A method and system for simulating spring motion behavior

Abstract

The application relates to a spring motion behavior simulation method and system. The spring motion behavior simulation method comprises the following steps: acquiring geometric defect feature data and assembly deviation feature data of a spring; constructing a spring digital model based on the geometric defect feature data and the assembly deviation feature data; predicting local coil contact and buckling deformation of the spring in the spring motion process based on the spring digital model, and quantifying nonlinear friction damping and dynamic effective stiffness variation of the spring. The application can more truly simulate the non-ideal behavior of the spring under the action of complex loads by integrating the actually existing geometric defects and assembly deviations into the digital model, improves the accuracy of design verification, and provides a reliable basis for performance optimization of a vehicle suspension system.

Description

Technical Field

[0001] This application relates to the field of spring design, and in particular to a method and system for simulating the motion behavior of springs. Background Technology

[0002] In mechanical system design, Computer-Aided Engineering (CAE) is a core tool for simulating suspension spring motion. By constructing an ideal 3D model, assigning standard material properties, and applying simplified loads, engineers can calculate spring compression, stress distribution, and fatigue life, providing fundamental performance references for early design and playing a crucial role in ensuring vehicle handling stability and ride comfort. However, real-world scenarios are far more complex than ideal assumptions. In the manufacturing process, even with high-precision production, issues such as localized uneven wire diameter, slight deviations in coil pitch, and imperfect end treatment can occur. During assembly, due to assembly tolerances, spring seat deviations, or operational differences, the spring axis may be misaligned with the theoretical suspension axis, and the end face may not be perfectly parallel to the spring seat, further introducing deviations.

[0003] When a vehicle is in motion, the dynamic composite load on the spring amplifies the effects of these deviations. These deviations cause the spring axis to buckle during compression, exhibiting a "banana-shaped" bend. This disrupts the coil spacing and coaxiality, causing adjacent coils that should maintain a gap to prematurely come into partial contact. The relative sliding in this contact state generates nonlinear frictional damping, the strength of which dynamically changes with the deformation state, contact area, and sliding speed, far exceeding the linear damping assumption of traditional models. This process also alters the spring's "effective stiffness." In ideal models, stiffness is constant or linear, but in reality, premature coil contact, the intervention of frictional damping, and overall buckling cause the spring force-displacement curve to exhibit complex nonlinearity, directly leading to deviations in the suspension system's comfort, handling, and shock absorption capabilities from ideal simulation results.

[0004] Therefore, the core limitation of current simulation methods lies in their inability to incorporate micro-manufacturing tolerances and macro-assembly deviations. Calculations based on perfect models and ideal assemblies cannot predict changes in coil contact, nonlinear damping, and stiffness during actual operation. This leads to a significant discrepancy between simulation results and actual performance under complex driving environments, affecting the accuracy of design verification and introducing uncertainty into performance optimization, making it difficult to fully guarantee the vehicle's adaptability and safety under operating conditions.

[0005] To address this, we propose a method and system for simulating the motion behavior of springs. Summary of the Invention

[0006] This application provides a method and system for simulating spring motion behavior, which at least solves the problem that existing spring motion behavior simulation methods cannot take into account micro-manufacturing tolerances and macro-assembly deviations, resulting in a significant gap between the simulation results and the actual performance of vehicles in complex driving environments, thus affecting the accuracy of design verification.

[0007] In a first aspect, this application provides a method for simulating the motion behavior of a spring, the method comprising the following steps: Obtain geometric defect feature data and assembly deviation feature data of the spring; A digital model of the spring is constructed based on the geometric defect feature data and the assembly deviation feature data; Based on the aforementioned digital model of the spring, the local coil contact and buckling deformation of the spring are predicted during the spring's movement, and the nonlinear frictional damping and dynamic effective stiffness changes of the spring are quantified.

[0008] Optionally, predicting local coil contact and buckling deformation of the spring during the spring's movement includes: The instantaneous geometric attitude and relative position of each coil of the spring are continuously monitored, and based on the instantaneous geometric attitude and relative position, the local deformation trend of each coil of the spring and the minimum distance between adjacent coils are calculated. When the minimum distance is less than the preset contact threshold, it is determined that the spring has local coil contact after buckling deformation, and the instantaneous time of the contact is recorded; Identify discrete points where local coil contact occurs and their respective coil regions, determine the coil contact region, and continuously track the relative movement of the coil contact region until the distance between the coils exceeds the preset contact threshold, in order to predict the duration of local coil contact of the spring after buckling deformation; Identify specific high-frequency dynamic load patterns and, based on the load patterns, the coil contact area, and the duration of the local coil contact, assess the impact on local wear and abnormal noise of the spring.

[0009] Optionally, identifying specific high-frequency dynamic load patterns includes: A multi-channel high-frequency acceleration sensor array is deployed, and vibration signals during vehicle operation are collected in real time based on the sensor array. The vibration signal is analyzed in time and frequency to identify high-frequency dynamic load events with a specific frequency range, and the instantaneous energy spectral density of the high-frequency dynamic load events is calculated to quantify the instantaneous amplitude of each high-frequency load event. Set the start and end timestamps of the load events, determine the duration of each high-frequency load event, and combine the spatial layout information of the sensor array to infer the spatial distribution characteristics of the high-frequency load on each component of the suspension system. By integrating the instantaneous amplitude, the event duration, and the spatial distribution characteristics, specific high-frequency dynamic load patterns can be identified.

[0010] Optionally, quantifying the nonlinear frictional damping and dynamic effective stiffness changes of the spring includes: The local coil contact is detected, and the degree of wear and foreign matter adhesion on the contact surface are evaluated; Based on the degree of wear and the adhesion of foreign objects, the local friction coefficient of the spring digital model is adjusted, and the instantaneous friction force is calculated based on the adjusted local friction coefficient and the pre-collected relative sliding speed between coils. The instantaneous frictional force is integrated into the digital model of the spring, and the vibrational energy of the spring is tracked. Based on the change in the vibrational energy, the contribution of frictional damping to vibration attenuation is quantified.

[0011] Optionally, detecting the local coil contact and evaluating the wear and foreign matter adhesion on the contact surface includes: The local coil contact is detected, and the micro-roughness evolution of the contact surface is simulated to obtain micro-roughness morphology data. The micro-roughness evolution includes: simulating the accumulation and distribution of foreign particles on the contact surface, and tracking the movement trajectory of foreign particles on the contact surface. The micro-roughness morphology data includes simulated wear morphology, simulated foreign object distribution, and simulated stick-slip phenomenon. The wear degree and foreign matter adhesion of the contact surface are evaluated based on the characteristics of the micro-roughness morphology data.

[0012] Optionally, simulating the micro-roughness evolution of the contact surface includes: The instantaneous contact pressure and relative sliding speed of the detection coil contact area are measured. Analyze the microstructure and surface hardness distribution of the spring material in the coil contact area; The abrasive wear rate, fatigue wear crack initiation and propagation rate are calculated based on the instantaneous contact pressure, the relative sliding speed, the grain structure, and the surface hardness distribution. Monitor the ambient humidity, temperature, and corrosive medium concentration in the coil contact area, and calculate the corrosion wear rate based on the ambient humidity, temperature, and corrosive medium concentration. The micro-roughness morphology data are updated by integrating the abrasive wear rate, the fatigue wear crack initiation and propagation rate, and the corrosion wear rate.

