A simulation analysis method and system of a disc brake

Abstract

This invention discloses a simulation analysis method and system for disc brakes, relating to the field of disc brake simulation analysis technology. It solves the technical problem in existing technologies where simulation models lack a quantitative benchmarking and correction mechanism with bench test data, relying heavily on manual experience to adjust parameters. Specifically, the system uses a simulation analysis platform as its core, communicating between the simulation model construction unit and the stress distribution detection unit. Through 3D modeling, multibody dynamics simulation, flexible body coupling, and bench test benchmarking and correction, a high-fidelity brake dynamics simulation model is established. Based on this model, automatic performance determination is performed under multiple operating conditions, including emergency braking, continuous braking, and repeated braking. Furthermore, through finite element contact analysis and stress cloud map identification, accurate detection of stress concentration areas, stress variation patterns, and deformation risks in the brake disc is achieved, ultimately forming a closed-loop analysis system encompassing "modeling—simulation—verification—correction—stress analysis—operating condition classification—risk warning."

Description

Technical Field

[0001] This invention relates to the field of disc brake simulation analysis technology, specifically to a simulation analysis method and system for disc brakes. Background Technology

[0002] Disc brakes have been widely used in the chassis braking systems of passenger cars and commercial vehicles due to their advantages such as stable braking performance, good heat dissipation, and fast response. However, with the increasing demands for braking safety from lightweight vehicles, high power density, and intelligent driving, problems such as vibration, noise, thermal fade, stress concentration, and fatigue cracking of brakes under complex conditions such as emergency braking, continuous braking on long downhill slopes, and repeated braking in urban road conditions are becoming increasingly prominent. The traditional development model that relies on physical prototype bench tests and road tests has drawbacks such as long cycle time, high cost, difficulty in reproducing transient loads, and difficulty in monitoring stress distribution across the entire field.

[0003] In existing simulation technologies:

[0004] The simulation model lacks a quantitative benchmarking and correction mechanism with bench test data, and relies heavily on manual experience to adjust parameters, resulting in insufficient simulation reliability.

[0005] In terms of operating condition evaluation, there is a lack of standardized judgment logic and threshold system for three typical operating conditions: emergency, continuous, and repeated braking.

[0006] In stress analysis, most only output stress cloud diagrams and maximum stress values, lacking automatic identification of principal stresses, secondary stresses, and low-stress areas, as well as in-depth analysis of stress growth patterns, distribution density, and deformation correlations. This makes it difficult to effectively predict local stress anomalies and early failure risks, and thus fails to meet the high-precision, high-efficiency, and high-reliability development requirements of modern brakes.

[0007] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0008] The purpose of this invention is to solve the problems mentioned above by proposing a simulation analysis method and system for disc brakes.

[0009] The objective of this invention can be achieved through the following technical solutions:

[0010] A simulation analysis system for a disc brake, the system includes a simulation analysis platform, and the simulation analysis platform is communicatively connected to a simulation model building unit and a stress distribution detection unit;

[0011] The simulation model building unit constructs a three-dimensional geometric simulation solid model, retains key features, imposes constraints according to the actual assembly relationship, imports the three-dimensional solid model into the simulation environment, and removes details that affect the model. Boundary conditions and kinematic pair constraints are established, motion analysis is performed simultaneously, simulation conditions of the simulation solid model are constructed, bench tests are conducted for verification, and the simulation solid model is inspected and corrected. Finally, braking performance simulation analysis is performed based on the corrected simulation solid model.

[0012] After the braking performance simulation analysis is completed and passes the analysis, the stress distribution detection unit constructs a contact analysis model based on the current simulation entity model, and performs stress distribution detection through the contact analysis model.

[0013] Furthermore, the bench test verification process is as follows:

[0014] The collected braking torque and brake disc temperature were labeled as characteristic parameters; the vibration acceleration and braking distance were labeled as effect parameters.

[0015] Select any characteristic parameter type to construct a characteristic parameter curve, and select any effect parameter to construct an effect parameter curve; create a simulation curve group;

[0016] Based on the test results obtained from bench tests, the corresponding characteristic parameter curves and effect parameter curves are extracted to form a test curve group.

[0017] Furthermore, the simulation curve group and the experimental curve group are compared with the same type of curves, the range of the back-and-forth span between the peak and valley values ​​of the curves is recorded, and the slope peaks of the simulation curve group and the experimental curve group are selected from the back-and-forth span, and the locations of the slope peaks of each type are determined to construct a set of peak fluctuation time points.

[0018] If the distribution density of the fluctuation points corresponding to the simulated curve group within the peak fluctuation point set is inconsistent with the distribution density of the fluctuation points corresponding to the experimental curve group, and the distribution density deviation exceeds the distribution density deviation threshold, it is inferred that the current simulated curve group is abnormal compared with the verification curve group, and the simulation entity model is corrected; the distribution density is represented by the number of fluctuation points within the set threshold time period;

[0019] If the distribution density of the fluctuation points corresponding to the fluctuation points in the simulated curve group is consistent with the distribution density of the fluctuation points corresponding to the experimental curve group, and the number of values ​​in the non-intersecting span between the peak and valley values ​​of the simulated curve group and the experimental curve group exceeds the value number threshold, then the simulation entity model is corrected.

