Parametric simulation design method for vehicle brake structure

Abstract

The invention relates to the technical field of vehicle brakes, in particular to a parameterized simulation design method for a vehicle brake structure. The method comprises the following steps: firstly, obtaining vehicle brake structure data and constructing a three-dimensional virtual model; then, multi-frequency rapid braking response simulation is carried out based on the model, the softening gradient of the brake disc is recognized, and displacement deformation of the brake disc caused by external force impact is analyzed; thirdly, defining the bearing boundary of the brake by combining the external force impact data and the structural data, and optimizing the structural performance; and finally, designing a parameterized simulation architecture based on the optimized data, and uploading the parameterized simulation architecture to a cloud platform to execute parameterized simulation of the brake. According to the method, the vehicle brake technology is optimized, so that the vehicle brake technology is more perfect.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle brakes, and particularly to a parametric simulation design method for the structure of a vehicle brake. Background Art

[0002] As a core component of vehicle safety performance, the design and performance of brakes are directly related to the safety, stability and driving experience of the whole vehicle. In the past, the design methods of brakes mostly relied on experience and tests, lacking in-depth understanding and optimization means for the brake structure, resulting in a cumbersome design process, high cost and low efficiency. The parametric simulation design method provides a new idea to solve this problem. Parametric design can generate different structural forms by adjusting design parameters according to different design requirements and constraints, so as to conduct accurate performance analysis and optimization of the brakes. By adopting three-dimensional virtual models and simulation technologies, the brakes can be simulated and verified multiple times in a virtual environment, predicting in advance their performance under actual working conditions and making timely adjustments and optimizations according to the simulation results. In addition, with the diversification and complexity of vehicle braking systems, especially under extreme working conditions such as high-speed driving and high loads, traditional test methods are difficult to meet the requirements. By integrating advanced simulation technologies and interactive simulations of multiple physical fields, vehicle brakes can conduct real-time response analysis under different working conditions, such as temperature rise, pressure distribution, material fatigue, etc. during emergency braking, and even simulate the softening and deformation of brake discs in a virtual environment, thereby accurately evaluating the overall performance and safety of the brakes. However, there are problems in the traditional parametric simulation design method for the structure of a vehicle brake, such as inaccurate analysis of brake disc softening and deformation, and imperfect optimization of the vehicle brake structure. Summary of the Invention

[0003] Based on this, it is necessary to provide a parametric simulation design method for the structure of a vehicle brake to solve at least one of the above technical problems.

[0004] To achieve the above object, a parametric simulation design method for the structure of a vehicle brake, the method includes the following steps:

[0005] Step S1: Obtain vehicle brake structure data; construct a three-dimensional virtual model of the vehicle brake based on the vehicle brake structure data to obtain a three-dimensional virtual model of the vehicle brake;

[0006] Step S2: Conduct multi-frequency emergency braking response simulations based on the three-dimensional virtual model of the vehicle brake to obtain multi-frequency emergency braking response data; identify multi-frequency brake disc softening gradients based on the multi-frequency emergency braking response data to obtain multi-frequency brake disc softening gradient data; conduct external force impact brake disc displacement and deformation analysis based on the multi-frequency brake disc softening gradient data to obtain external force impact brake disc displacement and deformation data;

[0007] Step S3: Define the load-bearing boundary of the vehicle brake based on the displacement deformation data of the brake disc under external force impact and the vehicle brake structure data to obtain the load-bearing boundary data of the brake; optimize the structural performance of the vehicle brake structure data based on the load-bearing boundary data of the brake to obtain the optimized data of the structural performance of the vehicle brake.

[0008] Step S4: Design a parametric simulation architecture based on the optimized data of the structural performance of the vehicle brake to obtain an optimized simulation architecture for structural performance parameters; send the optimized simulation architecture for structural performance parameters to the cloud platform to execute the parametric simulation design method for the vehicle brake structure.

