Bush load determination method and device, equipment and storage medium

Abstract

The invention discloses a bush load determination method and device, equipment and a storage medium, and relates to the technical field of vehicles, and the method comprises the steps: obtaining a target response signal corresponding to a preset position; based on the initial load signal, simulating a kinematic model corresponding to the vehicle to obtain a prediction response signal corresponding to a preset position in the kinematic model; according to a first difference corresponding to the predicted response signal and the target response signal at each sampling moment, correcting load data corresponding to each sampling moment in the initial load signal to obtain a candidate load signal; simulating a kinematic model based on the candidate load signal to obtain a candidate response signal corresponding to a preset position in the kinematic model; determining a second difference between the candidate response signal and the target response signal; and under the condition that the second difference meets a preset condition, a target load spectrum corresponding to the bushing in the vehicle is determined based on the candidate load signal. And the reliability and the precision of the bushing load determination result are improved.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to methods, apparatus, equipment and storage media for determining bushing loads. Background Technology

[0002] Bushings in an automotive chassis suspension system are key components for transmitting loads and damping vibrations. The load characteristics they bear directly determine the fatigue life of the bushings and the overall reliability of the suspension system.

[0003] However, the loads experienced by bushings during actual vehicle operation are highly complex, involving a combination of various road conditions (such as paved roads, unpaved roads, speed bumps, etc.), different driving behaviors (such as rapid acceleration, emergency braking, steering, etc.), and vehicle parameters (such as load and suspension system structural parameters). Therefore, accurately determining the loads experienced by bushings during vehicle operation has become a pressing technical problem that needs to be solved. Summary of the Invention

[0004] The main objective of this application is to provide a method, apparatus, device, and storage medium for determining bushing load, aiming to solve the technical problem of how to accurately determine the load on the bushing during vehicle operation.

[0005] To achieve the above objectives, this application proposes a method for determining bushing load, the method comprising: Acquire the target response signal corresponding to the preset position during vehicle movement; Based on the initial load signal, the kinematic model corresponding to the vehicle is simulated to obtain the predicted response signal corresponding to the preset position in the kinematic model; Based on the first difference between the predicted response signal and the target response signal at each sampling time, the load data corresponding to each sampling time in the initial load signal is corrected to obtain the candidate load signal; Based on the candidate load signal, the kinematic model is simulated to obtain the candidate response signal corresponding to the preset position in the kinematic model; Determine a second difference between the candidate response signal and the target response signal; If the second difference meets the preset conditions, the target load spectrum corresponding to the bushing in the vehicle is determined based on the candidate load signal.

[0006] In one embodiment, the second difference includes at least one of a first degree of overlap, a second degree of overlap, and a spurious damage ratio, and determining the second difference between the candidate response signal and the target response signal includes at least one of the following: Determine the first degree of overlap between the first time-domain signal corresponding to the candidate response signal and the second time-domain signal corresponding to the target response signal; Determine the second degree of overlap between the first spectral signal corresponding to the candidate response signal and the second spectral signal corresponding to the target response signal; Determine the pseudo-damage ratio between the first pseudo-damage corresponding to the candidate response signal and the second pseudo-damage corresponding to the target response signal.

[0007] In one embodiment, before simulating the kinematic model corresponding to the vehicle based on the initial load signal, the method further includes: The initial load signal is determined based on the material parameters of the bushing and the structural parameters corresponding to the vehicle's suspension system. The material parameters include at least one of tensile and compressive strength and shear strength; The structural parameters include at least one of the following: bushing outer diameter, bushing inner diameter, distance from the bushing stress point to the installation reference surface, installation preload, and suspension stiffness.

[0008] In one embodiment, the load data corresponding to each sampling moment in the initial load signal includes at least one of axial load, radial load, torsional load, and overturning moment. Determining the initial load signal based on the material parameters of the bushing and the structural parameters corresponding to the vehicle's suspension system includes: The effective bearing area and torsional section modulus of the bushing are determined based on the inner diameter and outer diameter of the bushing. The axial load is determined based on the axial empirical coefficient, the tensile and compressive strength, and the effective bearing area of ​​the bushing. The radial load is determined based on the radial empirical coefficient, the suspension stiffness, and the installation preload. The torsional load is determined based on the torsional empirical coefficient, the shear strength, and the torsional section modulus of the bushing. The overturning moment is determined based on the overturning empirical coefficient, the radial load, and the distance.

[0009] In one embodiment, the target load spectrum is determined based on the target response signal corresponding to the vehicle driving under each preset operating condition. After determining the target load spectrum corresponding to the bushing in the vehicle based on the candidate load signal, the method further includes: Based on the preset number of cycles corresponding to each preset working condition in the entire life cycle of the vehicle and the target load spectrum, the dynamic load spectrum of the bushing in the entire life cycle of the vehicle is determined. The dynamic load spectrum is processed to obtain multiple initial block load spectra, wherein each initial block load spectrum contains at least one load amplitude, the mean value corresponding to the load amplitude, and the number of cycles; Based on the third difference between every two initial block load spectra, the multiple initial block load spectra are processed to determine the target block load spectrum; Based on the target block load spectrum, the target load amplitude and the corresponding target number of cycles for bushing durability testing are determined.

[0010] In one embodiment, the third difference includes a first difference and a second difference, and the step of processing the multiple initial block load spectra based on the third difference between every two initial block load spectra to determine the target block load spectrum includes: Based on each load amplitude and the corresponding number of cycles, determine the third pseudo-damage corresponding to each load amplitude; The load amplitude and the corresponding mean of the third pseudo-damage in each initial block load spectrum are determined as the equivalent load amplitude and equivalent mean of the initial block load spectrum. Determine the first difference between the equivalent load amplitudes corresponding to every two initial block load spectra, and the second difference between the equivalent mean values; The two initial block load spectra corresponding to the first difference being less than the first value and the second difference being less than the second value are merged into a single target block load spectrum.

[0011] In one embodiment, determining the target load amplitude and corresponding target number of cycles for the bushing durability test based on the target block load spectrum includes: The largest equivalent load amplitude in the target block load spectrum is determined as the target load amplitude; Based on the third pseudo-damage corresponding to each load amplitude in each target block load spectrum, determine the fourth pseudo-damage corresponding to each target block load spectrum; Based on the target load amplitude corresponding to each target block load spectrum and the fourth pseudo-damage, determine the initial number of cycles corresponding to the target load amplitude; The initial number of cycles is optimized to determine the target number of cycles, so as to minimize the value of the optimization function. The optimization function includes the absolute value of the difference between the total pseudo-damage and the experimental pseudo-damage corresponding to the dynamic load spectrum, and the test duration. The experimental pseudo-damage and the test duration are determined based on the target load amplitude and the optimized initial number of cycles.

[0012] Furthermore, to achieve the above objectives, this application also proposes a bushing load determination device, which includes: The first acquisition module is used to acquire the target response signal corresponding to the preset position during the vehicle's movement; The second acquisition module is used to simulate the kinematic model corresponding to the vehicle based on the initial load signal, so as to obtain the predicted response signal corresponding to the preset position in the kinematic model; The correction module is used to correct the load data corresponding to each sampling time in the initial load signal based on the first difference between the predicted response signal and the target response signal at each sampling time, so as to obtain the candidate load signal; The third acquisition module is used to simulate the kinematic model based on the candidate load signal to obtain the candidate response signal corresponding to the preset position in the kinematic model; A first determining module is used to determine a second difference between the candidate response signal and the target response signal; The second determining module is used to determine the target load spectrum corresponding to the bushing in the vehicle based on the candidate load signal when the second difference meets the preset conditions.