[0020] Furthermore, the model correction process involves adjusting parameters and re-simulating until the error between the simulation results and the experimental data is controlled.

[0021] Furthermore, the process of braking performance simulation analysis is as follows:

[0022] After completing the correction or when no correction is needed, it is determined that the current simulation entity model meets the actual simulation requirements. During the bench test verification process, the characteristic parameters and effect parameters collected from the simulation entity model are compared and analyzed.

[0023] The boundary conditions and kinematic pair constraints of the current simulation entity model remain unchanged, and the simulation conditions are divided into emergency braking, continuous braking and repeated braking.

[0024] In emergency braking scenarios, the excess of characteristic parameters and corresponding braking demand parameter thresholds is collected, and the time delay for the effect parameters to reach the braking effect parameter thresholds is obtained, specifically the excess time between the actual time and the emergency braking time.

[0025] If the excess of the characteristic parameter and the corresponding braking demand parameter threshold exceeds the excess threshold, and there is no time delay for the effect parameter to reach the braking effect parameter threshold, then an emergency braking fulfillment signal is generated and sent to the simulation analysis platform; if the excess of the characteristic parameter and the corresponding braking demand parameter threshold does not exceed the excess threshold, or there is a time delay for the effect parameter to reach the braking effect parameter threshold, then an emergency braking anomaly signal is generated and sent to the simulation analysis platform.

[0026] Furthermore, in the continuous braking scenario, the interval deviation between the collected characteristic parameters and the corresponding braking requirement parameter threshold is used to obtain the frequency of numerical fluctuation of the braking effect parameter.

[0027] If the interval deviation is lower than the interval deviation threshold and the numerical fluctuation frequency is lower than the fluctuation frequency threshold, then the continuous braking satisfaction signal is sent to the simulation analysis platform; if the interval deviation is not lower than the interval deviation threshold or the numerical fluctuation frequency is not lower than the fluctuation frequency threshold, then the continuous braking satisfaction signal is generated and sent to the simulation analysis platform.

[0028] In the scenario of repeated braking, the interval between the characteristic parameters and the corresponding braking demand parameter thresholds at adjacent time moments is obtained, and the peak value of the fluctuation span of the corresponding effect parameters at adjacent time moments is also obtained.

[0029] If the interval between the characteristic parameter and the corresponding braking demand parameter threshold at adjacent time points exceeds the interval floating span threshold, or the peak value of the fluctuation span of the corresponding effect parameter at adjacent time points exceeds the peak value of the fluctuation span, then a repetitive braking anomaly signal is generated and sent to the simulation analysis platform; if the interval between the characteristic parameter and the corresponding braking demand parameter threshold at adjacent time points does not exceed the interval floating span threshold, and the peak value of the fluctuation span of the corresponding effect parameter at adjacent time points does not exceed the peak value of the fluctuation span, then a repetitive braking satisfaction signal is generated and sent to the simulation analysis platform.

[0030] Furthermore, the process of the stress distribution detection unit is as follows:

[0031] Based on the simulated solid model, geometric features are extracted; geometric cleanup is performed on the model.

[0032] Contact pair configuration: The brake disc friction surface is the primary surface, and the friction lining is the secondary surface;

[0033] Construct a contact analysis model;

[0034] The stress at various locations on the brake disc surface is obtained and a stress cloud map is constructed. The location of maximum stress is identified based on the stress cloud map and marked as the principal stress location. A stress deviation threshold is set, and the stress values ​​of the locations surrounding the principal stress location are extracted. If the stress value deviation between the principal stress location and the surrounding location exceeds the stress deviation threshold, the corresponding surrounding location is marked as a low stress location. If the stress value deviation between the principal stress location and the surrounding location does not exceed the stress deviation threshold, the corresponding surrounding location is marked as a secondary stress location.

[0035] Furthermore, in the contact analysis model, if the peak increase frequency at the principal stress location exceeds the peak increase frequency threshold, or if the increase span of the stress distribution density exceeds the density increase span threshold, a stress risk signal is generated and sent to the simulation analysis platform; if the peak increase frequency at the principal stress location does not exceed the peak increase frequency threshold, and the increase span of the stress distribution density does not exceed the density increase span threshold, a stress stability signal is generated and sent to the simulation analysis platform.

[0036] After receiving a stress risk signal or a stress stability signal, the simulation analysis platform monitors the deformation of the brake disc friction surface and the brake disc flange.

[0037] Furthermore, if deformation occurs upon receiving a stress risk signal, the current simulation condition is marked as a stress transient impact condition, and the stress transient impact condition is continuously iterated and updated based on multiple simulation results to obtain the corresponding parameter range. If no deformation occurs upon receiving a stress risk signal, the current simulation condition is marked as a stress gradual impact condition, and the corresponding parameter range is also obtained through iterative updates. If deformation occurs upon receiving a stress stabilization signal, the current simulation condition is marked as a stress occasional impact condition, and this stress occasional impact condition is marked. When performing the same type of condition in a real scenario, continuous parameter monitoring is required. If no deformation occurs upon receiving a stress stabilization signal, the current simulation condition is marked as a stress controllable condition.

