deviation, and contact state deviation—the mechanical response of the seat under extreme conditions can be more comprehensively and realistically reproduced. This avoids erroneous evaluations caused by the matching of a single indicator and improves the confidence of the seat performance evaluation.

[0082] In one feasible implementation, for example, during the development of a driver's seat for a compact car, the performance determination method of this embodiment includes the following: 1. Severeest boarding trajectory recognition: 35 drivers with different body types and driving habits were selected. Through motion capture and sensor data collection, the most severe boarding trajectory was screened out: the driver's buttocks slid down the side wing of the seat back from the upper part (coordinates X=100mm, Y=200mm, Z=300mm) to the connection point between the middle and lower parts (coordinates X=150mm, Y=250mm, Z=200mm), with a movement speed of 0.5m / s, a compression angle of 45°, and a continuous compression time of 2s. The maximum compression force of the lower side wing under this trajectory was 480N, the maximum deformation was 28mm, and the probability of contact between the sponge and the frame was 80%.

[0083] 2. CAE Simulation Analysis: A three-dimensional simulation model of the seat was established using Abaqus software. The sponge's elastic modulus was 0.3 MPa, Poisson's ratio was 0.4, resilience was 88%, and the contact friction coefficient was 0.3 (buttocks and skin) and 0.2 (sponge and frame). The worst-case trajectory parameters were input for simulation. The maximum compressive force was 470 N, and the maximum deformation was 27 mm. The sponge and frame made slight contact at the maximum deformation node, with no risk of snagging. The simulation results met the design requirements.

[0084] 3. Physical evaluation: A physical prototype was made, and the side wings of the seat back were tested according to the preset parameters of 0.5m / s movement speed, 45° compression angle and 2s continuous compression time. The maximum compression force was 485N and the maximum deformation was 28.5mm. There was no obvious contact between the sponge and the frame. After compression, it rebounded to the design state in 2.5s without dent. The physical evaluation was qualified.

[0085] 4. Mutual verification and adjustment: Comparing the CAE and physical results, the extrusion pressure deviation is 2.1% and the deformation deviation is 1.8%, which are within the allowable range. The accuracy of the CAE model meets the requirements. No adjustment to the seat structure is required, and the evaluation is qualified.

[0086] 5. Subsequent Applications: The evaluation process and optimization parameters were applied to the mass production of seats for this vehicle model. During subsequent user use, no issues arose with the seat foam failing to rebound or denting. User satisfaction increased by 30%, the development cycle was shortened by 25%, and development costs were reduced by 20%.