[0013] Optionally, the accumulation and distribution of the simulated foreign particles on the contact surface includes: The instantaneous vibration frequency and impact intensity of the coil contact area are detected, as well as the airflow velocity and airflow direction around the coil contact area; Based on the instantaneous vibration frequency, the impact intensity, the airflow velocity, and the airflow direction, the first mechanical data of the foreign object particle is calculated, wherein the first mechanical data includes the inertial force, gravity, aerodynamic force, collision force with the contact surface, and friction force with the contact surface of the foreign object particle. Based on the mechanical data, the movement trajectory of the foreign particles on the contact surface is tracked, and the packing density and spatial distribution map of the foreign particles on the contact surface are updated according to the movement trajectory.

[0014] Optionally, tracking the trajectory of foreign particles on the contact surface based on the mechanical data includes: The material properties, size, microstructure of the contact surface, and charge distribution of the foreign particles are detected. Calculate the van der Waals force and electrostatic force between the foreign particles based on their material properties and size. The adhesion force between the foreign particles and the contact surface is calculated based on the material properties of the foreign particles, the microstructure of the contact surface, and the charge distribution. By superimposing the van der Waals force, the electrostatic force, the adhesive force, and the first mechanical data, the second mechanical data of the foreign particles are obtained; Based on the second mechanical data, the instantaneous position and velocity of the foreign object particle are updated, thereby tracking the trajectory of the foreign object particle on the contact surface.

[0015] Optionally, updating the instantaneous position and velocity of the foreign particle based on the second mechanical data includes: The current shape and size of the foreign object particle are detected, and the instantaneous force area and instantaneous inertial characteristics of the foreign object particle are calculated based on the current shape and size. Based on the instantaneous force-bearing area, the aerodynamic force, the collision force with the contact surface, and the frictional force with the contact surface in the first mechanical data are recalculated, and based on the instantaneous inertial characteristics, the inertial force in the first mechanical data is recalculated. The second mechanical data is obtained by superimposing the recalculated first mechanical data, the van der Waals force, the electrostatic force, and the adhesive force. Based on the second mechanical data, the instantaneous position and velocity of the foreign object particle are updated.

[0016] Secondly, this application provides a spring motion behavior simulation system, the system comprising: The data acquisition module is used to acquire geometric defect feature data and assembly deviation feature data of the spring; A digital model building module is used to build a digital model of the spring based on the geometric defect feature data and the assembly deviation feature data; The motion behavior prediction module is used to predict the local coil contact and buckling deformation of the spring during the spring's motion based on the spring's digital model, and to quantify the changes in the spring's nonlinear friction damping and dynamic effective stiffness.

[0017] Compared with related technologies, the spring motion behavior simulation method and system provided in this application have at least the following technical advantages: By acquiring geometric defect characteristic data and assembly deviation characteristic data of the spring, and constructing a digital model of the spring based on these data, the method predicts local coil contact and buckling deformation of the spring during its movement, and quantifies the nonlinear frictional damping and dynamic effective stiffness changes of the spring. This method incorporates actual geometric defects and assembly deviations into the digital model, enabling a more realistic simulation of the non-ideal behavior of the spring under complex loads, namely, local coil contact caused by buckling, and the resulting nonlinear frictional damping and dynamically changing effective stiffness. This results in simulation results that closely match the performance of actual vehicles in complex driving environments, improving the accuracy of design verification and providing a reliable basis for performance optimization of vehicle suspension systems.

[0018] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating a method for simulating the motion behavior of a spring according to an exemplary embodiment.

[0020] Figure 2 This is one of the partial flowcharts illustrating step S3 according to an exemplary embodiment.

[0021] Figure 3 This is a partial flowchart illustrating step S34 according to an exemplary embodiment.

[0022] Figure 4 This is a second partial flowchart of step S3 according to an exemplary embodiment.

[0023] Figure 5 This is a partial flowchart illustrating step S31 according to an exemplary embodiment.

[0024] Figure 6 This is a partial flowchart illustrating step S311 according to an exemplary embodiment.

[0025] Figure 7 This is a block diagram illustrating a spring motion behavior simulation system according to an exemplary embodiment. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0027] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any creative effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0028] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0029] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0030] The core limitation of current simulation methods in related technologies lies in their inability to incorporate micro-manufacturing tolerances and macro-assembly deviations. Calculations based on perfect models and ideal assemblies cannot predict changes in coil contact, nonlinear damping, and stiffness during actual operation. This leads to a significant discrepancy between simulation results and actual performance under complex driving environments, affecting the accuracy of design verification and introducing uncertainty into performance optimization, making it difficult to fully guarantee the vehicle's adaptability and safety under operating conditions.

[0031] Based on the above, embodiments of the present invention provide a method and system for simulating spring motion behavior, which will be described in detail below with reference to specific embodiments and accompanying drawings.

[0032] Example 1 Embodiment 1 of the present invention provides a method for simulating the motion behavior of a spring. Figure 1 This is a flowchart illustrating a method for simulating the motion behavior of a spring according to an exemplary embodiment. Figure 1 As shown, the method includes: S1. Obtain the geometric defect feature data and assembly deviation feature data of the spring; In this embodiment, the geometric defect characteristic data of the spring refers to the microscopic or macroscopic geometric deviations generated during the manufacturing process, such as non-uniformity of wire diameter, deviation of coil pitch, and imperfections in end treatment. Geometric defect characteristic data can be obtained through high-precision 3D scanning, optical measurement, or X-ray tomography. The assembly deviation characteristic data of the spring, on the other hand, refers to the deviation from the ideal assembly state caused by factors such as tolerance accumulation, installation position offset, or angular tilt when the spring is installed into a mechanical system. Assembly deviation characteristic data can be obtained through post-assembly 3D measurement, mechanical sensor array detection, or image recognition technology. In this embodiment, the spring is obtained by performing a full-size scan of it using a high-precision 3D scanner to acquire its external geometric contour data, which is then compared with the ideal design model to identify geometric defects such as wire diameter, coil pitch, and end flatness. Furthermore, during the spring installation process, a laser displacement sensor or vision measurement system can be used to monitor the spring's installation position and orientation in real time, recording its deviation from the ideal assembly position, thereby obtaining assembly deviation characteristic data.

[0033] S2. Construct a digital model of the spring based on the geometric defect feature data and the assembly deviation feature data; In this embodiment, the spring digital model is a comprehensive virtual model that not only includes the ideal geometry and material properties of the spring, but also incorporates the aforementioned geometric defect feature data and assembly deviation feature data. This allows it to reflect the physical characteristics of a real spring with high fidelity and support complex mechanical simulation calculations. In constructing the spring digital model, firstly, finite element analysis (FEA) software is used to establish an initial geometric model of the spring. Then, the acquired geometric defect feature data, such as local non-uniformity of the coil pitch or minute variations in the wire diameter, is parametrically imported into the initial geometric model to locally correct its geometry. Next, assembly deviation feature data, such as the tilt angle of the spring axis or the non-parallelism between the end face and the spring seat, is applied as boundary conditions or initial displacement / rotation amounts to the corrected geometric model, thereby constructing a spring digital model that reflects the physical characteristics of a real spring. For example, non-uniform rational B-spline (NURBS) surface modeling technology can be used to accurately describe the complex geometric defects of spring steel wires. Combined with multibody dynamics (MBD) simulation software, assembly deviations can be used as constraints on the connection pair to construct a high-fidelity digital model of the spring.