[0038] The simulation analysis platform stores each working condition type and, after completing the simulation analysis and testing, synchronizes each working condition type to the brake disc's working log and performs real-time comparison.

[0039] A simulation analysis method for disc brakes is provided, and the specific simulation analysis process is as follows:

[0040] Step 1: Constructing a 3D geometric simulation solid model;

[0041] Step 2: Simultaneously perform motion analysis, construct the simulation working conditions of the simulation entity model, and conduct bench tests for verification, and perform testing and correction of the simulation entity model;

[0042] Step 3: Perform braking performance simulation analysis based on the revised simulation entity model;

[0043] Step 4: The stress distribution detection unit constructs a contact analysis model based on the current simulation entity model;

[0044] Step 5: Detect stress distribution using a contact analysis model.

[0045] Compared with the prior art, the beneficial effects of the present invention are:

[0046] 1. In this invention, three-dimensional solids of components such as brake discs, friction linings, calipers, pistons, and brackets are accurately constructed using CAD software such as SolidWorks, UG, and CATIA. Key features such as ventilation slots, flange fillets, and lining chamfers are preserved to ensure the geometric fidelity of the model. Constraints are applied according to the actual vehicle assembly relationship, and the models are exported in STEP and Parasolid formats to improve multi-software compatibility and data interaction capabilities. After importing into multibody dynamics software, non-critical details are reasonably simplified to reduce the computational load while ensuring accuracy. Realistic material properties are assigned to key components such as brake discs and calipers, and sufficient order modal neutral files are generated using ANSYS and Abaqus to achieve coupling between rigid and flexible bodies, thereby improving the realism of dynamic simulation. By accurately defining revolute joints, sliding joints, contact joints, and boundary conditions such as braking pressure, wheel speed, and fixed constraints, the braking load and motion relationship of the actual vehicle can be reproduced, providing a high-precision basic model for subsequent multi-condition dynamic analysis and reducing simulation errors caused by structural simplification and constraint errors from the source.

[0047] 2. In this invention, data such as braking torque, temperature, vibration, and braking distance are collected through bench tests. These data are then divided into characteristic parameters and effect parameters and formed into curve sets. Quantitative indicators such as peak-valley span, slope peak value, distribution density of fluctuation points, and number of values ​​in non-intersecting intervals are used to achieve automatic alignment between simulation and experiment, replacing traditional manual judgment. By setting distribution density deviation thresholds and numerical quantity thresholds, the model correction logic is standardized and automated, quickly controlling simulation errors to within 5%. Judgment rules based on excess output, time delay, interval deviation, fluctuation frequency, floating span, and fluctuation peak value are established for emergency braking, continuous braking, and repeated braking, respectively. These rules can automatically output qualified / abnormal signals for each working condition, realizing quantitative evaluation of braking performance in multiple scenarios. This significantly improves the credibility of simulation results and engineering implementation capabilities, providing a reliable basis for overall system judgment.

[0048] 3. In this invention, a stress analysis geometric model is reconstructed based on a qualified dynamic model, retaining stress concentration areas and completing geometric cleanup to balance calculation accuracy and efficiency. Real material constitutive models such as elastoplastic and isotropic elasticity are adopted, combined with master-slave contact, penalty function / enhanced Lagrangian method, temperature-dependent friction coefficient, and hard contact settings to realistically reproduce the braking interface's pressing, slippage, and frictional thermodynamic behavior. Dynamic time-domain loads are imported and mapped onto the loading surface, applying centrifugal inertial forces and actual vehicle installation constraints to ensure the stress boundary is highly consistent with dynamic operating conditions. By generating stress cloud maps, the location of principal stresses is automatically identified, and secondary stress and low-stress regions are divided. Automatic determination of stress anomalies is achieved based on peak frequency increase and distribution density span thresholds. Stress results are linked with deformation monitoring to distinguish between four operating conditions: transient, slow-state, occasional, and controllable stress, achieving an upgrade from "viewing stress cloud maps" to "judging risk levels." This allows for precise location of potential brake disc failure areas, providing direct data support for structural reinforcement and lightweight optimization. Attached Figure Description

[0049] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0050] Figure 1 This is a system principle block diagram of the present invention;

[0051] Figure 2 This is a system flowchart of the stress distribution detection unit in this invention. Detailed Implementation

[0052] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0054] Please see Figures 1-2 As shown, a simulation analysis system for a disc brake is provided. The system includes a simulation analysis platform, which is communicatively connected to a simulation model building unit and a stress distribution detection unit.

[0055] The simulation analysis platform generates simulation model construction signals and sends them to the simulation model construction unit;

[0056] After receiving the simulation model construction signal, the simulation model construction unit constructs a simulation model for the disc brake.

[0057] 3D geometric solid model construction; tool selection: use 3D CAD software such as SolidWorks, UG or CATIA to build accurate geometric models of each component of the disc brake, including brake disc, friction pads, calipers, pistons, brake shoes, brackets, etc.