[0013] In one embodiment, the second difference includes at least one of a first degree of overlap, a second degree of overlap, and a spurious damage ratio, and the first determining module is configured to: Determine the first degree of overlap between the first time-domain signal corresponding to the candidate response signal and the second time-domain signal corresponding to the target response signal; Determine the second degree of overlap between the first spectral signal corresponding to the candidate response signal and the second spectral signal corresponding to the target response signal; Determine the pseudo-damage ratio between the first pseudo-damage corresponding to the candidate response signal and the second pseudo-damage corresponding to the target response signal.

[0014] In one embodiment, a third determining module is further included, for: The initial load signal is determined based on the material parameters of the bushing and the structural parameters corresponding to the vehicle's suspension system. The material parameters include at least one of tensile and compressive strength and shear strength; The structural parameters include at least one of the following: bushing outer diameter, bushing inner diameter, distance from the bushing stress point to the installation reference surface, installation preload, and suspension stiffness.

[0015] In one embodiment, the load data corresponding to each sampling moment in the initial load signal includes at least one of axial load, radial load, torsional load, and overturning moment; the third determining module is used for: The effective bearing area and torsional section modulus of the bushing are determined based on the inner diameter and outer diameter of the bushing. The axial load is determined based on the axial empirical coefficient, the tensile and compressive strength, and the effective bearing area of ​​the bushing. The radial load is determined based on the radial empirical coefficient, the suspension stiffness, and the installation preload. The torsional load is determined based on the torsional empirical coefficient, the shear strength, and the torsional section modulus of the bushing. The overturning moment is determined based on the overturning empirical coefficient, the radial load, and the distance.

[0016] In one embodiment, the target load spectrum is determined based on the target response signal corresponding to the vehicle's operation under each preset working condition, and the system further includes a fourth determining module for: Based on the preset number of cycles corresponding to each preset working condition in the entire life cycle of the vehicle and the target load spectrum, the dynamic load spectrum of the bushing in the entire life cycle of the vehicle is determined. The dynamic load spectrum is processed to obtain multiple initial block load spectra, wherein each initial block load spectrum contains at least one load amplitude, the mean value corresponding to the load amplitude, and the number of cycles; Based on the third difference between every two initial block load spectra, the multiple initial block load spectra are processed to determine the target block load spectrum; Based on the target block load spectrum, the target load amplitude and the corresponding target number of cycles for bushing durability testing are determined.

[0017] In one embodiment, the third difference includes a first difference and a second difference, and the fourth determining module is configured to: Based on each load amplitude and the corresponding number of cycles, determine the third pseudo-damage corresponding to each load amplitude; The load amplitude and the corresponding mean of the third pseudo-damage in each initial block load spectrum are determined as the equivalent load amplitude and equivalent mean of the initial block load spectrum. Determine the first difference between the equivalent load amplitudes corresponding to every two initial block load spectra, and the second difference between the equivalent mean values; The two initial block load spectra corresponding to the first difference being less than the first value and the second difference being less than the second value are merged into a single target block load spectrum.

[0018] In one embodiment, the third difference includes a first difference and a second difference, and the fourth determining module is configured to: The largest equivalent load amplitude in the target block load spectrum is determined as the target load amplitude; Based on the third pseudo-damage corresponding to each load amplitude in each target block load spectrum, determine the fourth pseudo-damage corresponding to each target block load spectrum; Based on the target load amplitude corresponding to each target block load spectrum and the fourth pseudo-damage, determine the initial number of cycles corresponding to the target load amplitude; The initial number of cycles is optimized to determine the target number of cycles, so as to minimize the value of the optimization function. The optimization function includes the absolute value of the difference between the total pseudo-damage and the experimental pseudo-damage corresponding to the dynamic load spectrum, and the test duration. The experimental pseudo-damage and the test duration are determined based on the target load amplitude and the optimized initial number of cycles.

[0019] In addition, to achieve the above objectives, this application also proposes a bushing load 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 bushing load determination method as described above.

[0020] 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 when the computer program is executed by a processor, it implements the steps of the bushing load determination method described above.

[0021] 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 bushing load determination method described above.

[0022] One or more technical solutions proposed in this application have at least the following technical effects: The load determination method in this embodiment first compares the predicted response signal obtained from the simulation of the initial load signal with the target response signal at the sampling time dimension to obtain the first difference corresponding to each sampling time. Based on the first difference, the load data of the corresponding sampling time in the initial load signal is specifically corrected, which can accurately eliminate the response mismatch problem caused by the initial load deviation at a single sampling time, ensuring that the load data at each time can fit the actual vehicle response, providing a basic support for the accuracy of the overall load. At the overall time period dimension, the candidate response signal is obtained again by simulation based on the corrected candidate load signal, and the second difference between the candidate response signal and the target response signal is determined to verify the matching degree between the predicted response and the target response over the entire time period. Only when the second difference meets the preset condition is the target load spectrum corresponding to the bushing determined based on the candidate load signal, which effectively avoids the problem of overall time period response deviation that may be caused by local correction, and improves the reliability and accuracy of the bushing load determination result. Attached Figure Description

[0023] 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.

[0024] 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.

[0025] Figure 1 A flowchart illustrating the method for determining bushing load in this application (Example 1); Figure 2 A flowchart illustrating the method for determining bushing load in Embodiment 2 of this application; Figure 3 A flowchart illustrating the method for determining bushing load in Embodiment 2 of this application; Figure 4 This is a schematic diagram of the module structure of the bushing load determination device according to an embodiment of this application; Figure 5 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the bushing load determination method in the embodiments of this application.

[0026] 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

[0027] 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.

[0028] 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.

[0029] Existing technologies mostly rely on empirical formulas or simple mechanical models to estimate bushing loads. However, the load conditions experienced by automotive chassis suspension systems during actual operation are extremely complex, involving the combined effects of various road conditions (such as paved roads, unpaved roads, speed bumps, etc.), different driving behaviors (such as rapid acceleration, emergency braking, steering, etc.), and vehicle parameters (such as load and suspension system structural parameters). Because existing calculation methods do not fully consider the coupling effects of these complex factors, they can only roughly estimate the load range on the bushings and cannot accurately calculate the true fatigue durability load that the bushings bear during actual use.

[0030] Therefore, this application provides a solution to obtain a target response signal corresponding to a preset position during vehicle operation; simulate the kinematic model of the vehicle based on the initial load signal to obtain a predicted response signal corresponding to the preset position in the kinematic model; correct the load data corresponding to each sampling time in the initial load signal according to the first difference between the predicted response signal and the target response signal at each sampling time to obtain a candidate load signal; simulate the kinematic model based on the candidate load signal to obtain a candidate response signal corresponding to the preset position in the kinematic model; determine a second difference between the candidate response signal and the target response signal; and determine the target load spectrum corresponding to the bushing in the vehicle based on the candidate load signal when the second difference meets a preset condition.