[0087] For example, to help understand the implementation flow of the seat performance determination method obtained by combining this embodiment with the above embodiment one, please refer to... Figure 4 , Figure 4A simplified flowchart of a method for determining seat performance is provided, specifically: Phase 1: Scene Recognition and Data Acquisition. Q1: Identify the most severe boarding scenario for occupants. First, through ergonomic analysis or actual observation, identify the motion scenarios that cause maximum compression, shearing, or stretching to the seat side wings during occupant boarding and alighting, ensuring that subsequent analysis targets the conditions where the seat is most prone to failure. Under these most severe scenarios, Q2: Collect specific motion data. This includes the trajectory of the occupant's buttocks relative to the seat (intrusion path), the depth of intrusion (intrusion amount), and the specific pressure distribution on the seat side wings during this process. This data serves as the input source for subsequent physical testing and simulation analysis. Phase 2: Bidirectional Parallel Analysis. A parallel approach using "physical testing" and "CAE simulation" is employed for mutual verification. Physical testing includes: Q31: Setting the motion program for the robotic arm's physical evaluation: Based on the "intrusion path, intrusion amount, and pressure values" collected in Phase 1, a motion control program for the automated robotic arm is written. This program aims to allow the robotic arm to accurately reproduce the driver's most severe boarding action in a laboratory environment. Q41: Implement passenger and alighting evaluation using this program: Start the robotic arm and perform repeated passenger and alighting simulation tests on the physical sample of the seat according to the set program. Q32: CAE simulation includes: Establishing a CAE simulation model: Constructing a high-precision finite element model including the seat frame, foam (soft structure), and cover. Q42: CAE analysis of sponge deformation: Input the collected motion data as boundary conditions into the model, perform nonlinear dynamic analysis, and calculate the deformation and stress distribution of the soft structure (sponge) of the seat during the stress process. Third stage: Judgment and verification, Q51: After the physical test, check whether the deformation of the seat meets the requirements, such as whether there is permanent collapse, whether the rebound has failed, and whether there are irreversible wrinkles on the appearance. If the requirements are not met: Q81: Proceed to the "Modify Structural Design" stage. Designers need to adjust the seat structure, such as adding supports, changing the foam density, etc. Q91: Then "Make a sample and re-evaluate" until the requirements are met. If the requirements are met: Q6: Proceed to the final comprehensive judgment. Q52: Simulation verification involves comparing the deformation calculated by simulation with the actual test results. Q82: If the requirements are not met / the deviation between simulation and reality is large: At this point, the structure is not directly modified. Instead, Q92: The process proceeds to "Adjust the CAE input parameters based on the results of the robot's actual evaluation." This means that the material parameters of the simulation model need to be corrected, such as the constitutive relationship of the sponge and the coefficient of friction, to make the simulation results closer to the actual test results, thereby improving the model's confidence. After adjusting the parameters, CAE analysis is performed again. If the requirements are met / the simulation matches the actual result: The final comprehensive judgment is then made.Only when the physical test is qualified and the simulation analysis is reliable / qualified can it be used as the official evaluation result, i.e. Q6: The data obtained at this time has been verified by both physical testing and simulation, and has extremely high reliability. Q7: Finally, it is confirmed that the current seat structure design can withstand the worst boarding scenario and will not experience soft structure failure, such as sponge collapse or frame snagging.

[0088] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the method for determining seat performance in this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0089] This application also provides a seat performance determining device, please refer to... Figure 5 The seat performance determination device includes: The acquisition module 10 is used to acquire the extreme motion trajectory of the occupant, which is the motion path that poses the greatest risk of failure to the soft structure of the vehicle seat.

[0090] The testing module 20 is used to perform simulation analysis and physical testing based on the extreme motion trajectory to obtain simulation results and test results.

[0091] The determination module 30 is used to determine the seat performance based on the simulation results and the test results.

[0092] The seat performance determination device provided in this application, employing the seat performance determination method in the above embodiments, can solve the technical problem of low accuracy in current seat performance determination due to the mismatch between the current scenario and the actual scenario. Compared with the prior art, the beneficial effects of the seat performance determination device provided in this application are the same as those of the seat performance determination method provided in the above embodiments, and other technical features in the seat performance determination device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0093] In one embodiment, the acquisition module 10 is further configured to collect kinematic parameters of multiple occupants; based on the kinematic parameters, select the motion trajectory that causes the maximum force or the maximum deformation of the seat's soft structure; and use the motion trajectory as the extreme motion trajectory.

[0094] In one embodiment, the acquisition module 10 is further configured to establish a three-dimensional coordinate system with the apex of the seat back as the origin; collect the hip movement path coordinates, movement speed, compression angle, and continuous compression time of multiple occupants in the three-dimensional coordinate system; and determine the kinematic parameters of multiple occupants based on the hip movement path coordinates, the movement speed, the compression angle, and the continuous compression time.

[0095] In one embodiment, the determining module 30 is further configured to determine the deviation data between the simulation results and the test results, the deviation data including the target compressive force deviation, the target deformation deviation, and the contact state deviation between the seat soft structure and the seat frame; and to determine the seat performance based on the deviation data.

[0096] In one embodiment, the determining module 30 is further configured to compare the contact state deviation with a preset contact threshold and obtain the rebound recovery rate of the seat soft structure under extreme motion trajectory; when the contact state deviation exceeds the preset contact threshold and the rebound recovery rate is lower than the preset recovery rate threshold, it is determined that the seat soft structure is at risk of being caught by the seat frame, and the seat performance is determined to be unqualified.