[0009] The present invention can lay a foundation for subsequent analysis and optimization by obtaining the structure data of the vehicle brake and constructing a three-dimensional virtual model of the brake based on these data. This three-dimensional virtual model accurately presents the geometric shape and detailed features of the brake, providing a visual basis for further simulation and experiments. In this way, the structure of the brake can be comprehensively grasped and an accurate reference can be provided for performance analysis. Through multi-frequency rapid braking response simulations, the dynamic response data of the brake under different braking conditions can be obtained. Further analyzing these data and identifying the softening gradient of the brake disc can effectively evaluate the physical changes that occur in the brake disc during repeated braking. Thereby, the influence of external force impact on the brake disc can be analyzed to obtain its displacement deformation data, which provides an important basis for subsequent performance evaluation and design optimization. By combining the displacement deformation data of the brake disc under external force impact with the structure data of the vehicle brake, the load-bearing boundary is defined, and thus the load-bearing limit of the brake under working conditions and the stress state of the structure can be determined. Through this process, accurate boundary conditions can be provided for the optimization of the structural performance of the brake to ensure the rationality and feasibility of various parameters during the optimization process, enhancing the overall performance and stability of the brake. Based on the optimized structural performance data, a parametric simulation architecture is designed for more refined simulation analysis. Through the parametric simulation architecture, various parameters in the brake design can be flexibly adjusted to explore the optimal structural configuration. Uploading this architecture to the cloud platform for further simulation calculations not only improves the calculation efficiency but also quickly obtains the results of different design schemes, providing efficient decision-making support for designers and ultimately promoting the innovation and optimization of brake design. Therefore, the present invention is an optimized treatment of a traditional parametric simulation design method for a vehicle brake structure, solving the problems existing in the traditional parametric simulation design method for a vehicle brake structure, such as inaccurate analysis of brake disc softening and deformation and imperfect optimization of the vehicle brake structure, improving the accuracy of the analysis of brake disc softening and deformation, and perfecting the optimization of the vehicle brake structure.

[0010] Preferably, step S1 includes the following steps:

[0011] Step S11: Obtain the vehicle brake structure data;

[0012] Step S12: Conduct a morphological analysis among different components of the vehicle brake structure data to obtain the vehicle brake component morphological data;

[0013] Step S13: Extract the geometric dimensions among different components of the vehicle brake structure data to obtain the vehicle brake component geometric dimension data;

[0014] Step S14: Based on the vehicle brake component morphological data and the vehicle brake component geometric dimension data, construct a three-dimensional virtual model of the vehicle brake to obtain the three-dimensional virtual model of the vehicle brake.

[0015] The acquisition of the vehicle brake structure data in the present invention is the basis for the entire optimization process. This process provides accurate data support for subsequent analysis, modeling, and simulation by precisely collecting and organizing information such as the design parameters, material properties, and connection methods between components of the brake. The quality and integrity of the data directly affect the reliability of the subsequent analysis results. Therefore, step S11 ensures that the data foundation in the entire process is accurate and comprehensive. Conducting a morphological analysis among different components of the vehicle brake structure data is a key step in understanding and evaluating the function and performance of the brake. Through morphological analysis, the roles of each component in the structural design and their ways of cooperating with each other can be identified, which is crucial for subsequent structural optimization and performance evaluation. This step helps designers better understand the cooperation relationship between components and lays a good theoretical foundation for subsequent optimization. In step S13, by extracting the geometric dimensions among different components, accurate dimension data of each component of the brake can be obtained, which is crucial for the construction of the three-dimensional virtual model. The dimension data provides the precise dimensions and shape characteristics of each component, ensuring the accuracy and high fidelity of the virtual model. Only through accurate geometric data can effective performance simulation and structural optimization of the brake be carried out. Based on the previously extracted component morphological data and geometric dimension data, construct a three-dimensional virtual model of the vehicle brake, providing a detailed visual basis for subsequent analysis and optimization. The three-dimensional virtual model can intuitively reflect the structural characteristics and component configuration of the brake, helping designers identify potential problems and make necessary adjustments. This model not only supports functional simulation but also provides clear feedback during the optimization design process, greatly improving the design efficiency and accuracy.

[0016] Preferably, step S2 includes the following steps:

[0017] Step S21: Based on the three-dimensional virtual model of the vehicle brake, conduct multi-frequency rapid braking response simulations to obtain multi-frequency rapid braking response data;

[0018] Step S22: Extract the material properties of the brake disc based on the vehicle brake structure data to obtain the brake disc material property data;

[0019] Step S23: Identify the multi-frequency brake disc softening gradient for the brake disc material property data based on the multi-frequency rapid braking response data to obtain the multi-frequency brake disc softening gradient data;

[0020] Step S24: Analyze the displacement deformation of the brake disc under external force impact according to the multi-frequency brake disc softening gradient data to obtain the displacement deformation data of the brake disc under external force impact.