[0031] As can be seen from the above embodiments, this application, in terms of sampling time dimension, specifically corrects the load data corresponding to the sampling time in the initial load signal, which can accurately eliminate the response mismatch problem caused by the initial load deviation at a single sampling time, ensuring that the load data at each time can fit the actual vehicle response, and providing basic support for the accuracy of the overall load. In terms of the overall time period dimension, the target load spectrum corresponding to the bushing is determined based on the candidate load signal only when the second difference meets the preset condition, effectively avoiding the problem of overall time period response deviation that may be caused by local correction, and improving the reliability and accuracy of the bushing load determination result.

[0032] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, personal computer, mobile phone, etc., or an electronic device that can realize the above functions.

[0033] Based on this, embodiments of this application provide a method for determining bushing load, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the method for determining bushing load in this application.

[0034] In this embodiment, the method for determining the bushing load includes steps S10 to S60: Step S10: Obtain the target response signal corresponding to the preset position during vehicle movement.

[0035] The preset location can be a wheel, body, coil spring, etc. This application does not limit this.

[0036] The target response signal can be acceleration, stress, displacement, etc. This application does not limit this.

[0037] In some embodiments, acceleration sensors can be installed on the wheels and body to obtain the acceleration of the wheels and body. Stress sensors can be installed at locations where stress can be detected, such as coil springs, to obtain stress signals. Displacement sensors can be mounted on a frame mounting bracket, with the measuring end aligned with the edge of the wheel hub, to capture the radial displacement response of the bushing caused by wheel bounce.

[0038] In some embodiments, after acquiring the target response signal, the target response signal can be filtered, detrended, de-glitched, and synchronized, thereby improving the accuracy of the target response signal.

[0039] In one possible implementation, the target response signal corresponding to a preset position can be acquired when the vehicle is traveling under preset operating conditions, thereby determining the load on the bushing when the vehicle is traveling under preset operating conditions. In another possible implementation, the target response signal corresponding to a preset position can also be acquired when the vehicle is traveling at any time period, thereby determining the load on the bushing during any travel time period.

[0040] In some embodiments, the preset operating conditions can be constant speed driving on paved roads, driving on unpaved roads (gravel roads), impact from speed bumps, sharp turns, sudden braking, etc. This application does not limit these conditions.

[0041] Step S20: Based on the initial load signal, simulate the kinematic model corresponding to the vehicle to obtain the predicted response signal corresponding to the preset position in the kinematic model.

[0042] The initial load signal can be a pre-set initial load signal corresponding to the vehicle under the target response signal; or it can be a possible initial load predicted based on the target response signal. This application does not limit this.

[0043] It should be noted that the kinematic model can simulate the movement of a vehicle under the drive of an initial load signal, thereby obtaining the predicted response signal corresponding to the preset position.

[0044] In one feasible implementation, the kinematic model of the vehicle can be constructed using multibody dynamics software ADAMS / Car or ABAQUS. The kinematic model can include rigid components (such as the frame, wheels, steering knuckles, etc.), flexible components (such as suspension arms, bushings, etc.), and connection relationships (such as bushings and suspension arms, and the frame being connected by ball joints, and suspension springs and shock absorbers being connected by translational joints, etc.).

[0045] After constructing the kinematic model, the kinematic model parameters can be adjusted based on static or simple dynamic conditions to improve the accuracy of the kinematic model.

[0046] Step S30: Based on the first difference between the predicted response signal and the target response signal at each sampling time, the load data corresponding to each sampling time in the initial load signal is corrected to obtain the candidate load signal.

[0047] In one feasible implementation, with one preset position, the predicted response value of the predicted response signal at each sampling time is determined, and the target response value of the target response signal at each sampling time is determined. The difference between the predicted response value and the target response value is determined as the first difference.

[0048] In one feasible implementation, when there are multiple preset positions, the predicted response value of the predicted response signal at each preset position at each sampling time is determined, and the target response value of the target response signal at each preset position at each sampling time is determined; then, the difference between the predicted response value and the target response value at each preset position at each sampling time is determined; based on the weight corresponding to each preset position, the square of the first difference corresponding to each preset position is weighted to determine the first difference at each sampling time.

[0049] In some embodiments, the weight of each preset position can be determined based on the degree of influence of the response signal corresponding to the preset position on the bushing. For example, the response signal collected by the strain gauge at the helical spring directly reflects the core load of the bushing; therefore, the weight corresponding to the response signal collected by the strain gauge at the helical spring can be greater than that of the response signal collected by the acceleration sensor of the wheel.

[0050] In some embodiments, if the first difference corresponding to the sampling time is greater than a first preset threshold, a correction amount corresponding to the sampling time is determined. The first preset threshold can be 0.01, 0.02, etc. This application does not limit this.

[0051] It should be noted that the larger the first difference, the larger the correction amount; the smaller the first difference, the smaller the correction amount.

[0052] Step S40: Based on the candidate load signal, simulate the kinematic model to obtain the candidate response signal corresponding to the preset position in the kinematic model.

[0053] It should be noted that the modified candidate load signal is used to drive the kinematic model and output candidate response signal, which provides a new simulation benchmark for subsequent judgment of whether the load correction is effective, and ensures that the modified load can truly reflect the force on the actual vehicle.

[0054] In one possible implementation, after acquiring the candidate response signal, the first difference between the candidate response signal and the target response signal at each sampling time can be further determined. If the first difference is greater than a first preset threshold, the candidate load data is further corrected, and the operation of driving the kinematic model is returned until the first iteration stop condition is met. The load signal at the time of iteration stop is determined as the candidate load signal, and the response signal is determined as the candidate response signal.

[0055] In one possible implementation, the first iteration stopping condition may include at least one of the following: a first error is less than a first preset threshold, the target number of iterations is reached, and the difference between multiple consecutive candidate load signals is less than a second preset threshold.

[0056] For example, the second preset threshold can be 0.5 times, 0.1 times, etc. of the rated load. This application does not limit this.

[0057] Step S50: Determine the second difference between the candidate response signal and the target response signal.

[0058] In some embodiments, the second difference may include at least one of a first degree of overlap, a second degree of overlap, and a spurious damage ratio, and step S50 may include at least one of steps S501-S503.

[0059] Step S501: Determine the first overlap between the first time-domain signal corresponding to the candidate response signal and the first time-domain signal corresponding to the target response signal.

[0060] In one possible implementation, the first time-domain signal and the second time-domain signal are subjected to preprocessing operations such as denoising, zero-drift calibration, time synchronization, and sampling based on the sampling interval.

[0061] The formula for calculating the first degree of overlap is as follows:

[0062] in, The first degree of overlap, Let be the value of the first time-domain signal at the i-th sampling time. Let be the value of the second time-domain signal at the i-th sampling time.

[0063] It should be noted that the closer the first overlap is to 1, the higher the overlap between the first time domain signal and the second time domain signal.

[0064] Step S502: Determine the second degree of overlap between the first spectral signal corresponding to the candidate response signal and the second spectral signal corresponding to the target response signal.

[0065] In one possible implementation, the first and second spectral signals are subjected to preprocessing operations such as denoising, zero-drift calibration, time synchronization, and sampling based on the sampling interval.

[0066] The formula for calculating the second degree of overlap is as follows:

[0067] in, The second degree of overlap, Let be the value of the first spectral signal at the i-th sampling time. Let be the value of the second spectral signal at the i-th sampling time.