[0097] In one embodiment, the determining module 30 is further configured to calculate the weighted combined error of the target extrusion pressure deviation and the target deformation deviation when the contact state deviation does not exceed the preset contact threshold; and when the weighted combined error is within the preset error allowable range, determine that the accuracy of the simulation model meets the requirements and confirm that the seat performance is qualified.

[0098] In one embodiment, the determining module 30 is further configured to: determine that the simulation model is distorted when the weighted comprehensive error exceeds a preset error allowable range; calculate the relative error between the first deformation amount in the simulation result and the second deformation amount in the test result; when the relative error exceeds a first preset range, correct the material parameters in the simulation analysis according to the test results to obtain a corrected simulation analysis model, wherein the material parameters include the elastic modulus of the sponge, Poisson's ratio, or contact friction coefficient; and optimize the seat structure according to the corrected simulation analysis model.

[0099] In one embodiment, the testing module 20 is further configured to construct a finite element simulation model of the seat, input the kinematic parameters of the extreme motion trajectory as boundary conditions into the finite element simulation model for dynamic explicit solution, and output the stress cloud map, strain cloud map, and contact force data between the seat soft structure and the seat frame during the motion process; use the stress cloud map, strain cloud map, and contact force data between the seat soft structure and the seat frame as simulation results; build a physical testing platform, control a robotic arm or simulated dummy to perform repeated motion on the physical testing platform according to the extreme motion trajectory, and collect real-time pressure distribution data and surface deformation data of the seat soft structure; use the pressure distribution data and the surface deformation data as test results.

[0100] This application provides a seat performance determination device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the seat performance determination method in the above embodiment 1.

[0101] The following is for reference. Figure 6 The diagram illustrates a structural schematic suitable for implementing the seat performance determination device in the embodiments of this application. The seat performance determination device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 6 The seat performance determination device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this application.

[0102] like Figure 6As shown, the seat performance determination device may include a processing unit 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the seat performance determination device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touch screens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, LCDs (Liquid Crystal Displays), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. The communication device 1009 allows the seat performance determination device to communicate wirelessly or wiredly with other devices to exchange data. Although the figures show seat performance determination devices with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0103] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0104] The seat performance determination device provided in this application, employing the seat performance determination method described in the above embodiments, can solve the technical problem of low accuracy in current seat performance determination due to the mismatch between the current scenario and the actual scenario. Compared with the prior art, the beneficial effects of the seat performance determination device provided in this application are the same as those of the seat performance determination method provided in the above embodiments, and other technical features of this seat performance determination device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0105] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0106] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0107] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the seat performance determination method in the above embodiments.

[0108] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory or Flash Memory), optical fibers, CD-ROM (CD-Read Only Memory), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0109] The aforementioned computer-readable storage medium may be included in the seat performance determination device; or it may exist independently and not assembled into the seat performance determination device.

[0110] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the seat performance determination device, cause the seat performance determination device to: acquire the occupant's extreme motion trajectory, the extreme motion trajectory being the motion path that poses the greatest risk of failure to the soft structure of the vehicle seat; perform simulation analysis and physical testing based on the extreme motion trajectory to obtain simulation results and test results; and determine the seat performance based on the simulation results and the test results.

[0111] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including LAN (Local Area Network) or WAN (Wide Area Network)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0112] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0113] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0114] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described seat performance determination method. This addresses the technical problem of low accuracy in seat performance determination due to a mismatch between the current scenario and the actual scenario. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the seat performance determination method provided in the above embodiments, and will not be elaborated upon here.

[0115] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the seat performance determination method described above.

[0116] The computer program product provided in this application can solve the technical problem of low accuracy in determining seat performance due to the mismatch between the current scenario and the actual scenario. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the seat performance determination method provided in the above embodiments, and will not be repeated here.

[0117] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for determining seat performance, characterized in that, The method for determining seat performance includes: The extreme motion trajectory of the occupant is obtained, which is the motion path that poses the greatest risk of failure to the soft structure of the vehicle seat; Based on the extreme motion trajectory, simulation analysis and physical testing were performed respectively to obtain simulation results and test results; The seat performance is determined based on the simulation results and the test results.