[0034] S3. Based on the digital model of the spring, predict the local coil contact and buckling deformation of the spring during the spring's movement, and quantify the nonlinear friction damping and dynamic effective stiffness changes of the spring. In this embodiment, local coil contact refers to the phenomenon where, during the movement of the spring, adjacent coils that should maintain a gap become physically contacted in a localized area due to buckling deformation or geometric defects. This contact is not the general contact that occurs when the spring is compressed to its limit, but rather a localized and unintended contact induced by non-ideal factors.

[0035] Buckling deformation refers to the phenomenon that when a spring is subjected to axial load, its axis bends or becomes unstable, causing the spring to lose its linear stability as a whole or in part.

[0036] Nonlinear friction damping refers to the damping effect provided by the frictional force generated by the relative sliding between coils when local coil contact occurs. The characteristic of this damping is that its magnitude and direction are not simply linearly related to the relative velocity, but are complexly influenced by various factors such as contact pressure, contact area, surface roughness, material properties, and foreign matter adhesion.

[0037] Dynamic effective stiffness variation refers to the characteristic that, during the motion of a spring, due to local coil contact, buckling deformation, and the intervention of nonlinear frictional damping, the force-displacement relationship is no longer constant or a simple linear relationship, but exhibits dynamic changes with time, displacement, and load.

[0038] Specifically, the constructed digital spring model is first imported into a multibody dynamics simulation platform. Within this platform, simulated external loads and motion boundary conditions are applied, such as the dynamic loads borne by the suspension system during vehicle operation. During the simulation, the instantaneous geometric attitude and relative position of each coil of the spring are continuously monitored. When the distance between adjacent coils is less than a preset contact threshold, the system determines that local coil contact has occurred and records the instantaneous time, location, and duration of the contact. Simultaneously, by analyzing the degree of bending and deformation mode of the spring axis, the buckling deformation of the spring can be predicted. When local coil contact occurs, based on the relative sliding velocity and contact pressure of the contact area, combined with a preset friction coefficient model, the instantaneous friction force is calculated and applied as a nonlinear damping force to the digital spring model. By tracking the force-displacement response of the spring throughout its motion, the effective stiffness change of the spring can be dynamically calculated and quantified. For example, during the simulation, contact algorithms (such as the penalty function method or the Lagrange multiplier method) can be used to accurately simulate the contact behavior between coils, and friction models (such as the Coulomb friction model or more complex friction models) can be combined to calculate friction damping. By post-processing the simulation results, we can obtain the local coil contact pattern, buckling deformation, nonlinear friction damping curve, and dynamic effective stiffness curve of the spring at different motion stages.

[0039] The technical solution of the above embodiments, by acquiring geometric defect feature data and assembly deviation feature data of the spring, and constructing a digital model of the spring based on these data, can more accurately simulate the motion behavior of the spring under actual working conditions. Specifically, when acquiring the geometric defect feature data and assembly deviation feature data of the spring, this application can comprehensively capture the non-ideal factors generated during the manufacturing and installation process of the spring, laying the foundation for subsequent accurate modeling. These data make the spring digital model no longer an idealized abstraction, but can reflect the physical characteristics of the real spring with high fidelity. Subsequently, based on the spring digital model, when predicting the local coil contact and buckling deformation of the spring during the spring's movement, and quantifying the nonlinear friction damping and dynamic effective stiffness changes of the spring, this application can deeply analyze the nonlinear behavior of the spring under complex loads. Finally, by predicting the local coil contact and buckling deformation, key failure modes and performance degradation mechanisms that cannot be captured by traditional ideal models can be identified; at the same time, quantifying the nonlinear friction damping and dynamic effective stiffness changes makes the evaluation of the spring's energy dissipation and mechanical response more accurate, thereby enabling more accurate prediction of the spring's performance under actual working conditions.

[0040] In one possible design, Figure 2 This is one of the partial flowcharts illustrating step S3 according to an exemplary embodiment. (Refer to the attached diagram.) Figure 2 Step S3 includes: S301. Continuously monitor the instantaneous geometric attitude and relative position of each coil of the spring, and calculate the local deformation trend of each coil of the spring and the minimum distance between adjacent coils based on the instantaneous geometric attitude and the relative position. In this embodiment, a high-precision sensor (e.g., a laser displacement sensor, an optical tracking system, or a virtual sensor integrated into a digital model) is used to acquire in real time the three-dimensional shape of the spring during its motion, the spatial coordinates of each coil, and its position relative to other coils. Based on these instantaneous geometric attitude and relative position data, geometric algorithms or finite element analysis methods can be used to calculate the local bending, torsion, and other deformation trends of each coil, and to accurately calculate the minimum distance between any two adjacent coils.

[0041] S302. When the minimum distance is less than the preset contact threshold, determine the local coil contact that occurs after the spring is bent and deformed, and record the instantaneous time of the contact. In this embodiment, the preset contact threshold is typically set to a very small positive value, such as 0.01 mm to 0.1 mm, to account for numerical calculation errors or microscopic surface roughness, ensuring accurate identification before or during actual physical contact. Once contact is determined to have occurred, the system records the precise instantaneous time of the contact, providing a basis for subsequent contact duration analysis.

[0042] S303. Identify the discrete points where the local coil contact occurs and their respective coil regions, determine the coil contact region, and continuously track the relative movement of the coil contact region until the distance between the coils exceeds the preset contact threshold, so as to predict the duration of the local coil contact of the spring after buckling deformation. In this embodiment, by analyzing the contact judgment results, all discrete points where contact occurs are clustered to determine the specific contact area. Subsequently, the relative motion of the coil contact area is continuously tracked until the distance between the coils exceeds the preset contact threshold again, thereby predicting the duration of local coil contact after the spring undergoes buckling deformation.

[0043] S304. Identify specific high-frequency dynamic load patterns, and based on the load patterns, the coil contact area, and the duration of the local coil contact, evaluate the impact on local wear and abnormal noise of the spring; In this embodiment, identifying specific high-frequency dynamic load patterns involves performing spectral analysis on the external excitation signal to identify high-frequency vibration or impact loads that may lead to contact and wear of the spring coil. Subsequently, based on the identified load patterns, the determined coil contact area, and the predicted duration of local coil contact, the impact of localized wear and abnormal noise on the spring can be evaluated. For example, by establishing a wear model or an abnormal noise prediction model and using these parameters as input, the potential amount of wear and the likelihood and intensity of abnormal noise occurrence can be quantified.

[0044] The technical solution of the above embodiments, by continuously monitoring the instantaneous geometric attitude and relative position of each coil of the spring, and calculating the local deformation trend and the minimum distance between adjacent coils, can capture coil contact that may occur during the spring's movement in real time and accurately. First, by setting a preset contact threshold, the occurrence of local coil contact can be accurately determined, and its instantaneous time can be recorded, providing a time reference for subsequent contact analysis. Furthermore, by identifying contact discrete points and coil regions, and continuously tracking their relative motion, this application can predict the duration of local coil contact, which is crucial for understanding the dynamic characteristics of contact events. Finally, by combining specific high-frequency dynamic load modes, this application can comprehensively evaluate the potential impact of local coil contact on local spring wear and abnormal noise, thereby identifying and resolving potential problems in advance during the design and operation phases.