[0068] It should be noted that the closer the second overlap is to 1, the higher the overlap between the first and second spectral signals.

[0069] Step S503: Determine the pseudo-damage ratio between the first pseudo-damage corresponding to the candidate response signal and the second pseudo-damage corresponding to the target response signal.

[0070] In some embodiments, the mapping relationship between the amplitude of the response signal at each preset location and the bushing life can be predetermined throughout the vehicle's entire life cycle, and then pseudo-damage can be determined based on the mapping relationship and the response signal.

[0071] For example, if the type of response signal is stress, then the mapping relationship between stress amplitude and bushing life can be: ,in, The number of loops. Let be the stress amplitude, m be the material constant, and C be the fatigue strength coefficient. Then, rainflow statistics are performed on the candidate response signals to determine multiple first stress amplitudes corresponding to the candidate response signals and the first cycle number corresponding to each first stress amplitude. Based on the mapping relationship, the pseudo-damage corresponding to each first stress amplitude is determined, and the sum of the pseudo-damages corresponding to all first stress amplitudes is determined as the first pseudo-damage.

[0072] Similarly, rainflow statistics are performed on the target response signal to determine multiple second stress amplitudes corresponding to the target response signal and the number of second cycles corresponding to each second stress amplitude. Based on the mapping relationship, the pseudo-damage corresponding to each second stress amplitude is determined. Then, the sum of the pseudo-damages corresponding to all second stress amplitudes is determined as the second pseudo-damage.

[0073] The spurious damage ratio is the ratio between the first spurious damage and the second spurious damage.

[0074] In this embodiment, by determining the first degree of overlap between the candidate response signal and the target response signal in the time domain, the second degree of overlap in the frequency domain, and the pseudo-damage ratio in terms of bushing life requirements, the differences between the candidate response signal and the target response signal are comprehensively compared. This can improve the accuracy of load verification and ultimately ensure that the target load spectrum can truly reproduce the stress state of the bushing during vehicle operation, providing key technical support for the high-performance design and high-reliability application of bushings.

[0075] Step S60: If the second difference meets the preset conditions, determine the target load spectrum corresponding to the bushing in the vehicle based on the candidate load signal.

[0076] In some embodiments, the second difference satisfies the first preset condition, which may include at least one of the following: the first degree of overlap is greater than or equal to the first threshold; the second degree of overlap is greater than or equal to the second threshold; the proportion of false damage is greater than or equal to the third threshold and less than or equal to the fourth threshold, wherein the third threshold is less than the fourth threshold.

[0077] It should be noted that the first threshold and the second threshold may be the same or different. This application does not impose any limitation on this. For example, the first threshold and the second threshold may both be 0.95. Or, the first threshold may be 0.96 and the second threshold may be 0.95. This application does not impose any limitation on this.

[0078] It should be noted that, under the condition that the second difference meets the preset conditions, the determined candidate load signal can accurately reflect the load borne by the vehicle under the target response signal. Therefore, the candidate load signal can be input into the kinematic model to drive the kinematic model to move, thereby accurately obtaining the target load spectrum corresponding to the bushing during vehicle operation.

[0079] The load determination method in this embodiment first compares the predicted response signal obtained from the simulation of the initial load signal with the target response signal at the sampling time dimension to obtain the first difference corresponding to each sampling time. Based on the first difference, the load data of the corresponding sampling time in the initial load signal is specifically corrected, which can accurately eliminate the response mismatch problem caused by the initial load deviation at a single sampling time, ensuring that the load data at each time can fit the actual vehicle response, providing a basic support for the accuracy of the overall load. At the overall time period dimension, the candidate response signal is obtained again by simulation based on the corrected candidate load signal, and the second difference between the candidate response signal and the target response signal is determined to verify the matching degree between the predicted response and the target response over the entire time period. Only when the second difference meets the preset condition is the target load spectrum corresponding to the bushing determined based on the candidate load signal, which effectively avoids the problem of overall time period response deviation that may be caused by local correction, and improves the reliability and accuracy of the bushing load determination result.

[0080] 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 Following step S20, the method for determining the bushing load further includes step S21: Step S21: Determine the initial load signal based on the material parameters of the bushing and the corresponding structural parameters of the vehicle's suspension system.

[0081] The material parameters include at least one of tensile and compressive strength and shear strength; The structural parameters include at least one of the following: bushing outer diameter, bushing inner diameter, distance from the bushing stress point to the installation reference surface, installation preload, and suspension stiffness.

[0082] In one feasible implementation, the load data corresponding to each sampling moment in the initial load signal includes at least one of axial load, radial load, torsional load, and overturning moment. Step S21 may include steps S211 to S215: Step S211: Determine the effective bearing area and torsional section modulus of the bushing based on the inner diameter and outer diameter of the bushing.

[0083] The formula for calculating the effective bearing area S is as follows:

[0084] Where D is the outer diameter of the bushing. This is the inner diameter of the bushing.

[0085] The formula for calculating the torsional section modulus w of the bushing is as follows:

[0086] Where D is the outer diameter of the bushing. This is the inner diameter of the bushing.

[0087] Step S212: Determine the axial load based on the axial empirical coefficient, tensile and compressive strength, and effective bearing area of ​​the bushing.

[0088] Among them, axial load The formula for calculating the compressive or tensile force along the central axis of the bushing is:

[0089] in, This is an empirical coefficient for the axial direction. For tensile and compressive strength, This refers to the effective bearing area of ​​the bushing. The axial empirical coefficient is generally taken as 0.35-0.45, and can be adjusted according to the bushing preload. The larger the preload, the larger the value of the axial empirical coefficient.

[0090] Step S213: Determine the radial load based on the radial empirical coefficient, suspension stiffness, and installation preload.

[0091] Among them, radial load For a transverse load perpendicular to the bushing axis, it can be decomposed into X and Y component loads. , .

[0092] In one possible implementation, The calculation formula is: = ×K×Δx in, Here, K is the radial empirical coefficient, Δ is the suspension stiffness, and Δ is the radial empirical coefficient. x This refers to the bushing's installation offset in the X direction. The radial empirical coefficient can range from 0.25 to 0.35 and can be calibrated based on road test data of similar vehicle models. This application does not impose any limitations on this.

[0093] In one possible implementation, The calculation formula is: = ×K×Δy in Δy is the installation offset of the bushing in the Y direction.

[0094] Step S214: Determine the torsional load based on the torsional empirical coefficient, shear strength, and bushing torsional section modulus.

[0095] Among them, torsional load The torque load about the bushing axis is calculated using the following formula:

[0096] in, Let τ be the empirical coefficient for torsion, and τ be the shear strength. This is the torsional section modulus of the bushing. The shear strength can be 0.3-0.4, and can be adjusted in conjunction with the shear modulus of the bushing material.

[0097] Step S215: Determine the overturning moment based on the overturning experience coefficient, radial load, and distance.

[0098] Among them, overturning moment The formula for calculating the eccentric moment borne by the bushing is:

[0099] in, The overturning empirical coefficient (value can be 0.15-0.25) is used, and L is the distance from the bushing stress point to the installation reference surface.

[0100] Therefore, the initial load is further divided into four core forces: axial load, radial load, torsional load, and overturning moment, to achieve accurate quantification of multi-dimensional loads, solve the one-sidedness of traditional single load calculation, and make the initial load data more consistent with the actual stress state.