2. The method of claim 1, wherein, The steps for obtaining the occupant's extreme motion trajectory include: Collect kinematic parameters from multiple occupants; Based on the aforementioned kinematic parameters, motion trajectories that result in the maximum stress or deformation of the seat's soft structure are selected. The aforementioned trajectory is taken as the extreme trajectory of motion.

3. The method of claim 2, wherein, The steps for collecting kinematic parameters from multiple occupants include: Establish a three-dimensional coordinate system with the vertex of the seat back as the origin; The coordinates of the hip movement path, movement speed, compression angle, and continuous compression time of multiple occupants were collected in the three-dimensional coordinate system. The kinematic parameters of multiple occupants are determined based on the coordinates of the hip movement path, the movement speed, the compression angle, and the duration of continuous compression.

4. The method of claim 1, wherein, The step of determining seat performance based on the simulation results and the test results includes: Determine the deviation data between the simulation results and the test results. The deviation data includes the target compressive force deviation, the target deformation deviation, and the contact state deviation between the soft structure of the seat and the seat frame. Seat performance is determined based on the aforementioned deviation data.

5. The method of claim 4, wherein, The step of determining seat performance based on the deviation data includes: The contact state deviation is compared with a preset contact threshold, and the rebound recovery rate of the seat soft structure under extreme motion trajectory is obtained; When the contact state deviation exceeds the preset contact threshold and the rebound recovery rate is lower than the preset recovery rate threshold, it is determined that the soft structure of the seat is at risk of being caught by the seat frame, and the seat performance is determined to be unqualified.

6. The method of claim 5, wherein, After the step of comparing the contact state deviation with a preset contact threshold, the method further includes: When the contact state deviation does not exceed the preset contact threshold, the weighted combined error of the target extrusion pressure deviation and the target deformation deviation is calculated; When the weighted comprehensive error is within the preset error allowable range, it is determined that the accuracy of the simulation model meets the requirements, and the performance of the seat is confirmed to be qualified.

7. The method of claim 6, wherein, After the step of calculating the weighted combined error of the target extrusion pressure deviation and the target deformation deviation when the contact state deviation does not exceed the preset contact threshold, the method further includes: When the weighted composite error exceeds the preset error allowable range, the simulation model is determined to be distorted, and the relative error between the first deformation in the simulation result and the second deformation in the test result is calculated. When the relative error exceeds a first preset range, the material parameters in the simulation analysis are corrected according to the test results to obtain a corrected simulation analysis model. The material parameters include the sponge's elastic modulus, Poisson's ratio, or contact friction coefficient. The seat structure was optimized based on the revised simulation analysis model.

8. The method of any one of claims 1 to 7, wherein, The steps of performing simulation analysis and physical testing based on the extreme motion trajectory to obtain simulation results and test results include: A finite element simulation model of the seat is constructed, and the kinematic parameters of the extreme motion trajectory are input into the finite element simulation model as boundary conditions for dynamic explicit solution. The stress cloud map, strain cloud map and contact force data between the soft structure of the seat and the seat frame during the motion process are output. The stress cloud diagram, the strain cloud diagram, and the contact force data between the soft structure of the seat and the seat frame are used as simulation results; A physical testing platform was built, and a robotic arm or a simulated dummy was controlled to perform repetitive movements on the physical testing platform according to the extreme motion trajectory, and real-time pressure distribution data and surface deformation data of the soft structure of the seat were collected. The pressure distribution data and the surface deformation data are used as test results.

9. A seat performance determination apparatus characterized by comprising: The device includes: The acquisition module is used to acquire the extreme motion trajectory of the occupant, which is the motion path that poses the greatest risk of failure to the soft structure of the vehicle seat; The testing module is used to perform simulation analysis and physical testing based on the extreme motion trajectory to obtain simulation results and test results. The determination module is used to determine the seat performance based on the simulation results and the test results.

10. A storage medium, characterized by The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the seat performance determination method as described in any one of claims 1 to 8.

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