[0045] In one possible design, Figure 3 This is a partial flowchart illustrating step S34 according to an exemplary embodiment. (Refer to the attached diagram.) Figure 3 Step S34 includes: S341. Deploy a multi-channel high-frequency acceleration sensor array and collect vibration signals during vehicle operation in real time based on the sensor array; In this embodiment, multiple high-frequency acceleration sensors are first installed at key locations near the vehicle's suspension system or springs. These sensors are configured to collect vibration signals generated by the vehicle during driving in real time and continuously, thereby obtaining sufficiently rich raw vibration data with high time resolution.

[0046] S342. Perform time-frequency analysis on the vibration signal to identify high-frequency dynamic load events with a specific frequency range, calculate the instantaneous energy spectral density of the high-frequency dynamic load events, and quantify the instantaneous amplitude of each high-frequency load event. In this embodiment, the time-frequency analysis of the vibration signal can employ signal processing techniques such as Fourier transform, wavelet transform, or Hilbert-Huang transform to convert the acquired vibration signal from the time domain to the frequency domain, or perform joint time-frequency analysis. Through the above analysis, high-frequency dynamic load events occurring within a specific frequency range (e.g., frequencies related to spring resonance, coil contact, or abnormal noise) can be identified. Furthermore, the instantaneous energy spectral density is calculated for the identified high-frequency dynamic load events to quantify the instantaneous energy distribution of each high-frequency load event at the time of its occurrence, obtaining its instantaneous amplitude to characterize the load intensity.

[0047] S343. Set the start and end timestamps of the load events, determine the duration of each high-frequency load event, and infer the spatial distribution characteristics of the high-frequency load on each component of the suspension system by combining the spatial layout information of the sensor array. In this embodiment, the start and end times of each high-frequency load event are accurately marked using signal processing algorithms or preset thresholds, thereby determining the duration of each high-frequency load event. Simultaneously, by combining the spatial layout information of the sensor array, such as the specific installation position and orientation of each sensor in the suspension system, the spatial distribution characteristics of the high-frequency load on various components of the suspension system can be inferred, such as which component the load primarily acts on and its direction, thus obtaining the spatial information of the load.

[0048] S344. Integrate the instantaneous amplitude, the event duration, and the spatial distribution characteristics to identify specific high-frequency dynamic load patterns; In this embodiment, the load intensity, duration, and spatial location information obtained from the above analysis are comprehensively considered to identify high-frequency dynamic loads with specific patterns, such as periodic impact loads, random vibration loads, or harmonic loads of specific frequencies.

[0049] The technical solution described above, by deploying a multi-channel high-frequency acceleration sensor array, can comprehensively and in real-time capture complex vibration signals generated during vehicle operation. By performing time-frequency analysis on these vibration signals, high-frequency dynamic load events related to spring motion behavior can be accurately separated from background noise, and their instantaneous amplitudes can be quantified, thus avoiding ambiguity in load intensity estimation. Furthermore, by setting the start and end timestamps of load events, the duration of each high-frequency load event can be accurately determined, which is crucial for assessing wear accumulation under long-term action. Simultaneously, by combining the spatial layout information of the sensor array with inverse inference of the spatial distribution characteristics of the load, the assessment of localized spring wear and abnormal noise can take into account the specific location and direction of the load action, thereby improving the precision and accuracy of the assessment.

[0050] In one example, suppose we need to simulate the motion behavior of a car suspension spring under real-world driving conditions. First, an array of six high-frequency accelerometers is deployed at key locations such as the top of the suspension towers, the lower control arm connection point, and the upper and lower ends of the spring body. These sensors are configured to acquire vibration signals in real time at a sampling rate of 10kHz when the car is traveling at high speeds, traversing bumpy roads, or making sharp turns.

[0051] When a car traverses a bumpy road, a sensor array collects a series of high-frequency vibration signals. These raw signals are then input into a signal processing unit for short-time Fourier transform (STFT) time-frequency analysis. Through analysis, multiple high-frequency dynamic load events occurring in the 200Hz to 1000Hz frequency range can be identified. For example, at a certain moment, an impact event with a frequency of 500Hz and a duration of 50 milliseconds is identified. For each identified high-frequency load event, its instantaneous energy spectral density is calculated, thereby quantifying the instantaneous amplitude of the event; for example, the peak acceleration of an impact event reaches 5g.

[0052] Simultaneously, by setting the start and end points when the signal exceeds a preset threshold, the duration of each high-frequency load event can be precisely determined. Combined with pre-recorded spatial coordinate information of the sensor array, such as sensor A being located at the top of the suspension tower and sensor B being located at the upper end of the spring, it can be inferred that the 500Hz impact load mainly acts on the upper coil area of ​​the spring, and its main direction is vertical.

[0053] Ultimately, by integrating these instantaneous amplitudes, event durations, and spatial distribution characteristics (e.g., 5g peak, 50ms duration, and vertical impact on the upper coil of the spring), a specific high-frequency dynamic load pattern was identified. This pattern was then input into the spring's digital model to more accurately assess the wear of the spring's local coils and potential abnormal noises under this pattern. For example, it was predicted that under a specific impact pattern, the wear rate in the contact area of ​​the upper coil of the spring would increase significantly, potentially producing a high-frequency "squeaking" sound.

[0054] In one possible design, Figure 4 This is a second partial flowchart illustrating step S3 according to an exemplary embodiment. (Refer to the attached diagram.) Figure 4 Step S3 includes: S31. Detect the local coil contact and evaluate the wear level and foreign matter adhesion of the contact surface; In this embodiment, events of contact between coils are acquired using sensors or simulation methods. Subsequently, the degree of wear on the contact surfaces and the presence of foreign matter are evaluated to obtain physical state information of the contact area; the degree of wear refers to the loss of material or morphological changes on the contact surface, while the presence of foreign matter involves the accumulation of impurities such as dust and particles in the contact area.

[0055] S32. Based on the wear level and the foreign object adhesion, adjust the local friction coefficient of the spring digital model, and calculate the instantaneous friction force based on the adjusted local friction coefficient and the pre-collected relative sliding speed between coils. In this embodiment, adjusting the local friction coefficient aims to make the friction coefficient in the spring digital model more realistically reflect the friction characteristics of the actual contact surface. For example, wear may cause changes in surface roughness, and foreign objects may increase or decrease friction. Simultaneously, by combining the pre-collected relative sliding speeds between the coils, the instantaneous friction force can be calculated; this instantaneous friction force is an important component of the interaction force between the coils during spring movement.

[0056] S33. Integrate the instantaneous frictional force into the digital model of the spring, track the vibration energy of the spring, and quantify the contribution of frictional damping to vibration attenuation based on the change of the vibration energy; In this embodiment, the calculated instantaneous frictional force is integrated into the digital model of the spring, enabling the digital model to more accurately simulate the dynamic response of the spring. Subsequently, by tracking the vibration energy of the spring, the specific contribution of frictional damping to vibration attenuation can be observed. Based on the changes in vibrational energy, such as the energy dissipation rate, it can be directly used to quantify nonlinear frictional damping.