[0101] In one possible implementation, if the load data corresponding to each sampling moment in the initial load signal includes at least one of axial load, radial load, torsional load, and overturning moment, for each sampling moment, the gradient of the first error with respect to each load component is calculated by using the partial derivative to obtain the correction amount corresponding to each load component. Then, the correction amount of each load component is superimposed on the current load to obtain a new load, and the simulation continues until the iteration stopping condition is met.

[0102] In this embodiment, the initial load signal is determined based on the material parameters of the bushing and the structural parameters corresponding to the vehicle's suspension system. This provides a dual constraint of material safety and structural compatibility for determining the initial load signal, avoiding initial deviations caused by taking values ​​without a basis. This reduces the number of iterations and improves efficiency.

[0103] In one possible implementation, after step S50, the method further includes: if the second difference does not meet the preset condition, continuing to correct the load data corresponding to each sampling time in the candidate load signal, and based on the corrected candidate load signal, returning to the operation of driving the kinematic model until the first iteration stop condition is met, thereby determining the new candidate response signal when the first iteration stop condition is met, the new second difference between the new candidate response signal and the target response signal, and determining whether the new second difference meets the preset condition until the second iteration stop condition is met, and finally determining the target load spectrum based on the candidate load signal when the second iteration stop condition is met.

[0104] The second iteration stopping condition may include at least one of the following: satisfying the second iteration stopping condition, the difference between multiple consecutive second differences is less than the difference threshold.

[0105] The difference threshold can be 0.6%, 1%, etc. This application does not limit it.

[0106] In one possible implementation, if the second difference includes the first degree of overlap, the second degree of overlap, and the pseudo-damage ratio, then if the first degree of overlap is less than the first threshold, the second degree of overlap is less than the second threshold, the pseudo-damage ratio is greater than or equal to the third threshold and less than or equal to the fourth threshold, the difference between the first degree of overlap in multiple consecutive iterations is less than the difference threshold, the difference between the second degree of overlap in multiple consecutive iterations is less than the difference threshold, and the difference between the pseudo-damage ratios in multiple consecutive iterations is less than the difference threshold, then the second iteration stopping condition is determined to be satisfied.

[0107] In one possible implementation, after step S50, the method further includes: if the second difference does not meet the preset condition, correcting the mesh parameters of the kinematic model, and re-executing the operation of driving the corrected kinematic model to move based on the initial load signal until the second iteration stop condition is met.

[0108] In related technologies, if the actual fatigue durability load borne by the bushing during actual use cannot be accurately calculated, the bench tests based on these load calculations will deviate significantly from the actual fatigue durability performance of the bushing in the vehicle. This results in inaccurate evaluation of the bushing's fatigue durability performance by bench tests, potentially leading to premature fatigue failure of the developed bushing product during actual vehicle use, thus affecting the overall reliability of the automotive chassis suspension system. Therefore, this application, after accurately determining the load borne by the bushing during operation, can further determine the target load amplitude and corresponding target number of cycles for bench testing based on the accurate load, thereby further improving the accuracy and efficiency of bench testing.

[0109] 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 the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Furthermore, if the target load spectrum is determined based on the target response signal corresponding to the vehicle's operation under each preset working condition, please refer to... Figure 3 After step S60, the method for determining the bushing load also includes steps S70~S100: Step S70: Determine the dynamic load spectrum of the bushing corresponding to the entire life cycle of the vehicle based on the preset number of cycles and the target load spectrum for each preset working condition in the entire life cycle of the vehicle.

[0110] In one possible implementation, when obtaining the target load spectrum corresponding to the bushing as the vehicle travels under each preset operating condition, a first threshold and a second threshold can be determined based on the type of the preset operating condition. For example, the first threshold under normal operating conditions (such as constant speed driving) is smaller than the first threshold under complex operating conditions (such as sudden braking, sharp turning, etc.); the second threshold under normal operating conditions is smaller than the second threshold under complex operating conditions. For instance, the first and second thresholds for normal operating conditions can be 0.95, and the first and second thresholds for complex operating conditions can be 0.97. This application does not limit this.

[0111] In one possible implementation, the third and fourth thresholds can be determined based on the vehicle's operating conditions. For example, under normal operating conditions, the third threshold can be 0.9 and the fourth threshold can be 1.1; under complex operating conditions, the third threshold can be 0.95 and the fourth threshold can be 1.05. This application does not limit the values ​​of the third and fourth thresholds.

[0112] It should be noted that bushing fatigue damage mainly originates from combinations of high-amplitude, highly dynamic loads, and complex operating conditions (such as sudden braking and sharp turns) are the core scenarios in which these loads are generated. Therefore, by changing the threshold of complex operating conditions, the accuracy of the predicted load under complex operating conditions can be improved, thereby allowing for more accurate determination of the data used for bench testing, and ultimately, more accurate prediction of bushing fatigue damage.

[0113] In some embodiments, preset operating conditions and the preset number of cycles corresponding to each preset operating condition can be determined based on vehicle road condition specifications (such as an equivalent 10-year / 200,000-kilometer warranty life for the whole vehicle).

[0114] In one possible implementation, the target load spectrum is iterated based on a preset number of cycles corresponding to each preset working condition, thereby obtaining the dynamic load spectrum of the bushing throughout the vehicle's entire life cycle.

[0115] Step S80: Process the dynamic load spectrum to obtain multiple initial block load spectra, wherein each initial block load spectrum contains at least one load amplitude, the mean value corresponding to the load amplitude, and the number of cycles.

[0116] In one possible implementation, rainflow statistical analysis is performed on the dynamic load spectrum to obtain multiple load amplitudes, the mean value corresponding to each load amplitude, and the number of cycles. Then, based on the load amplitude interval and the mean value interval, the multiple load amplitudes, the mean value corresponding to each load amplitude, and the number of cycles are divided into intervals to obtain multiple initial block load spectra.

[0117] For example, the load amplitude can be divided into three intervals: high, medium, and low (e.g., 0-30% of the maximum amplitude is the low interval, 30%-70% is the medium interval, and 70%-100% is the high interval). The mean can be divided into three categories: positive, negative, and zero mean, based on positive, negative, and zero values, thus obtaining nine initial block load spectra. It should be noted that this application does not limit the number of load amplitude intervals or the number of mean intervals.

[0118] In one possible implementation, after dividing multiple load amplitudes, their corresponding average values, and cycle counts into intervals based on load amplitude and mean ranges, multiple block load spectra are obtained. Then, based on each load amplitude and its corresponding cycle count, a third pseudo-damage is determined for each load amplitude. The sum of the third pseudo-damages corresponding to all load amplitudes within the block load spectrum is then determined as the fifth pseudo-damage corresponding to the block load spectrum. Finally, the block load spectra with the largest fifth pseudo-damages are determined as the initial block load spectra, where the sum of the fifth pseudo-damages corresponding to the multiple initial block load spectra is greater than the third value. This allows selecting block load spectra with higher damage contribution as the initial block load spectra, prioritizing load combinations with high amplitudes and high cycle counts to ensure coverage of the main damage conditions of the bushing.