[0021] The present invention conducts multi-frequency rapid braking response simulation based on the three-dimensional virtual model of the vehicle brake, and can simulate the dynamic response behavior of the brake in various braking scenarios. This process helps to understand the performance of the brake under different working conditions, including the thermal deformation, wear and other effects of the brake under extreme loads. Through this simulation, a large amount of braking response data can be generated, which helps engineers evaluate the performance of the braking system and provides basic data support for subsequent optimization. Extracting the material property data of the brake disc according to the vehicle brake structure data is an important step to ensure the accuracy of the simulation results. The material properties of the brake disc (such as hardness, thermal conductivity, wear resistance, etc.) directly affect its performance under different working environments. By extracting accurate material property data, input data that truly reflects the material behavior can be provided for the simulation analysis, ensuring that the simulation can truly reflect the actual working conditions and improving the reliability of the optimization effect. By analyzing the multi-frequency rapid braking response data and the brake disc material property data, the softening gradient of the brake disc during repeated braking can be identified. The identification of the brake disc softening gradient can reveal the law of material property changes on the surface or inside of the brake disc during multiple brakings, such as thermal fatigue or material deterioration. This data is crucial for evaluating the durability and stability of the brake disc, provides a scientific basis for the improvement of the brake design, and thus improves the long-term performance of the braking system. After identifying the brake disc softening gradient, by analyzing the displacement deformation of the brake disc under external force impact, the influence of external impact on the brake disc structure can be deeply understood. The deformation caused by external force impact not only affects the performance of the brake disc, but also leads to structural damage or serious failure. Through this analysis, the extreme load conditions encountered by the brake disc during actual use can be obtained, providing improvement solutions for designers, and thus enhancing the reliability and stability of the brake under extreme working conditions.

[0022] Preferably, step S23 includes the following steps:

[0023] Step S231: Conduct a non-linear regression analysis of the temperature-stress relationship for the brake disc material property data based on the multi-frequency rapid braking response data to obtain the non-linear regression data of the temperature-stress relationship;

[0024] Step S232: Estimate the difference in braking distances for multiple consecutive rapid braking responses to obtain data on the difference in braking distances for multiple frequencies;

[0025] Step S233: Calculate the incremental intervention braking force based on the data on the difference in braking distances for multiple frequencies and the non-linear regression data on the temperature-stress relationship to obtain data on the incremental intervention braking force;

[0026] Step S234: Analyze the attenuation of the thermal friction coefficient of the brake disc material properties based on the non-linear regression data on the temperature-stress relationship and the data on the difference in braking distances for multiple frequencies to obtain data on the attenuation of the thermal friction coefficient;

[0027] Step S235: Identify the softening gradient of the brake disc for multiple frequencies based on the non-linear regression data on the temperature-stress relationship, the data on the incremental intervention braking force, and the data on the attenuation of the thermal friction coefficient to obtain data on the softening gradient of the brake disc for multiple frequencies.

[0028] The present invention conducts a non-linear regression analysis of the temperature-stress relationship for the brake disc material property data based on multi-frequency rapid braking response data, which is the key to accurately simulating the performance changes of the brake disc under extreme working conditions. The non-linear regression analysis can reveal the complex non-linear relationship between temperature and stress, which is crucial for accurately modeling the behavior of the brake disc in a high-temperature and high-stress environment. Through this analysis, the thermal stress response of the material can be more accurately described, providing a reliable theoretical basis for further performance prediction and optimization. Estimating the differences in continuous multi-frequency braking distances for multi-frequency rapid braking response data helps identify the degradation trend of the brake disc's performance during multiple braking processes. This estimation process reveals the changes in the brake disc during multiple operations through the analysis of braking distance differences, especially the performance fluctuations caused by thermal effects and wear. These differences provide important reference data for subsequent analysis of the softening gradient, helping to accurately evaluate the changes that occur in the brake disc during multiple braking processes. Calculating the incremental intervention braking force based on the multi-frequency braking distance difference data and the non-linear regression data of the temperature-stress relationship can quantify the impact of each braking during multiple braking processes. By calculating the incremental intervention braking force, a better understanding of the actual response of the brake disc under different braking conditions can be obtained. This process helps to reveal the performance changes caused by temperature and stress changes during the operation of the brake, and further provides accurate data support for the optimized design of the brake disc to ensure the stability of the system under various working conditions. Based on the non-linear regression data of the temperature-stress relationship and the multi-frequency braking distance difference data, conducting an analysis of the attenuation of the thermal friction coefficient can evaluate the performance degradation of the brake disc due to changes in temperature and friction during long-term use. By analyzing the attenuation trend of the friction coefficient, the durability of the brake disc under extreme conditions such as high temperature and rapid braking can be accurately understood, helping designers to optimize the material and structure to improve the long-term performance and reliability of the brake disc. Combining the non-linear regression data of the temperature-stress relationship, the incremental intervention braking force data, and the thermal friction coefficient attenuation data to identify the multi-frequency brake disc softening gradient can accurately reveal the performance degradation mode of the brake disc during multiple rapid braking processes. Through this comprehensive analysis, the specific gradient of brake disc softening can be identified, providing a scientific basis for evaluating the long-term performance of the braking system. This step provides important data support for further optimizing the brake disc material and designing a more efficient and durable brake, helping to improve the safety and reliability of the brake in practical applications.