[0057] The technical solutions described above can more accurately quantify the nonlinear frictional damping and dynamic effective stiffness changes of a spring during its motion. Specifically, by considering the degree of wear and foreign object adhesion during local coil contact and dynamically adjusting the friction coefficient accordingly, the calculation of frictional force becomes more refined and realistic. This not only improves the accuracy of spring motion behavior simulation but also provides more reliable data support for predicting spring performance degradation, lifespan, and abnormal noises, thereby helping to optimize spring design and improve system reliability.

[0058] In one possible design, Figure 5 This is a partial flowchart illustrating step S31 according to an exemplary embodiment. (Refer to the attached diagram.) Figure 5 Step S31 includes: S311. Detect the local coil contact and simulate the micro-roughness evolution of the contact surface to obtain micro-roughness morphology data, wherein the micro-roughness evolution includes: simulating the accumulation and distribution of foreign particles on the contact surface, and tracking the movement trajectory of foreign particles on the contact surface; the micro-roughness morphology data includes simulated wear morphology, simulated foreign object distribution, and simulated stick-slip phenomenon. In this embodiment, a physical model and numerical methods are established to dynamically predict and reconstruct the changes in the microstructure of the spring coil contact area surface over time. The evolution of micro-roughness includes modeling the wear mechanisms of the contact surface material, such as abrasive wear, fatigue wear, and corrosive wear, to simulate the formation and development of the wear morphology. Simultaneously, it involves simulating the movement, accumulation, and distribution of foreign particles in the environment on the contact surface to reflect the influence of foreign particle distribution on surface properties. Furthermore, by simulating the stick-slip phenomenon at the contact interface, the nonlinear characteristics of friction behavior can be more realistically reflected, thus providing a dynamic and detailed description of the surface state and a data foundation for subsequent wear and foreign particle adhesion assessments.

[0059] Microscopic roughness morphology data refers to the quantitative information about the microscopic geometric features and material distribution of the contact surface obtained through the above simulation process. Specifically, simulated wear morphology refers to the microstructural features such as pits, scratches, and spalling caused by wear on the contact surface, obtained through numerical simulation; simulated foreign matter distribution refers to the distribution information of foreign matter particles on the contact surface, such as density, size, and location, obtained by simulating the movement and accumulation of foreign matter particles; simulated stick-slip phenomenon refers to the stick-slip behavior data obtained by simulating the nonlinear characteristics of the frictional force at the contact interface as a function of relative sliding velocity, such as the instantaneous fluctuation of the friction coefficient and the alternation of sliding and stagnation. These data together constitute a comprehensive description of the contact surface state.

[0060] S312. Evaluate the wear degree and foreign matter adhesion of the contact surface based on the characteristics of the micro-roughness morphology data; In this embodiment, based on the micro-roughness morphology data obtained from the above simulation, the wear degree and foreign matter adhesion of the contact surface are quantified through specific algorithms and evaluation models. For example, the wear degree can be evaluated by analyzing surface roughness parameters (such as Ra, Rz), wear volume, or wear depth in the simulated wear morphology data; the foreign matter adhesion can be evaluated by analyzing the foreign matter coverage, foreign matter particle size, and quantity in the simulated foreign matter distribution data; at the same time, by combining the data from the simulated stick-slip phenomenon, the influence of friction behavior on wear and foreign matter adhesion can be more comprehensively understood, thereby transforming the complex micro-simulation results into quantifiable evaluation indicators.

[0061] The technical solutions described above improve the accuracy and comprehensiveness of assessing the wear degree and foreign object adhesion of the local coil contact surface of a spring. By simulating the accumulation and distribution of foreign particles on the contact surface and tracking their movement trajectory, the influence of foreign objects on the contact interface can be dynamically captured, which is more comprehensive than simple static detection. Simultaneously, by simulating wear morphology and stick-slip phenomena, a deeper understanding of the physical changes of the contact surface under dynamic loads can be achieved, thus obtaining microscopic roughness morphology data that more closely approximates reality. It is precisely this refined simulation that allows the assessment of the wear degree and foreign object adhesion of the contact surface to be based on richer and more accurate microscopic information, thereby providing a more reliable basis for adjusting the local friction coefficient and calculating instantaneous friction force in the subsequent digital model of the spring.

[0062] In one example, suppose we need to simulate the motion behavior of a car suspension spring during long-term operation. First, when local coil contact occurs during spring movement, the system initiates a simulation of the micro-roughness evolution of the contact surface. Specifically, it simulates the accumulation and distribution of foreign particles (such as road dust, metal shavings, etc.) on the contact surface. This can be achieved by establishing a particle dynamics model, considering the inertial force, gravity, aerodynamic force, and collision and friction forces between the particles and the surface. Simultaneously, the trajectory of these foreign particles on the contact surface is tracked, for example, by describing the instantaneous position and velocity of the particles using Lagrangian or Eulerian methods. Furthermore, the wear process of the contact surface material is simulated, for example, by updating the surface morphology by calculating abrasive wear rate, fatigue wear crack initiation and propagation rate, and corrosion wear rate. These simulation processes collectively generate micro-roughness morphology data, including simulated wear morphology (such as surface roughness parameters, wear depth maps), simulated foreign object distribution (such as foreign object particle density maps, coverage), and simulated stick-slip phenomena (such as the fluctuation curve of friction force over time or displacement).

[0063] Finally, based on these detailed micro-roughness morphology data characteristics, such as analyzing the severity of wear morphology through image processing techniques or statistically analyzing the uniformity and coverage of foreign matter distribution, the wear degree and foreign matter adhesion of the contact surface are accurately assessed. These assessment results are then used to adjust the local friction coefficient in the spring digital model, thereby more accurately predicting the nonlinear friction damping and dynamic effective stiffness changes of the spring.

[0064] In one possible design, Figure 6 This is a partial flowchart illustrating step S311 according to an exemplary embodiment. (Refer to the attached diagram.) Figure 6 Step S311 includes: S3111, Detect the instantaneous contact pressure and relative sliding speed of the coil contact area; In this embodiment, the instantaneous contact pressure and relative sliding velocity are detected by integrating a finite element analysis (FEA) or multibody dynamics (MBD) simulation module into the spring digital model. The finite element analysis (FEA) or multibody dynamics (MBD) simulation module can calculate the local stress distribution of the coil at contact in real time, thereby obtaining the instantaneous contact pressure, and determine the relative sliding velocity based on the relative motion trajectory and velocity vector of the coil.

[0065] S3112. Analyze the microstructure and surface hardness distribution of the spring material in the coil contact area; In this embodiment, analysis is performed based on spring material property data obtained in advance through experimental testing or material databases. The spring material property data includes the material's grain size, grain boundary characteristics, phase composition, and surface Rockwell or Vickers hardness values ​​under different heat treatment conditions. In the digital model, these material properties can be mapped to specific grid points or cells in the coil contact area.

[0066] S3113. Calculate the abrasive wear rate, fatigue wear crack initiation and propagation rate based on the instantaneous contact pressure, the relative sliding speed, the grain structure and the surface hardness distribution. In this embodiment, the abrasive wear rate is calculated based on the Archard wear equation, which takes into account factors such as contact pressure, sliding distance, and material hardness. The fatigue wear crack initiation and propagation rates are evaluated based on fatigue life prediction models such as the Paris-Erdogan law or SN curves. These models combine parameters such as local stress cycles, material fatigue limit, and crack propagation threshold.