[0119] The specific process for calculating the third pseudo-damage is as follows: 1. Obtaining the stress-life curve of the material: The stress-life curve is obtained through fatigue testing of the bushing material. (N is the number of loops, (where m is the stress amplitude, C is the material constant, and C is the fatigue strength coefficient), and convert it into a load-life curve. (F is the load amplitude, and C' is the converted constant).

[0120] 2. Calculation of the third pseudo-damage corresponding to the load amplitude: Based on Miner's linear cumulative damage theory, the third pseudo-damage corresponding to the load amplitude is... , where ni is the number of cycles of the load amplitude in the dynamic load spectrum, and Ni is the material fatigue life corresponding to the load amplitude in the load-life curve.

[0121] The third value can be 0.9, 0.95, etc. This application does not limit this value.

[0122] Step S90: Based on the third difference between every two initial block load spectra, process the multiple initial block load spectra to determine the target block load spectrum.

[0123] In one feasible implementation, step S90 may include steps S91 to S94: Step S91: Determine the third pseudo-damage corresponding to each first load amplitude based on each load amplitude and the corresponding number of cycles.

[0124] Step S92: Determine the load amplitude and the corresponding mean of the third pseudo-damage with the largest value in each initial block load spectrum as the equivalent load amplitude and equivalent mean of the initial block load spectrum.

[0125] For example, the initial block load spectrum includes load amplitude 1 and its corresponding mean 1, load amplitude 2 and its corresponding mean 2, and load amplitude 3 and its corresponding mean 3. The third pseudo-damage corresponding to load amplitude 3 is the largest. Therefore, load amplitude 3 is determined as the equivalent load amplitude corresponding to the initial block load spectrum, and mean 3 is determined as the equivalent mean.

[0126] Step S93: Determine the first difference between the equivalent load amplitudes corresponding to every two initial block load spectra, and the second difference between the equivalent mean values.

[0127] Step S94: The two initial block load spectra corresponding to the first difference being less than the first value and the second difference being less than the second value are merged into a single target block load spectrum.

[0128] In one possible implementation, the first value can be determined based on the maximum value among the equivalent load amplitudes corresponding to the two initial block load spectra. For example, if the equivalent load amplitude corresponding to initial block load spectrum 1 is greater than the equivalent load amplitude corresponding to initial block load spectrum 2, then the first value is determined to be a multiple of the equivalent load amplitude corresponding to initial block load spectrum 1 and 0.5%. Here, 0.5% is for illustrative purposes only and is not a limitation of this application.

[0129] In another possible implementation, the first value can be a fixed value, such as 5, 10, etc. This application does not limit this.

[0130] In one possible implementation, the second value can be determined based on the maximum of the equivalent means corresponding to the two initial block load spectra. For example, if the equivalent mean corresponding to initial block load spectrum 1 is greater than the equivalent mean corresponding to initial block load spectrum 2, then the first value is determined to be the equivalent mean corresponding to initial block load spectrum 1 multiplied by 3%. Here, 3% is for illustrative purposes only and is not a limitation of this application.

[0131] In another possible implementation, the second value can be a fixed value, such as 5, 8, etc. This application does not limit this.

[0132] It should be noted that if the first difference between any initial block load spectrum and other initial block load spectra is greater than or equal to the first value, or the second difference is greater than or equal to the second value, then the initial block load spectrum is determined as the target block load spectrum.

[0133] Therefore, the third pseudo-damage is determined by the load amplitude and the number of cycles. The load amplitude and mean value corresponding to the largest third pseudo-damage are taken as equivalent parameters, which can anchor the core load of bushing fatigue damage (such as high amplitude, high damage load) and retain key damage information. Then, the first difference of the equivalent load amplitude and the second difference of the equivalent mean value are used as the merging threshold. Merging is only performed when the two are less than the first and second values, respectively, to ensure that the damage degree of the merged block spectrum load amplitude and the mean stress state are consistent. While reducing the number of test units, it avoids the characteristic distortion caused by blind merging.

[0134] Step S100: Based on the target block load spectrum, determine the target load amplitude and the corresponding target number of cycles for the bushing durability test.

[0135] In one feasible implementation, step S100 may include steps S101 to S104: Step S101: The largest equivalent load amplitude in the target block load spectrum is determined as the target load amplitude.

[0136] It should be noted that if the target block load spectrum is formed by merging two initial block load spectra, the largest equivalent load amplitude among the two initial block load spectra is determined as the target load amplitude. If the target block load spectrum is a single initial block load spectrum, the equivalent load amplitude corresponding to the initial block load spectrum is determined as the target load amplitude.

[0137] Step S102: Determine the fourth pseudo-damage corresponding to each target block load spectrum based on the third pseudo-damage corresponding to each load amplitude in each target block load spectrum.

[0138] In one possible implementation, the sum of the third pseudo-damages corresponding to all load amplitudes in the target block load spectrum is determined as the fourth pseudo-damage corresponding to the target block load spectrum.

[0139] Step S103: Determine the initial number of cycles corresponding to the target load amplitude based on the target load amplitude corresponding to each target block load spectrum and the fourth pseudo-damage.

[0140] In one possible implementation, a single pseudo-damage corresponding to the target load amplitude is determined, and the ratio between the fourth pseudo-damage and the single pseudo-damage is determined as the initial number of cycles corresponding to the target load amplitude.

[0141] Step S104: Optimize the initial number of iterations and determine the target number of iterations to minimize the value of the optimization function.

[0142] The optimization function includes the absolute value of the difference between the total pseudo-damage corresponding to the dynamic load spectrum and the experimental pseudo-damage, as well as the test duration. The experimental pseudo-damage and test duration are determined based on the target load amplitude and the optimized initial number of cycles. Therefore, by introducing a dual-objective optimization function of test efficiency and damage equivalence, with the objectives of minimizing the pseudo-damage equivalence error and the shortest test duration, test efficiency is improved while ensuring the pseudo-damage equivalence error.

[0143] In one possible implementation, the optimization function F can be:

[0144] in, The total pseudo-damage corresponding to the dynamic load spectrum. The test spurious damage is determined based on the target load amplitude and the corrected initial number of cycles, where ρ is the time weight and T is the total test duration based on the target load amplitude and the corrected initial number of cycles.

[0145] In one possible implementation, the sum of the third pseudo-damages corresponding to all load amplitudes can be determined as the total pseudo-damage.

[0146] In one possible implementation, the fatigue life of the target material corresponding to each target load amplitude can be determined based on the load-life curve. The ratio between the initial number of cycles corresponding to each target load amplitude and the fatigue life of the target material can be used to determine the sub-pseudo-damage corresponding to each target load amplitude. The sum of all sub-pseudo-damages can be determined as the experimental pseudo-damage.

[0147] In one possible implementation, the initial number of iterations can be optimized based on a genetic algorithm to determine the target number of iterations.

[0148] Therefore, setting the maximum equivalent load amplitude as the target load amplitude can cover the ultimate stress conditions in actual use of the bushing, avoiding the risk of premature failure after installation due to the test not involving the ultimate load. Then, based on the fourth pseudo-damage (total pseudo-damage) of the target block spectrum and the target load amplitude, the initial number of cycles is calculated to establish a damage equivalence basis between the test and actual working conditions, ensuring that the test damage can map the damage throughout the entire life cycle. Finally, with the goal of minimizing the absolute value of the total pseudo-damage difference and the optimization function of the test duration, the number of cycles is optimized, which can shorten the test duration within a controllable range of damage deviation.