[0029] Preferably, step S233 includes the following steps:

[0030] Conduct an analysis of stress heteroscedasticity for the non-linear regression data of the temperature-stress relationship to obtain stress heteroscedasticity data;

[0031] Calculate the thermal energy stress density of the brake disc based on the stress heteroscedasticity data and the multi-frequency braking distance difference data to obtain the thermal energy stress density of the brake disc;

[0032] Based on the thermal energy stress density of the brake disc, perform an analysis of the thermal energy aging change to obtain the thermal energy stress aging change data;

[0033] According to the thermal energy stress density of the brake disc and the thermal energy stress aging change data, perform an intervention braking force increment calculation to obtain the intervention braking force increment data.

[0034] The present invention conducts a stress heteroscedasticity analysis on the non-linear regression data of the temperature-stress relationship, and can identify the stress distribution changes of the brake disc under different temperature and stress conditions. Stress heteroscedasticity reflects the stress non-uniformity of the brake disc material during operation, especially under high temperature or high stress conditions, where the material exhibits different stress responses. This analysis can help predict local fatigue and damage of the brake disc under long-term or high-frequency braking conditions, and provide accurate stress field data for subsequent performance evaluation. Calculating the thermal energy stress density of the brake disc based on the stress heteroscedasticity data and the multi-frequency braking distance difference data helps to quantify the stress density distribution caused by thermal energy accumulation in the brake disc during multiple braking processes, especially under high temperature conditions. The thermal energy stress density reflects the stress state of the brake disc under thermal load, especially when the brake frequently operates, and the local high stress areas caused by heat accumulation affect the durability and performance stability of the brake disc. Through this calculation, the stress response of the brake disc under different thermal loads can be effectively evaluated, and the failure mode can be predicted. Conducting an analysis of the thermal energy aging change based on the thermal energy stress density data of the brake disc can reveal the performance degradation process of the material under long-term thermal stress. The thermal energy aging change analysis helps to understand the long-term impact of thermal load on the structure of the brake disc material, especially the changes in the microstructure of the material under cyclic stress and high temperature environment. Through this analysis, the aging effect of the brake disc material can be quantified, so as to predict problems such as wear and thermal fatigue that occur in the actual use of the brake disc, and carry out design optimization in advance to extend the service life. According to the thermal energy stress density and the thermal energy aging change data of the brake disc, performing an intervention braking force increment calculation can accurately simulate the impact of each braking on the performance of the brake disc during multiple braking processes. The intervention braking force increment calculation takes into account the braking force changes generated by the brake disc due to thermal energy accumulation, stress change, and material degradation after experiencing multiple cyclic brakings. Through this calculation, the performance changes gradually accumulated during the braking process can be identified, and the performance of the brake disc under long-term high-frequency braking conditions can be evaluated, providing a basis for designing a more stable and efficient braking system.

[0035] Preferably, step S24 includes the following steps:

[0036] Step S241: Perform a softening degree fluctuation analysis on the multi-frequency brake disc softening gradient data to obtain the softening degree fluctuation data;

[0037] Step S242: Quantify the stress co-frequency points of the brake disc based on the softening degree fluctuation data to obtain the softening stress co-frequency points of the brake disc;

[0038] Step S243: Simulate the interface contact response state based on the softening stress co-frequency points of the brake disc to obtain the interface contact response state data;

[0039] Step S244: Analyze the displacement deformation of the brake disc under external force impact according to the softening stress co-frequency points of the brake disc and the interface contact response state data to obtain the displacement deformation data of the brake disc under external force impact.