[0067] S3114. Monitor the ambient humidity, temperature and corrosive medium concentration in the contact area of ​​the coil, and calculate the corrosion wear rate based on the ambient humidity, the temperature and the corrosive medium concentration; In this embodiment, an environmental parameter module is introduced into the simulated environment to monitor the ambient humidity, temperature, and corrosive medium concentration in the coil contact area. The environmental parameter module simulates or receives input from external environmental sensors to reflect changes in humidity and temperature in the actual working environment of the spring, as well as the concentration of potentially corrosive substances (such as salt spray and acid rain). Based on the ambient humidity, temperature, and corrosive medium concentration, the corrosion wear rate is calculated using an electrochemical corrosion model or empirical corrosion rate formula, taking into account the influence of environmental factors on the material's corrosion behavior, such as corrosion current density, corrosion potential, and corrosion product formation rate.

[0068] S3115. The abrasive wear rate, the fatigue wear crack initiation and propagation rate, and the corrosion wear rate are fused together to update the micro-roughness morphology data; In this embodiment, the various wear rates calculated above are superimposed or weighted averaged to comprehensively reflect the contribution of different wear mechanisms to the morphology of the contact surface. The updated micro-roughness morphology data includes surface roughness parameters (such as Ra, Rz), wear depth distribution map, crack density, and size distribution.

[0069] The technical solution described above decomposes the micro-roughness evolution process into multiple mechanisms such as abrasive wear, fatigue wear, and corrosion wear, and establishes corresponding calculation models for each mechanism, thereby enabling a more comprehensive simulation of the actual wear process of the spring coil contact surface. Specifically, by detecting key parameters such as instantaneous contact pressure, relative sliding speed, material microstructure, and environmental conditions, and substituting them as inputs into their respective wear rate calculation models, the influence of different wear mechanisms on surface morphology can be quantified. Finally, by fusing these wear rates, the micro-roughness morphology data in the spring digital model can be dynamically updated, allowing the simulation results to more realistically reflect the wear state of the spring under complex working conditions.

[0070] In one possible design, in step S311, the accumulation and distribution of the simulated foreign particles on the contact surface includes: S311a. Detect the instantaneous vibration frequency and impact intensity of the coil contact area, as well as the airflow velocity and airflow direction around the coil contact area; In this embodiment, the instantaneous vibration frequency and impact intensity are detected by integrating virtual sensors into the digital spring model or by calibration using actual test data. This reflects the dynamic environment of the contact area and directly affects the movement of foreign particles. Simultaneously, the airflow velocity and direction around the coil contact area can be obtained through computational fluid dynamics (CFD) simulations or wind tunnel experimental data, used to describe the fluid environment in which the foreign particles reside.

[0071] S311b. Calculate the first mechanical data of the foreign object particle based on the instantaneous vibration frequency, the impact intensity, the airflow velocity, and the airflow direction, wherein the first mechanical data includes the inertial force, gravity, aerodynamic force, collision force with the contact surface, and friction force with the contact surface of the foreign object particle. In this embodiment, among the first mechanical data, the inertial force is related to the mass and acceleration of the foreign object particle; the gravity is related to the mass and gravitational acceleration of the foreign object particle; the aerodynamic force, such as air resistance and lift, is related to the airflow speed, the shape and size of the foreign object particle; the collision force with the contact surface is generated when the foreign object particle collides with the contact surface, and is related to the collision speed, material elasticity, etc.; the frictional force with the contact surface is generated when the foreign object particle slides relative to the contact surface, and is related to the contact pressure, the coefficient of friction, etc.

[0072] S311c. Based on the mechanical data, track the movement trajectory of the foreign particles on the contact surface, and update the packing density and spatial distribution map of the foreign particles on the contact surface according to the movement trajectory. In this embodiment, the first mechanical data obtained from the above calculation is used as input, and physical models such as Newton's second law are used to iteratively calculate the instantaneous position and velocity of the foreign particles on the contact surface, thereby simulating their motion trajectory. Furthermore, based on the motion trajectory, the packing density and spatial distribution map of the foreign particles on the contact surface are updated. By statistically analyzing the areas through which the foreign particles pass or remain at different times, the packing density on the contact surface is updated in real time. The spatial distribution map visually displays the distribution of foreign particles on the contact surface, helping to assess the impact of foreign object adhesion on wear and abnormal noise.

[0073] The technical solutions described above enable a refined simulation of the accumulation and distribution process of foreign particles on the contact surface of a spring coil. Specifically, by considering various dynamic environmental factors such as vibration, impact, and airflow, and calculating the various mechanical forces acting on the foreign particles, this embodiment can more accurately predict the trajectory of the foreign particles, thereby obtaining a more realistic accumulation density and spatial distribution map. This improves the accuracy of assessing the wear level of the contact surface and the adhesion of foreign particles, provides a more reliable quantitative basis for the nonlinear frictional damping and dynamic effective stiffness changes of the spring's motion behavior, and ultimately enhances the accuracy and reliability of the entire spring motion behavior simulation method.

[0074] In one possible design, in step S311, tracking the trajectory of the foreign particle on the contact surface based on the mechanical data includes: S311d, Detect the material properties, size, microstructure of the contact surface, and charge distribution of the foreign particles; In this embodiment, the results of the above detection provide necessary input parameters for subsequent calculations of the interaction forces between foreign particles and the adhesion forces between foreign particles and the contact surface. For example, the material properties and size of the foreign particles directly affect the magnitude of van der Waals forces and electrostatic forces, while the microstructure and charge distribution of the contact surface have a significant impact on the adhesion force.

[0075] S311e. Calculate the van der Waals force and electrostatic force between the foreign particles based on the material properties and size of the foreign particles. In this embodiment, van der Waals forces are short-range intermolecular forces, particularly significant when the foreign particles are small. Their magnitude is closely related to the dielectric constant of the particle material and the distance between the particles. Electrostatic forces, on the other hand, originate from the charge that may be present on the foreign particles or contact surfaces. Their range is relatively long, and they are inversely proportional to the amount of charge and the square of the distance between the particles. By accurately calculating these forces, the behavior of foreign particles when they approach or come into contact with each other can be simulated more realistically.

[0076] S311f. Calculate the adhesion force between the foreign particles and the contact surface based on the material properties of the foreign particles, the microstructure of the contact surface, and the charge distribution. In this embodiment, adhesive force is the key factor for foreign particles to adhere to the contact surface, combining van der Waals forces, electrostatic forces, and possibly capillary forces. The microstructure of the contact surface, such as roughness, affects the actual contact area, and thus the magnitude of the adhesive force. Charge distribution generates electrostatic attraction or repulsion, further affecting the adhesion effect.

[0077] S311g, superimposed with the van der Waals force, the electrostatic force, the adhesive force, and the first mechanical data, to obtain the second mechanical data of the foreign particles; In this embodiment, the first mechanical data mainly covers the mechanical effects at the macroscopic level, while van der Waals forces, electrostatic forces, and adhesive forces supplement the interactions at the microscopic level. By superimposing these forces, a more comprehensive and precise resultant force acting on the foreign particles can be obtained.

[0078] S311h: Based on the second mechanical data, update the instantaneous position and velocity of the foreign object particle, thereby tracking the movement trajectory of the foreign object particle on the contact surface; In this embodiment, the trajectory of the foreign particles can more accurately reflect their real behavior under complex force fields, thus providing a more reliable basis for subsequent simulation of the packing density and spatial distribution of foreign particles on the contact surface.