[0149] In another possible implementation, the largest equivalent load amplitude in the target block load spectrum is determined as the target load amplitude, and the initial number of cycles corresponding to the target load amplitude is determined as the target number of cycles.

[0150] In this embodiment, a dynamic load spectrum is generated by combining the preset number of cycles for the entire life cycle operating conditions with a precise target load spectrum. This fully reproduces the load characteristics and cumulative damage effects of multiple operating conditions in actual use of the bushing, avoiding incomplete test coverage caused by single-condition loads and providing a real stress basis for the test. Then, the dynamic load spectrum is processed into an initial block load spectrum containing load amplitude, mean, and number of cycles. This transforms continuous, unexecutable load data into discrete test units while retaining core damage information, solving the engineering problem that continuous loads cannot be directly used for bench testing. Furthermore, the target block load spectrum is obtained by third-order difference optimization, eliminating redundant units, reducing the number of tests, shortening the cycle, and ensuring damage equivalence, thus balancing test efficiency and accuracy. Finally, test parameters are determined based on the target block spectrum to achieve damage equivalence between bench testing and actual stress, preventing premature failure of the bushing after vehicle assembly, improving the reliability of the chassis suspension system, and completing the closed loop from precise load to test verification.

[0151] 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 the bushing load of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0152] This application also provides a device for determining bushing load, please refer to... Figure 4 The bushing load determination device includes: The first acquisition module 401 is used to acquire the target response signal corresponding to the preset position during the vehicle's movement. The second acquisition module 402 is used to simulate the kinematic model of the vehicle based on the initial load signal in order to obtain the predicted response signal corresponding to the preset position in the kinematic model. The correction module 403 is used to correct the load data corresponding to each sampling time in the initial load signal based on the first difference between the predicted response signal and the target response signal at each sampling time, so as to obtain the candidate load signal. The third acquisition module 404 is used to simulate the kinematic model based on the candidate load signal in order to obtain the candidate response signal corresponding to the preset position in the kinematic model. The first determining module 405 is used to determine a second difference between the candidate response signal and the target response signal; The second determining module 406 is used to determine the target load spectrum corresponding to the bushing in the vehicle based on the candidate load signal when the second difference meets the preset conditions.

[0153] In one embodiment, the second difference includes at least one of a first degree of overlap, a second degree of overlap, and a spurious damage ratio; the first determining module 405 is configured to: Determine the first degree of overlap between the first time-domain signal corresponding to the candidate response signal and the second time-domain signal corresponding to the target response signal; Determine the second degree of overlap between the first spectral signal corresponding to the candidate response signal and the second spectral signal corresponding to the target response signal; Determine the pseudo-damage ratio between the first pseudo-damage corresponding to the candidate response signal and the second pseudo-damage corresponding to the target response signal.

[0154] In one embodiment, a third determining module is further included, for: The initial load signal is determined based on the material parameters of the bushing and the corresponding structural parameters of the vehicle's suspension system. The material parameters include at least one of tensile and compressive strength and shear strength; The structural parameters include at least one of the following: bushing outer diameter, bushing inner diameter, distance from the bushing stress point to the installation reference surface, installation preload, and suspension stiffness.

[0155] In one embodiment, the load data corresponding to each sampling moment in the initial load signal includes at least one of axial load, radial load, torsional load, and overturning moment; the third determining module is used for: The effective bearing area and torsional section modulus of the bushing are determined based on the inner and outer diameters of the bushing. The axial load is determined based on the axial empirical coefficient, tensile and compressive strength, and effective bearing area of ​​the bushing. The radial load is determined based on the radial empirical coefficient, suspension stiffness, and installation preload. The torsional load is determined based on the empirical torsional coefficient, shear strength, and bushing torsional section modulus. The overturning moment is determined based on the overturning empirical coefficient, radial load, and distance.

[0156] In one embodiment, the target load spectrum is determined based on the target response signal corresponding to the vehicle's operation under each preset working condition, and the system further includes a fourth determining module for: Based on the preset number of cycles and the target load spectrum corresponding to each preset working condition in the entire vehicle life cycle, determine the dynamic load spectrum of the bushing in the entire vehicle life cycle. The dynamic load spectrum is processed to obtain multiple initial block load spectra. Each initial block load spectrum contains at least one load amplitude, the mean value of the load amplitude, and the number of cycles. Based on the third difference between every two initial block load spectra, multiple initial block load spectra are processed to determine the target block load spectra; Based on the target block load spectrum, the target load amplitude and the corresponding target number of cycles for bushing durability testing are determined.

[0157] In one embodiment, the third difference includes the first difference and the second difference; the fourth determining module is used for: Based on each load amplitude and the corresponding number of cycles, determine the third pseudo-damage corresponding to each load amplitude; The load amplitude and the corresponding mean of the third pseudo-damage in each initial block load spectrum are determined as the equivalent load amplitude and equivalent mean of the initial block load spectrum. Determine the first difference between the equivalent load amplitudes corresponding to every two initial block load spectra, and the second difference between the equivalent mean values; The two initial block load spectra corresponding to the first difference being less than the first value and the second difference being less than the second value are merged into a single target block load spectrum.

[0158] In one embodiment, the third difference includes the first difference and the second difference; the fourth determining module is used for: The maximum equivalent load amplitude in the target block load spectrum is determined as the target load amplitude; Based on the third pseudo-damage corresponding to each load amplitude in each target block load spectrum, determine the fourth pseudo-damage corresponding to each target block load spectrum; Based on the target load amplitude corresponding to each target block load spectrum and the fourth pseudo-damage, determine the initial number of cycles corresponding to the target load amplitude. The initial number of cycles is optimized to determine the target number of cycles, which minimizes the value of the optimization function. The optimization function includes the absolute value of the difference between the total pseudo-damage corresponding to the dynamic load spectrum and the experimental pseudo-damage, as well as the test duration. The experimental pseudo-damage and test duration are determined based on the target load amplitude and the optimized initial number of cycles.

[0159] The bushing load determination device provided in this application, employing the bushing load determination method in the above embodiments, can solve the technical problem of being unable to accurately determine the load on the bushing during vehicle operation. Compared with the prior art, the beneficial effects of the bushing load determination device provided in this application are the same as those of the bushing load determination method provided in the above embodiments, and other technical features in the bushing load determination device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0160] This application provides a bushing load 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, which are executed by the at least one processor to enable the at least one processor to perform the bushing load determination method in Embodiment 1 above.

[0161] The following is for reference. Figure 5The diagram illustrates a structural schematic of a device suitable for implementing the bushing load determination method in the embodiments of this application. The bushing load 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 5 The bushing load determination device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0162] like Figure 5 As shown, the bushing load determination device may include a processing unit 501 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from storage device 503 into random access memory (RAM) 504. The RAM 504 also stores various programs and data required for the operation of the bushing load determination device. The processing unit 501, ROM 502, and RAM 504 are interconnected via a bus 505. An input / output (I / O) interface 506 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 506: input devices 507 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 508 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 503 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows the bushing load determination device to communicate wirelessly or wiredly with other devices to exchange data. While bushing load determination devices with various systems are shown in the figures, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0163] 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 503, or installed from ROM 502. When the computer program is executed by processing device 501, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0164] The bushing load determination device provided in this application, employing the bushing load determination method in the above embodiments, can solve the technical problem of being unable to accurately determine the load on the bushing during vehicle operation. Compared with the prior art, the beneficial effects of the bushing load determination device provided in this application are the same as those of the bushing load determination method provided in the above embodiments, and other technical features in this bushing load determination device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0165] 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.