[0058] Key features such as brake disc ventilation slots, flange fillets, and lining chamfers should be retained to avoid oversimplification that could lead to simulation distortion.

[0059] Assembly constraints: Constraints are applied according to the actual assembly relationship to ensure that the relative positions of each component are consistent with the actual vehicle.

[0060] Interface Export: Export the assembly in STEP or Parasolid format to ensure compatibility with multibody dynamics software.

[0061] The CAD import interface of multibody dynamics software such as ADAMS and RecurDyn is used to import the 3D solid model into the simulation environment; details that have little impact on dynamic analysis, such as small holes, chamfers, and decorative structures on non-load-bearing surfaces, are removed to reduce the amount of calculation.

[0062] For components sensitive to mass and moment of inertia (such as brake discs and calipers), their geometric mass properties must be strictly preserved; material property assignment: assign real material parameters (density, elastic modulus, Poisson's ratio) to each component to ensure the accuracy of dynamic calculations;

[0063] Modal Neutral File (MNF) Generation:

[0064] Using finite element software such as ANSYS and Abaqus, modal analysis is performed on key flexible components (such as brake discs and caliper housings); a sufficient number of modes (usually ≥30) are extracted to generate modal neutral files (MNF).

[0065] Flexible body import: Import the MNF file into the multibody dynamics software, replace the corresponding rigid parts, and generate a flexible body model;

[0066] Coupling settings:

[0067] Define the connection relationships between flexible bodies and rigid components, such as the rigid connection between the brake disc and the wheel hub, and the hinged connection between the caliper and the bracket; ensure the correct transformation between the modal coordinates of the flexible body and the global coordinate system.

[0068] Boundary conditions and kinematic pair constraints are established;

[0069] Kinematic pair constraints:

[0070] Brake disc and hub: fixed pair (or rotating pair, considering coupling with the wheel).

[0071] Caliper and bracket: sliding pair (allows the caliper to move axially along the brake disc);

[0072] Piston and caliper: sliding pair (simulating the action of the piston pushing the liner);

[0073] Friction lining and brake disc: Contact pair (definition of frictional contact);

[0074] Load boundary conditions:

[0075] Braking pressure: Based on the brake line pressure or pedal force, it is converted into piston thrust and applied to the piston;

[0076] Wheel speed: applied to the brake disc in the form of rotational motion to simulate the vehicle's driving state;

[0077] Constraint reaction force: A fixed constraint is applied at the connection point between the bracket and the vehicle body to simulate the support of the vehicle body for the brake.

[0078] Motion and dynamics analysis settings:

[0079] Simulation operating condition definition:

[0080] Typical braking conditions: such as emergency braking (100km / h→0), continuous braking (downhill), and repeated braking (urban conditions).

[0081] Input parameters: initial velocity, braking pressure, braking time, road surface adhesion coefficient, etc.

[0082] Solver parameter settings:

[0083] Integration algorithm: Select a solver suitable for the contact problem (such as WSTIFF, GSTIFF).

[0084] Simulation step size: dynamically adjusted according to the working conditions. The step size during the contact phase should be small enough (e.g., 1e-4s) to capture transient impacts.

[0085] Convergence Criteria: Set the convergence accuracy for force and displacement to ensure calculation stability.

[0086] Output variable definition:

[0087] Time-domain data: braking torque, brake disc speed, piston displacement, acceleration and stress of each component.

[0088] Frequency domain data: vibration spectrum, noise source identification.

[0089] bench test verification

[0090] Test bench setup: A dedicated test bench for disc brakes is used to simulate the braking conditions of a real vehicle.

[0091] Data collection:

[0092] Measurements include: braking torque, brake disc temperature, vibration acceleration, and braking distance.

[0093] The collected braking torque and brake disc temperature were labeled as characteristic parameters; the vibration acceleration and braking distance were labeled as effect parameters.

[0094] Comparison: Select any characteristic parameter type to construct a characteristic parameter curve, and simultaneously select any effect parameter to construct an effect parameter curve; assemble a simulation curve group;

[0095] Based on the test results obtained from bench tests, extract the corresponding type of characteristic parameter curves and effect parameter curves, and build a test curve group.

[0096] The simulation curve group and the experimental curve group are compared with the same type of curves. The range of the back-and-forth span between the peak and valley values ​​of the curves is recorded. At the same time, the slope peaks of the simulation curve group and the experimental curve group are selected from the back-and-forth span, and the points of the slope peaks of each type are determined to construct a set of peak fluctuation time points.

[0097] If the distribution density of the fluctuation points corresponding to the simulated curve group within the peak fluctuation point set is inconsistent with the distribution density of the fluctuation points corresponding to the experimental curve group, and the distribution density deviation exceeds the distribution density deviation threshold, it is inferred that the current simulated curve group is abnormal compared with the verification curve group, and the simulation entity model is corrected; the distribution density is represented by the number of fluctuation points within the set threshold time period;

[0098] If the distribution density of the fluctuation points corresponding to the fluctuation points of the simulated curve group within the peak fluctuation point set is consistent with the distribution density of the fluctuation points corresponding to the fluctuation points of the experimental curve group, and the number of values ​​in the non-intersecting span between the peak and valley values ​​of the simulated curve group and the experimental curve group exceeds the value number threshold, then the simulation entity model is corrected.