[0079] The technical solutions described above can significantly improve the accuracy of predicting the trajectory of foreign particles in spring motion behavior simulation. By comprehensively considering van der Waals forces, electrostatic forces, and adhesive forces at the microscopic level, the simulation results can more realistically reflect the complex behavior of foreign particles on the contact surface, such as particle aggregation, adhesion, sliding, or jumping. This helps to more accurately predict the packing density and spatial distribution of foreign particles and provides a more reliable data foundation for assessing problems such as localized wear and abnormal noise, thereby guiding spring design optimization and fault diagnosis.

[0080] In one example, suppose there are fine dust particles with a diameter of several micrometers in the contact area of ​​the spring coil. Considering only macroscopic mechanical data, these particles might be simulated as simply moving with the airflow or bouncing away after a collision.

[0081] The method described in this application first detects the material properties (e.g., silica), size (e.g., 5 micrometers), microstructure of the contact surface (e.g., roughness of steel surface), and possible charge distribution of these dust particles. Based on this information, significant van der Waals forces between the dust particles can be calculated, causing the particles to attract each other and form clusters. Simultaneously, adhesive forces exist between the particles and the spring surface, making some particles difficult to detach after contact, instead adhering to or sliding along the surface. If the particles or surface are electrostatically charged, the electrostatic force will further affect their motion. By superimposing these microscopic forces with macroscopic forces such as inertial forces, gravity, and aerodynamic forces, the resulting second mechanical data can more accurately predict the actual trajectory of these dust particles, such as where they accumulate, what distribution pattern they form, and under what conditions they might be dislodged by vibration.

[0082] In one possible design, step S311h includes: S311h1, Detect the current shape and size of the foreign object particle, and calculate the instantaneous force area and instantaneous inertial characteristics of the foreign object particle based on the current shape and size; In this embodiment, in a simulated environment, the deformation of foreign particles under stress is predicted using particle dynamics models or finite element analysis, thereby obtaining their instantaneous shape and size. The instantaneous force-bearing area refers to the effective area of ​​the foreign particle interacting with the surrounding medium (such as airflow) or contact surface at a given moment. Instantaneous inertial characteristics include the instantaneous mass distribution and moment of inertia of the foreign particle.

[0083] S311h2. Based on the instantaneous force-bearing area, recalculate the aerodynamic force, the collision force with the contact surface, and the frictional force with the contact surface in the first mechanical data, and recalculate the inertial force in the first mechanical data based on the instantaneous inertial characteristics. In this embodiment, aerodynamic forces, impact forces, and frictional forces are recalculated based on the instantaneous force-bearing area to dynamically adapt to the real-time state of the foreign particles. For example, aerodynamic forces are adjusted according to changes in the windward area of ​​the foreign particles; impact forces and frictional forces are more accurately evaluated based on the actual geometry and contact area of ​​the contact surfaces. Similarly, recalculating inertial forces based on instantaneous inertial characteristics can more accurately reflect the dynamic response of foreign particles during acceleration or deceleration. For example, when a foreign particle tumbles or rotates, its moment of inertia affects its trajectory.

[0084] S311h3, superimpose the recalculated first mechanical data, the van der Waals force, the electrostatic force, and the adhesive force to update the second mechanical data; based on the second mechanical data, update the instantaneous position and velocity of the foreign particle; In this embodiment, the updated mechanical data can more realistically reflect the force situation of foreign particles in complex environments, thereby providing input for updating the instantaneous position and velocity of foreign particles.

[0085] The technical solution described above improves the accuracy and realism of foreign particle trajectory simulation by dynamically detecting the current shape and size of the foreign particles and adjusting their force-bearing area and inertial characteristics in real time. Specifically, when the shape and size of the foreign particles change, their interaction area with the surrounding medium and their own inertial response also change. This solution can re-evaluate the first mechanical data, such as aerodynamic force, collision force, friction force, and inertial force, by accurately calculating these instantaneous force-bearing areas and instantaneous inertial characteristics. Therefore, by superimposing these updated first mechanical data with van der Waals forces, electrostatic forces, and adhesive forces, more accurate second mechanical data can be obtained. Based on this more accurate second mechanical data, the instantaneous position and velocity of the foreign particles are updated more realistically, thereby ensuring the accuracy of foreign particle trajectory tracking and improving the reliability of simulating the packing density and spatial distribution of foreign particles on the contact surface.

[0086] In summary, the spring motion behavior simulation method provided by this invention acquires geometric defect feature data and assembly deviation feature data of the spring, and constructs a digital model of the spring based on these data. This allows for the prediction of local coil contact and buckling deformation during spring motion, and the quantification of the spring's nonlinear frictional damping and dynamic effective stiffness changes. By incorporating actual geometric defects and assembly deviations into the digital model, this method can more realistically simulate the non-ideal behavior of the spring under complex loads, namely, local coil contact caused by buckling, and the resulting nonlinear frictional damping and dynamically changing effective stiffness. This makes the simulation results highly consistent with the performance of actual vehicles in complex driving environments, significantly improving the accuracy of design verification and providing a reliable basis for optimizing the performance of vehicle suspension systems.

[0087] Example 2 Embodiment 2 of the present invention provides a spring motion behavior simulation system. Figure 7 This is a block diagram illustrating a spring motion behavior simulation system according to an exemplary embodiment. (Refer to the attached diagram.) Figure 7 The system includes: Data acquisition module 01 is used to acquire geometric defect feature data and assembly deviation feature data of the spring; Digital model construction module 02 is used to construct a digital model of the spring based on the geometric defect feature data and the assembly deviation feature data; The motion behavior prediction module 03 is used to predict the local coil contact and buckling deformation of the spring during the spring's motion based on the spring's digital model, and to quantify the changes in the spring's nonlinear friction damping and dynamic effective stiffness.

[0088] In summary, the spring motion behavior simulation method and system provided in this embodiment of the invention have the following features: Data acquisition module 01 is responsible for comprehensively collecting the non-ideal physical characteristics of the spring, providing a realistic data foundation for subsequent modeling. Digital model construction module 02 integrates this realistic data into the virtual spring model, ensuring the model's accuracy and high fidelity. Based on this, motion behavior prediction module 03 can utilize the virtual spring model to predict and quantify the complex nonlinear behavior of the spring during its dynamic motion, thereby overcoming the shortcomings of traditional simulation methods in considering actual manufacturing and assembly deviations, significantly improving the reliability of simulation results and the ability to predict actual working conditions.

[0089] By acquiring geometric defect characteristic data and assembly deviation characteristic data of the spring, and constructing a digital model of the spring based on these data, the local coil contact and buckling deformation of the spring during its movement can be predicted, and the nonlinear frictional damping and dynamic effective stiffness changes of the spring can be quantified. This application incorporates actual geometric defects and assembly deviations into the digital model, thereby enabling a more realistic simulation of the non-ideal behavior of the spring under complex loads, namely, local coil contact caused by buckling, and the resulting nonlinear frictional damping and dynamically changing effective stiffness. This makes the simulation results highly consistent with the performance of actual vehicles in complex driving environments, significantly improving the accuracy of design verification and providing a reliable basis for performance optimization of vehicle suspension systems.