[0166] 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.

[0167] 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 perform the bushing load determination method in the above embodiments.

[0168] 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 or 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, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), 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 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.

[0169] The aforementioned computer-readable storage medium may be included in the device for determining the bushing load; or it may exist independently and not assembled into the device for determining the bushing load.

[0170] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the bushing load determining device, enable the bushing load determining device to implement the bushing load determining method.

[0171] 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++, and 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 a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0172] 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.

[0173] 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.

[0174] 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 performing the above-described method for determining bushing loads, thereby solving the technical problem of being unable to accurately determine the loads experienced by the bushing during vehicle operation. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the bushing load determination method provided in the above embodiments, and will not be repeated here.

[0175] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the bushing load determination method as described above.

[0176] The computer program product provided in this application can solve the technical problem of being unable to accurately determine the load on the bushing during vehicle operation. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the bushing load determination method provided in the above embodiments, and will not be repeated here.

[0177] 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 bushing load, characterized in that, The method for determining the bushing load includes: Acquire the target response signal corresponding to the preset position during vehicle movement; Based on the initial load signal, the kinematic model corresponding to the vehicle is simulated to obtain the predicted response signal corresponding to the preset position in the kinematic model; Based on the first difference between the predicted response signal and the target response signal at each sampling time, the load data corresponding to each sampling time in the initial load signal is corrected to obtain the candidate load signal; Based on the candidate load signal, the kinematic model is simulated to obtain the candidate response signal corresponding to the preset position in the kinematic model; Determine a second difference between the candidate response signal and the target response signal; If the second difference meets the preset conditions, the target load spectrum corresponding to the bushing in the vehicle is determined based on the candidate load signal.

2. The method according to claim 1, characterized in that, The second difference includes at least one of a first degree of overlap, a second degree of overlap, and a spurious damage ratio, and determining the second difference between the candidate response signal and the target response signal includes at least one of the following: Determine the first degree of overlap between the first time-domain signal corresponding to the candidate response signal and the second time-domain signal corresponding to the target response signal; Determine the second degree of overlap between the first spectral signal corresponding to the candidate response signal and the second spectral signal corresponding to the target response signal; Determine the pseudo-damage ratio between the first pseudo-damage corresponding to the candidate response signal and the second pseudo-damage corresponding to the target response signal.

3. The method according to claim 1, characterized in that, Before simulating the kinematic model of the vehicle based on the initial load signal, the method further includes: The initial load signal is determined based on the material parameters of the bushing and the structural parameters corresponding to the vehicle's suspension system. The material parameters include at least one of tensile and compressive strength and shear strength; The structural parameters include at least one of the following: bushing outer diameter, bushing inner diameter, distance from the bushing stress point to the installation reference surface, installation preload, and suspension stiffness.

4. The method according to claim 3, characterized in that, The load data corresponding to each sampling moment in the initial load signal includes at least one of axial load, radial load, torsional load, and overturning moment. Determining the initial load signal based on the material parameters of the bushing and the structural parameters corresponding to the vehicle's suspension system includes: The effective bearing area and torsional section modulus of the bushing are determined based on the inner diameter and outer diameter of the bushing. The axial load is determined based on the axial empirical coefficient, the tensile and compressive strength, and the effective bearing area of ​​the bushing. The radial load is determined based on the radial empirical coefficient, the suspension stiffness, and the installation preload. The torsional load is determined based on the torsional empirical coefficient, the shear strength, and the torsional section modulus of the bushing. The overturning moment is determined based on the overturning empirical coefficient, the radial load, and the distance.

5. The method according to any one of claims 1-4, characterized in that, The target load spectrum is determined based on the target response signal corresponding to the vehicle's operation under each preset working condition. After determining the target load spectrum corresponding to the bushing in the vehicle based on the candidate load signal, the method further includes: Based on the preset number of cycles corresponding to each preset working condition in the entire life cycle of the vehicle and the target load spectrum, the dynamic load spectrum of the bushing in the entire life cycle of the vehicle is determined. The dynamic load spectrum is processed to obtain multiple initial block load spectra, wherein each initial block load spectrum contains at least one load amplitude, the mean value corresponding to the load amplitude, and the number of cycles; Based on the third difference between every two initial block load spectra, the multiple initial block load spectra are processed to determine the target block load spectra; Based on the target block load spectrum, the target load amplitude and the corresponding target number of cycles for bushing durability testing are determined.

6. The method according to claim 5, characterized in that, The third difference includes the first difference and the second difference. The step of processing multiple initial block load spectra based on the third difference between every two initial block load spectra to determine the target block load spectrum includes: Based on each load amplitude and the corresponding number of cycles, determine the third pseudo-damage corresponding to each load amplitude; The load amplitude and the corresponding mean of the third pseudo-damage in each initial block load spectrum are determined as the equivalent load amplitude and equivalent mean of the initial block load spectrum. Determine the first difference between the equivalent load amplitudes corresponding to every two initial block load spectra, and the second difference between the equivalent mean values; The two initial block load spectra corresponding to the first difference being less than the first value and the second difference being less than the second value are merged into a single target block load spectrum.

7. The method according to claim 6, characterized in that, The step of determining the target load amplitude and corresponding target cycle number for the bushing durability test based on the target block load spectrum includes: The largest equivalent load amplitude in the target block load spectrum is determined as the target load amplitude; Based on the third pseudo-damage corresponding to each load amplitude in each target block load spectrum, determine the fourth pseudo-damage corresponding to each target block load spectrum; Based on the target load amplitude corresponding to each target block load spectrum and the fourth pseudo-damage, determine the initial number of cycles corresponding to the target load amplitude; The initial number of cycles is optimized to determine the target number of cycles, so as to minimize the value of the optimization function. The optimization function includes the absolute value of the difference between the total pseudo-damage and the experimental pseudo-damage corresponding to the dynamic load spectrum, and the test duration. The experimental pseudo-damage and the test duration are determined based on the target load amplitude and the optimized initial number of cycles.

8. A device for determining bushing load, characterized in that, The bushing load determination device includes: The first acquisition module is used to acquire the target response signal corresponding to the preset position during the vehicle's movement; The second acquisition module is used to simulate the kinematic model corresponding to the vehicle based on the initial load signal, so as to obtain the predicted response signal corresponding to the preset position in the kinematic model; The correction module is used to correct the load data corresponding to each sampling time in the initial load signal based on the first difference between the predicted response signal and the target response signal at each sampling time, so as to obtain the candidate load signal; The third acquisition module is used to simulate the kinematic model based on the candidate load signal to obtain the candidate response signal corresponding to the preset position in the kinematic model; A first determining module is used to determine a second difference between the candidate response signal and the target response signal; The second determining module is used to determine the target load spectrum corresponding to the bushing in the vehicle based on the candidate load signal when the second difference meets the preset conditions.

9. A device for determining bushing load, characterized in that, The device includes: 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 method for determining the bushing load as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, 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 bushing load determination method as described in any one of claims 1 to 7.

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