[0099] In cases other than those described above, it is inferred that the current simulation entity model does not require modification.

[0100] It needs to be explained that the distribution density deviation threshold is derived from the fact that it characterizes the temporal consistency between the simulation and experimental curves at different points in time.

[0101] Acquisition method: Based on the repeatability of multiple bench test data of the same model brake, take 1.2 to 1.5 times the maximum distribution density deviation within the test group, or set to 5% to 10% according to the project acceptance requirements.

[0102] The origin of the non-intersecting span numerical value threshold: characterizes the difference between the peaks and valleys of the simulation and experimental curves; acquisition method: based on the enterprise's simulation accuracy standards, it is usually required that the numerical value deviation be ≤5%, and the corresponding curve overlap meets the requirements for engineering use.

[0103] Origin of simulation and experimental error control thresholds: Industry-standard simulation acceptance criteria;

[0104] Acquisition method: The relative error of key indicators such as bench braking torque, temperature, and displacement is ≤5%.

[0105] Model correction:

[0106] Adjust key parameters such as friction coefficient, contact stiffness, and material damping;

[0107] Repeat the simulation until the error between the simulation results and the experimental data is within 5%; that is, the deviation of the distribution density or the number of values ​​in the non-intersecting span range is within 5%.

[0108] After completing the correction or when no correction is needed, it is determined that the current simulation entity model meets the actual simulation requirements. During the bench test verification process, the characteristic parameters and effect parameters collected from the simulation entity model are compared and analyzed.

[0109] The boundary conditions and kinematic pair constraints of the current simulation entity model remain unchanged, and the simulation conditions are divided into emergency braking, continuous braking and repeated braking.

[0110] In emergency braking scenarios, the excess of characteristic parameters and corresponding braking demand parameter thresholds is collected, and the time delay for the effect parameters to reach the braking effect parameter thresholds is obtained, specifically the excess time between the actual time and the emergency braking time.

[0111] If the excess of the characteristic parameter and the corresponding braking requirement parameter threshold exceeds the excess threshold, and there is no time delay for the effect parameter to reach the braking effect parameter threshold, then it is inferred that the braking effect of the simulation entity model under the current working condition is qualified in the emergency braking scenario, and an emergency braking satisfaction signal is generated and sent to the simulation analysis platform.

[0112] If the excess of the characteristic parameter and the corresponding braking requirement parameter threshold does not exceed the excess threshold, or if there is a time delay in the effect parameter reaching the braking effect parameter threshold, it is inferred that the braking effect of the simulation entity model under the current working condition is unqualified in the emergency braking scenario, and an emergency braking abnormal signal is generated and sent to the simulation analysis platform.

[0113] In continuous braking scenarios, the interval deviation between the collected characteristic parameters and the corresponding braking requirement parameter threshold is used to obtain the frequency of numerical fluctuations of the braking effect parameters.

[0114] If the interval deviation is lower than the interval deviation threshold and the frequency of numerical fluctuation is lower than the fluctuation frequency threshold, then the continuous braking satisfies the signal and sends it to the simulation analysis platform.

[0115] If the interval deviation is not lower than the interval deviation threshold, or the frequency of numerical fluctuation is not lower than the fluctuation frequency threshold, it is inferred that there is a risk of braking speed reduction during braking, and a continuous braking satisfaction signal is generated and sent to the simulation analysis platform.

[0116] In the scenario of repeated braking, the interval between the characteristic parameters and the corresponding braking demand parameter thresholds at adjacent time moments is obtained, and the peak value of the fluctuation span of the corresponding effect parameters at adjacent time moments is also obtained.

[0117] If the interval between the characteristic parameter and the corresponding braking demand parameter threshold at adjacent time times exceeds the interval fluctuation span threshold, or if the peak value of the fluctuation span of the corresponding effect parameter at adjacent time times exceeds the peak value of the fluctuation span, then a repeated braking abnormal signal is generated and sent to the simulation analysis platform.

[0118] If the interval between the characteristic parameter and the corresponding braking demand parameter threshold at adjacent time moments does not exceed the interval fluctuation span threshold, and the peak value of the fluctuation span of the corresponding effect parameter at adjacent time moments does not exceed the peak value of the fluctuation span, then a repeated braking satisfaction signal is generated and sent to the simulation analysis platform.

[0119] It needs to be explained that the origin of the excess amount threshold and the time delay threshold is based on the regulatory braking distance requirements and the vehicle braking performance targets.

[0120] Acquisition method: It is derived from the braking performance indicators of vehicle manufacturers and the requirements of regulations such as GB7258. The excess amount threshold is generally taken as 5% to 10% of the required threshold, and the time delay threshold is usually taken as ≤50ms to 100ms.

[0121] The origins of the interval deviation threshold and fluctuation frequency threshold: to prevent brake fade and unstable braking force on long downhill slopes;

[0122] Acquisition method: In the continuous braking test on the bench, the steady-state fluctuation of the braking torque is ≤3%~5%** to be considered qualified, and the corresponding interval deviation threshold and fluctuation frequency threshold are set.