[0090] Example 3 Embodiment 3 of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the steps of the method provided in Embodiment 1.

[0091] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0092] In a possible implementation, the present invention can also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform steps implementing the method provided in Embodiment 1.

[0093] The program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0094] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0095] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for simulating the motion behavior of a spring, characterized in that, The method includes the following steps: Obtain geometric defect feature data and assembly deviation feature data of the spring; A digital model of the spring is constructed based on the geometric defect feature data and the assembly deviation feature data; Based on the aforementioned digital model of the spring, the local coil contact and buckling deformation of the spring are predicted during the spring's movement, and the nonlinear frictional damping and dynamic effective stiffness changes of the spring are quantified.

2. The method for simulating the motion behavior of a spring according to claim 1, characterized in that, The prediction of local coil contact and buckling deformation of the spring during the spring's movement includes: The instantaneous geometric attitude and relative position of each coil of the spring are continuously monitored, and based on the instantaneous geometric attitude and relative position, the local deformation trend of each coil of the spring and the minimum distance between adjacent coils are calculated. When the minimum distance is less than the preset contact threshold, it is determined that the spring has local coil contact after buckling deformation, and the instantaneous time of the contact is recorded; Identify discrete points where local coil contact occurs and their respective coil regions, determine the coil contact region, and continuously track the relative movement of the coil contact region until the distance between the coils exceeds the preset contact threshold, in order to predict the duration of local coil contact of the spring after buckling deformation; Identify specific high-frequency dynamic load patterns and, based on the load patterns, the coil contact area, and the duration of the local coil contact, assess the impact on local wear and abnormal noise of the spring.

3. The method for simulating spring motion behavior according to claim 2, characterized in that, The identification of specific high-frequency dynamic load patterns includes: A multi-channel high-frequency acceleration sensor array is deployed, and vibration signals during vehicle operation are collected in real time based on the sensor array. The vibration signal is analyzed in time and frequency to identify high-frequency dynamic load events with a specific frequency range, and the instantaneous energy spectral density of the high-frequency dynamic load events is calculated to quantify the instantaneous amplitude of each high-frequency load event. Set the start and end timestamps of the load events, determine the duration of each high-frequency load event, and combine the spatial layout information of the sensor array to infer the spatial distribution characteristics of the high-frequency load on each component of the suspension system. By integrating the instantaneous amplitude, the event duration, and the spatial distribution characteristics, specific high-frequency dynamic load patterns can be identified.

4. The method for simulating spring motion behavior according to claim 2, characterized in that, The quantification of the nonlinear frictional damping and dynamic effective stiffness changes of the spring includes: The local coil contact is detected, and the degree of wear and foreign matter adhesion on the contact surface are evaluated; Based on the degree of wear and the adhesion of foreign objects, the local friction coefficient of the spring digital model is adjusted, and the instantaneous friction force is calculated based on the adjusted local friction coefficient and the pre-collected relative sliding speed between coils. The instantaneous frictional force is integrated into the digital model of the spring, and the vibrational energy of the spring is tracked. Based on the change in the vibrational energy, the contribution of frictional damping to vibration attenuation is quantified.

5. The method for simulating spring motion behavior according to claim 4, characterized in that, The detection of the local coil contact and the assessment of the wear and foreign matter adhesion on the contact surface include: The local coil contact is detected, and the micro-roughness evolution of the contact surface is simulated to obtain micro-roughness morphology data. The micro-roughness evolution includes: simulating the accumulation and distribution of foreign particles on the contact surface, and tracking the movement trajectory of foreign particles on the contact surface. The micro-roughness morphology data includes simulated wear morphology, simulated foreign object distribution, and simulated stick-slip phenomenon. The wear degree and foreign matter adhesion of the contact surface are evaluated based on the characteristics of the micro-roughness morphology data.

6. The method for simulating the motion behavior of a spring according to claim 5, characterized in that, The simulation of the micro-roughness evolution of the contact surface includes: The instantaneous contact pressure and relative sliding speed of the detection coil contact area are measured. Analyze the microstructure and surface hardness distribution of the spring material in the coil contact area; The abrasive wear rate, fatigue wear crack initiation and propagation rate are calculated based on the instantaneous contact pressure, the relative sliding speed, the grain structure, and the surface hardness distribution. Monitor the ambient humidity, temperature, and corrosive medium concentration in the coil contact area, and calculate the corrosion wear rate based on the ambient humidity, temperature, and corrosive medium concentration. The micro-roughness morphology data are updated by integrating the abrasive wear rate, the fatigue wear crack initiation and propagation rate, and the corrosion wear rate.

7. The method for simulating the motion behavior of a spring according to claim 5, characterized in that, The accumulation and distribution of simulated foreign particles on the contact surface include: The instantaneous vibration frequency and impact intensity of the coil contact area are detected, as well as the airflow velocity and airflow direction around the coil contact area; Based on the instantaneous vibration frequency, the impact intensity, the airflow velocity, and the airflow direction, the first mechanical data of the foreign object particle is calculated, wherein the first mechanical data includes the inertial force, gravity, aerodynamic force, collision force with the contact surface, and friction force with the contact surface of the foreign object particle. Based on the mechanical data, the movement trajectory of the foreign particles on the contact surface is tracked, and the packing density and spatial distribution map of the foreign particles on the contact surface are updated according to the movement trajectory.

8. The method for simulating the motion behavior of a spring according to claim 7, characterized in that, The method of tracking the movement trajectory of foreign particles on the contact surface based on the mechanical data includes: The material properties, size, microstructure of the contact surface, and charge distribution of the foreign particles are detected. Calculate the van der Waals force and electrostatic force between the foreign particles based on their material properties and size. The adhesion force between the foreign particles and the contact surface is calculated based on the material properties of the foreign particles, the microstructure of the contact surface, and the charge distribution. By superimposing the van der Waals force, the electrostatic force, the adhesive force, and the first mechanical data, the second mechanical data of the foreign particles are obtained; Based on the second mechanical data, the instantaneous position and velocity of the foreign object particle are updated, thereby tracking the trajectory of the foreign object particle on the contact surface.

9. The method for simulating the motion behavior of a spring according to claim 8, characterized in that, The step of updating the instantaneous position and velocity of the foreign object particle based on the second mechanical data includes: The current shape and size of the foreign object particle are detected, and the instantaneous force area and instantaneous inertial characteristics of the foreign object particle are calculated based on the current shape and size. Based on the instantaneous force-bearing area, the aerodynamic force, the collision force with the contact surface, and the frictional force with the contact surface in the first mechanical data are recalculated, and based on the instantaneous inertial characteristics, the inertial force in the first mechanical data is recalculated. The second mechanical data is obtained by superimposing the recalculated first mechanical data, the van der Waals force, the electrostatic force, and the adhesive force. Based on the second mechanical data, the instantaneous position and velocity of the foreign object particle are updated.

10. A spring motion behavior simulation system, characterized in that, The system includes: The data acquisition module is used to acquire geometric defect feature data and assembly deviation feature data of the spring; A digital model building module is used to build a digital model of the spring based on the geometric defect feature data and the assembly deviation feature data; The motion behavior prediction module is used to predict the local coil contact and buckling deformation of the spring during the spring's motion based on the spring's digital model, and to quantify the changes in the spring's nonlinear friction damping and dynamic effective stiffness.

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