[0040] The present invention conducts softening degree fluctuation analysis on the multi-frequency brake disc softening gradient data, which helps to reveal the change law of the softening degree of the brake disc during multiple rapid braking processes. Through fluctuation analysis, it is possible to identify the softening trends and amplitude fluctuations in different regions of the brake disc during operation, thereby providing data support for evaluating its long-term performance degradation. This process is particularly important for understanding the thermal fatigue, wear, and performance decline of the brake disc under different usage cycles, and provides a basis for optimizing material selection and design. Quantifying the stress co-frequency points of the brake disc based on the softening degree fluctuation data can identify the stress characteristics experienced by the softening region of the brake disc during multi-frequency braking. By quantifying the stress co-frequency points under different frequencies and softening degrees, the softening influence and stress distribution patterns in different regions can be clarified. This quantification process helps to more accurately predict the stress changes of the brake disc under long-term and high-frequency braking conditions, identify potential failure risks, and optimize the design to improve durability and safety. Simulating the interface contact response state based on the softening stress co-frequency points of the brake disc can simulate the contact behavior between the brake disc and other components of the brake under actual working conditions. By simulating the contact response of the brake disc in different softening states, key factors such as the pressure distribution and friction force change between the contact surfaces can be analyzed. This simulation is crucial for understanding the interaction between the brake disc and the friction material under different working conditions, and can reveal the contact non-uniformity and wear patterns caused by softening, providing data support for further optimizing the contact surface design. Analyzing the displacement deformation of the brake disc under external force impact according to the softening stress co-frequency points of the brake disc and the interface contact response state data can reveal the deformation and displacement characteristics of the brake disc under external impact. By analyzing the response of the softened brake disc when subjected to external force impact, its anti-impact ability and deformation behavior can be evaluated. Especially after multiple brakings, the softened region causes the brake disc to deform more significantly when encountering a large external force. This analysis can provide a basis for the safety design of the brake disc, help design a more impact-resistant brake disc, and improve the stability and safety of the overall system.

[0041] The beneficial effects of the present invention are as follows. By obtaining the structural data of the vehicle brake and constructing a three-dimensional virtual model of the brake based on this data, it can lay a foundation for subsequent analysis and optimization. This three-dimensional virtual model precisely presents the geometric shape and detailed features of the brake, providing a visual basis for further simulation and experiments. In this way, the structure of the brake can be comprehensively grasped, and an accurate reference can be provided for performance analysis. Through multi-frequency rapid braking response simulations, the dynamic response data of the brake under different braking conditions can be obtained. Further analyzing these data to identify the softening gradient of the brake disc can effectively evaluate the physical changes that occur in the brake disc during repeated braking. Thereby, the impact of external forces on the brake disc can be analyzed to obtain its displacement and deformation data, which provides an important basis for subsequent performance evaluation and design optimization. Using the displacement and deformation data of the brake disc under external force impact combined with the structural data of the vehicle brake to define the load-bearing boundary, it is then possible to clarify the load-bearing limit of the brake under working conditions and the stress state of the structure. Through this process, accurate boundary conditions can be provided for the structural performance optimization of the brake to ensure the rationality and feasibility of various parameters during the optimization process, enhancing the overall performance and stability of the brake. Based on the optimized structural performance data, a parameterized simulation framework is designed for more refined simulation analysis. Through the parameterized simulation framework, various parameters in the brake design can be flexibly adjusted to explore the optimal structural configuration. Uploading this framework to the cloud platform for further simulation calculations not only improves the calculation efficiency but also quickly obtains the results of different design schemes, providing efficient decision-making support for designers and ultimately promoting the innovation and optimization of brake design. Therefore, the present invention is an optimized treatment of the traditional parametric simulation design method for a vehicle brake structure, solving the problems existing in the traditional parametric simulation design method for a vehicle brake structure, such as inaccurate analysis of brake disc softening and deformation and imperfect optimization of the vehicle brake structure, improving the accuracy of brake disc softening and deformation analysis, and improving the optimization of the vehicle brake structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic flow chart of the steps of a parametric simulation design method for a vehicle brake structure;

[0043] Figure 2 is Figure 1 a detailed implementation step flow chart of step S2 in