[0123] Origin of the interval fluctuation span threshold and the peak fluctuation span threshold: to evaluate performance drift and fatigue trend under repeated braking; Acquisition method: based on urban operating condition cyclic test data, the threshold is set when the parameter fluctuation between adjacent cycles is ≤5%~8%.

[0124] After receiving emergency braking satisfaction signal, continuous braking satisfaction signal and repeated braking satisfaction signal simultaneously, the simulation analysis platform outputs a normal braking performance signal from the current simulation entity model, and generates a stress distribution detection signal and sends it to the stress distribution detection unit.

[0125] After receiving the stress distribution detection signal, the stress distribution detection unit constructs a contact analysis model based on the current simulation entity model.

[0126] Geometric model reconstruction

[0127] Based on the simulation solid model, the geometric features of key components such as brake disc, friction lining, and caliper are extracted, with a focus on preserving stress concentration areas such as brake disc flange fillets and ventilation slots.

[0128] Perform geometric cleanup on the model, removing non-critical details such as small holes and chamfers, while ensuring the accuracy of key features such as flange fillets;

[0129] Material constitutive definition

[0130] Brake disc: An elastoplastic constitutive model is adopted, and parameters such as the elastic modulus, yield strength, and hardening curve of the brake disc material are input.

[0131] Friction lining: It adopts an isotropic elastic constitutive model and takes into account its compression characteristics under braking pressure.

[0132] Contact pair settings:

[0133] Master-slave contact definition: The brake disc friction surface is the master surface, and the friction lining is the slave surface. The contact is handled using a penalty function or the augmented Lagrange method.

[0134] Friction coefficient: Input the dynamic / static friction coefficients based on experimental data, and consider the effect of temperature on the friction coefficient;

[0135] Contact behavior: Set normal "hard contact" and tangential "penalty friction" to simulate the compression and sliding during braking.

[0136] Importing and applying dynamic boundary conditions:

[0137] Data source:

[0138] Extract time-domain load data from the multibody dynamics simulation results, including braking pressure, braking torque, brake disc speed, piston displacement, etc.

[0139] Extract load conditions at key time points, such as peak values ​​during emergency braking and steady-state conditions during continuous braking.

[0140] Boundary mapping: Mapping the nodal forces / torques output by multibody dynamics to the corresponding loading surfaces of the finite element model (such as the piston action surface, brake disc hub connection surface).

[0141] A rotational inertial force is applied to the brake disc to simulate the centrifugal effect during high-speed braking.

[0142] Constraints: Apply full or displacement constraints to the bolt holes connecting the brake disc flange and the wheel hub to simulate the actual vehicle installation state; apply fixed constraints to the caliper bracket to simulate its connection with the vehicle body.

[0143] Obtain the stress at various locations on the surface of the brake disc and construct a stress cloud map;

[0144] Identify the location of maximum stress based on the stress cloud map and mark it as the principal stress location; set a stress deviation threshold and extract the stress values ​​of the area surrounding the principal stress location. If the stress value deviation between the principal stress location and the surrounding area exceeds the stress deviation threshold, the corresponding surrounding area is marked as a low stress location; if the stress value deviation between the principal stress location and the surrounding area does not exceed the stress deviation threshold, the corresponding surrounding area is marked as a secondary stress location.

[0145] In the contact analysis model, if the peak increase frequency of the principal stress location exceeds the peak increase frequency threshold, or if the increase span of the stress distribution density exceeds the density increase span threshold, it is inferred that the stress analysis of the brake disc in the contact analysis model is abnormal, a stress risk signal is generated and sent to the simulation analysis platform.

[0146] If the peak increase frequency at the principal stress location does not exceed the peak increase frequency threshold, and the increase span of the stress distribution density at the stress location does not exceed the density increase span threshold, then it can be inferred that the stress analysis of the brake disc in the contact analysis model is normal, and a stress stability signal is generated and sent to the simulation analysis platform.

[0147] After receiving a stress risk signal or a stress stability signal, the simulation analysis platform monitors the deformation of the brake disc friction surface and the brake disc flange. It should be explained that when the simulation model is built, the load-bearing stress of the component material is compared with the actual load-bearing stress to determine whether deformation has occurred.

[0148] If deformation occurs when receiving a stress risk signal, it is inferred that the stress bearing is abnormal under the current simulation condition. The current simulation condition is marked as a stress transient impact condition, and the stress transient impact condition is continuously updated iteratively based on multiple simulation results to obtain the corresponding parameter range of the stress transient impact condition, such as the emergency braking peak value and other condition-related parameters. If no deformation occurs when receiving a stress risk signal, it is inferred that the stress bearing is affected under the current simulation condition. The current simulation condition is marked as a stress gradual impact condition, and the corresponding parameter range of the stress gradual impact condition is also obtained through iterative updates.

[0149] If deformation occurs when receiving a stress stabilization signal, it is inferred that the stress bearing is unstable under the current simulation condition. The current simulation condition is marked as a stress-induced accidental influence condition. When executing the same type of condition in the actual scenario, continuous parameter monitoring is required.

[0150] If no deformation occurs when the stress stabilization signal is received, it is inferred that the stress bearing is stable under the current simulation condition, and the current simulation condition is marked as a stress-controllable condition.

[0151] The simulation analysis platform stores various working conditions and determines whether the brake disc in the current simulation has stress risk based on the presence of stress risk signals. After completing the simulation analysis and detection, it synchronizes each working condition type to the brake disc's working log and performs real-time comparison to facilitate timely response and decision-making.

[0152] It needs to be explained that the stress deviation threshold is derived from distinguishing between the effective high-stress region and the low-stress transition region.

[0153] Acquisition method: Take 10%~20% of the maximum principal stress, and mark the area with deviation exceeding the threshold as a low stress area.

[0154] The origins of peak frequency threshold and distribution density span threshold: to predict local stress deterioration and fatigue risk;

[0155] Acquisition method: Using the failure samples from brake disc fatigue durability tests as negative samples, the stress growth rate and regional distribution are statistically analyzed, and a warning threshold is set.

[0156] A simulation analysis method for disc brakes is provided, and the specific simulation analysis process is as follows:

[0157] Step 1: Constructing a 3D geometric simulation solid model;

[0158] Step 2: Simultaneously perform motion analysis, construct the simulation working conditions of the simulation entity model, and conduct bench tests for verification, and perform testing and correction of the simulation entity model;

[0159] Step 3: Perform braking performance simulation analysis based on the revised simulation entity model;

[0160] Step 4: The stress distribution detection unit constructs a contact analysis model based on the current simulation entity model;

[0161] Step 5: Detect stress distribution using a contact analysis model.

[0162] Thresholds, preset values, preset ranges, etc. are set for result comparison and analysis to determine whether they are good or bad. The value of these thresholds is determined by a combination of large-scale model analysis of sample data and human experience. They can also be adjusted appropriately based on seasonal or common-sense influences.

[0163] Furthermore, the settings for weighting ratios, influence factors, etc., are based on the magnitude of each parameter's influence on the results. The specific values ​​are allocated to ultimately reflect the impact on the results. The settings for input and storage are also determined by a combination of large-scale model analysis of sample data and human experience. Appropriate adjustments can also be made based on seasonal or rational influence conditions.

[0164] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A simulation analysis system for a disc brake, characterized in that, The system includes a simulation analysis platform, which is connected to a simulation model building unit and a stress distribution detection unit via communication. The simulation model building unit constructs a three-dimensional geometric simulation solid model, retains key features, imposes constraints according to the actual assembly relationship, imports the three-dimensional solid model into the simulation environment, and removes details that affect the model. Boundary conditions and kinematic pair constraints are established, motion analysis is performed simultaneously, simulation conditions of the simulation solid model are constructed, bench tests are conducted for verification, and the simulation solid model is inspected and corrected. Finally, braking performance simulation analysis is performed based on the corrected simulation solid model. After the braking performance simulation analysis is completed and passes the analysis, the stress distribution detection unit constructs a contact analysis model based on the current simulation entity model, and performs stress distribution detection through the contact analysis model.

2. The simulation analysis system for a disc brake according to claim 1, characterized in that, The bench test verification process is as follows: The collected braking torque and brake disc temperature were labeled as characteristic parameters; the vibration acceleration and braking distance were labeled as effect parameters. Select any characteristic parameter type to construct a characteristic parameter curve, and select any effect parameter to construct an effect parameter curve; create a simulation curve group; Based on the test results obtained from bench tests, the corresponding characteristic parameter curves and effect parameter curves are extracted to form a test curve group.

3. The simulation analysis system for a disc brake according to claim 2, characterized in that, The simulation curve group and the experimental curve group are compared with the same type of curves. The range of the back-and-forth span between the peak and valley values ​​of the curves is recorded. At the same time, the slope peaks of the simulation curve group and the experimental curve group are selected from the back-and-forth span, and the points of the slope peaks of each type are determined to construct a set of peak fluctuation time points. If the distribution density of the fluctuation points corresponding to the simulated curve group within the peak fluctuation point set is inconsistent with the distribution density of the fluctuation points corresponding to the experimental curve group, and the distribution density deviation exceeds the distribution density deviation threshold, it is inferred that the current simulated curve group is abnormal compared with the verification curve group, and the simulation entity model is corrected; the distribution density is represented by the number of fluctuation points within the set threshold time period; If the distribution density of the fluctuation points corresponding to the fluctuation points in the simulated curve group is consistent with the distribution density of the fluctuation points corresponding to the experimental curve group, and the number of values ​​in the non-intersecting span between the peak and valley values ​​of the simulated curve group and the experimental curve group exceeds the value number threshold, then the simulation entity model is corrected.

4. The simulation analysis system for a disc brake according to claim 3, characterized in that, The model correction process involves adjusting parameters and re-simulating until the error between the simulation results and the experimental data is controlled.

5. The simulation analysis system for a disc brake according to claim 4, characterized in that, The process of braking performance simulation analysis is as follows: After completing the correction or when no correction is needed, it is determined that the current simulation entity model meets the actual simulation requirements. During the bench test verification process, the characteristic parameters and effect parameters collected from the simulation entity model are compared and analyzed. The boundary conditions and kinematic pair constraints of the current simulation entity model remain unchanged, and the simulation conditions are divided into emergency braking, continuous braking and repeated braking. In emergency braking scenarios, the excess of characteristic parameters and corresponding braking demand parameter thresholds is collected, and the time delay for the effect parameters to reach the braking effect parameter thresholds is obtained, specifically the excess time between the actual time and the emergency braking time. If the excess of the characteristic parameter and the corresponding braking demand parameter threshold exceeds the excess threshold, and there is no time delay for the effect parameter to reach the braking effect parameter threshold, then an emergency braking fulfillment signal is generated and sent to the simulation analysis platform; if the excess of the characteristic parameter and the corresponding braking demand parameter threshold does not exceed the excess threshold, or there is a time delay for the effect parameter to reach the braking effect parameter threshold, then an emergency braking anomaly signal is generated and sent to the simulation analysis platform.

6. The simulation analysis system for a disc brake according to claim 5, characterized in that, In continuous braking scenarios, the interval deviation between the collected characteristic parameters and the corresponding braking requirement parameter threshold is used to obtain the frequency of numerical fluctuations of the braking effect parameters. If the interval deviation is lower than the interval deviation threshold and the numerical fluctuation frequency is lower than the fluctuation frequency threshold, a continuous braking satisfaction signal is generated and sent to the simulation analysis platform; if the interval deviation is not lower than the interval deviation threshold or the numerical fluctuation frequency is not lower than the fluctuation frequency threshold, a continuous braking satisfaction signal is generated and sent to the simulation analysis platform. In the scenario of repeated braking, the interval between the characteristic parameters and the corresponding braking demand parameter thresholds at adjacent time moments is obtained, and the peak value of the fluctuation span of the corresponding effect parameters at adjacent time moments is also obtained. If the interval between the characteristic parameter and the corresponding braking demand parameter threshold at adjacent time points exceeds the interval floating span threshold, or the peak value of the fluctuation span of the corresponding effect parameter at adjacent time points exceeds the peak value threshold of the fluctuation span, then a repetitive braking anomaly signal is generated and sent to the simulation analysis platform; if the interval between the characteristic parameter and the corresponding braking demand parameter threshold at adjacent time points does not exceed the interval floating span threshold, and the peak value of the fluctuation span of the corresponding effect parameter at adjacent time points does not exceed the peak value threshold of the fluctuation span, then a repetitive braking satisfaction signal is generated and sent to the simulation analysis platform.

7. The simulation analysis system for a disc brake according to claim 1, characterized in that, The process of the stress distribution detection unit is as follows: Based on the simulated solid model, geometric features are extracted; geometric cleanup is performed on the model. Contact pair configuration: The brake disc friction surface is the primary surface, and the friction lining is the secondary surface; Construct a contact analysis model; Obtain the stress at various locations on the surface of the brake disc and construct a stress cloud map; Identify the location of maximum stress based on the stress cloud diagram and mark it as the principal stress location; A stress deviation threshold is set, and the stress values ​​of the area surrounding the principal stress location are extracted. When the stress value deviation between the principal stress location and the surrounding area location exceeds the stress deviation threshold, the corresponding surrounding area location is marked as a low stress location; when the stress value deviation between the principal stress location and the surrounding area location does not exceed the stress deviation threshold, the corresponding surrounding area location is marked as a secondary stress location.

8. The simulation analysis system for a disc brake according to claim 7, characterized in that, In the contact analysis model, if the peak increase frequency at the principal stress location exceeds the peak increase frequency threshold, or the increase span of the stress distribution density exceeds the density increase span threshold, a stress risk signal is generated and sent to the simulation analysis platform; if the peak increase frequency at the principal stress location does not exceed the peak increase frequency threshold, and the increase span of the stress distribution density does not exceed the density increase span threshold, a stress stability signal is generated and sent to the simulation analysis platform. After receiving a stress risk signal or a stress stability signal, the simulation analysis platform monitors the deformation of the brake disc friction surface and the brake disc flange.

9. The simulation analysis system for a disc brake according to claim 8, characterized in that, If deformation occurs when receiving stress risk signals, the current simulation condition is marked as a stress transient impact condition, and the stress transient impact condition is continuously iterated and updated based on multiple simulation results to obtain the parameter range corresponding to the stress transient impact condition. If no deformation occurs when receiving the stress risk signal, the current simulation condition is marked as a stress slow-state influence condition, and the corresponding parameter range of the stress slow-state influence condition is obtained through iterative updates. If deformation occurs when receiving a stress stabilization signal, the current simulation condition is marked as a stress-induced accidental influence condition. When performing the same type of condition in a real scenario, continuous parameter monitoring is required. If no deformation occurs when the stress stabilization signal is received, the current simulation condition is marked as a stress-controllable condition. The simulation analysis platform stores each working condition type and, after completing the simulation analysis and testing, synchronizes each working condition type to the brake disc's working log and performs real-time comparison.

10. A simulation analysis method for a disc brake, characterized in that, A simulation analysis system applied to a disc brake as described in any one of claims 1-9.

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