[0044] The realization, functional characteristics, and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] The technical method of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0046] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0047] It should be understood that although terms such as "first" and "second" may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly, the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0048] To achieve the above object, please refer to Figures 1 to 2 , a parametric simulation design method for the structure of a vehicle brake, the method comprising the following steps:

[0049] Step S1: Obtain vehicle brake structure data; construct a three-dimensional virtual model of the vehicle brake based on the vehicle brake structure data to obtain a three-dimensional virtual model of the vehicle brake;

[0050] Step S2: Perform multi-frequency rapid braking response simulations based on the three-dimensional virtual model of the vehicle brake to obtain multi-frequency rapid braking response data; identify the multi-frequency brake disc softening gradient based on the multi-frequency rapid braking response data to obtain multi-frequency brake disc softening gradient data; perform an analysis of the displacement deformation of the brake disc under external force impact based on the multi-frequency brake disc softening gradient data to obtain displacement deformation data of the brake disc under external force impact;

[0051] Step S3: Define the brake bearing boundary according to the displacement deformation data of the brake disc under external force impact and the vehicle brake structure data to obtain brake bearing boundary data; optimize the structural performance of the vehicle brake structure data based on the brake bearing boundary data to obtain optimized vehicle brake structure performance data;

[0052] Step S4: Design a parametric simulation architecture based on the optimized data of the vehicle brake structure performance to obtain an optimized simulation architecture for structural performance parameters; send the optimized simulation architecture for structural performance parameters to the cloud platform to execute the parametric simulation design method for the vehicle brake structure.

[0053] In the embodiment of the present invention, referring to Figure 1 As shown, it is a schematic diagram of the step flow of a parametric simulation design method for a vehicle brake structure of the present invention. In this example, the parametric simulation design method for the vehicle brake structure includes the following steps:

[0054] Step S1: Obtain the vehicle brake structure data; construct a three-dimensional virtual model of the vehicle brake based on the vehicle brake structure data to obtain a three-dimensional virtual model of the vehicle brake;

[0055] In the embodiment of the present invention, first, obtain the design data of the vehicle brake, which are derived from the actual brake component drawings, measurement data, or files output by the CAD system. The obtained data includes the geometric shapes, material properties, and assembly structures of each component of the brake. The dimensions, shapes, connection methods, etc. of each component must be recorded in detail. Then, based on these structure data, perform three-dimensional modeling through accurate coordinate and dimension information. Use traditional CAD design software (such as AutoCAD, SolidWorks, etc.) to input detailed geometric data to construct a three-dimensional virtual model of the vehicle brake. This model includes all components of the brake and accurately reproduces its physical dimensions and spatial position relationships. When constructing the three-dimensional virtual model, it is also necessary to label the material properties of each component to ensure that the physical performance data of each component is correctly reflected. Specifically, when operating, standardize the geometric dimensions of the components, and model all components according to the established tolerance standards. Through detailed component dimension extraction and establishment of assembly fit relationships, finally generate a complete three-dimensional model that can be used for subsequent simulation analysis.

[0056] Step S2: Simulate the multi-frequency rapid braking response based on the three-dimensional virtual model of the vehicle brake to obtain multi-frequency rapid braking response data; identify the multi-frequency brake disc softening gradient based on the multi-frequency rapid braking response data to obtain multi-frequency brake disc softening gradient data; analyze the displacement deformation of the brake disc under external force impact according to the multi-frequency brake disc softening gradient data to obtain displacement deformation data of the brake disc under external force impact;

[0057] In the embodiments of the present invention, in this step, first, it is necessary to perform multi-frequency rapid braking response simulations on the three-dimensional virtual model of the vehicle brake. Using the finite element analysis method, the brake is simulated to analyze its dynamic responses under different braking conditions. For this purpose, it is necessary to first input the material properties of the brake, especially the thermodynamic characteristics of the brake disc, the friction coefficient, and the temperature-stress relationship, etc. Using thermodynamic simulation software (such as ANSYS, Abaqus, etc.), perform multi-frequency rapid braking response simulation calculations to obtain the braking response data for each frequency. Next, through subsequent processing based on the braking response data, identify the multi-frequency brake disc softening gradient. The specific operation is to extract the relationship between temperature and stress changes from the response data after each rapid braking through regression analysis technology, and further identify the softening gradient of the brake disc under different braking conditions. The algorithm used is non-linear regression analysis, and the softening gradient is calculated through the temperature-stress curve to obtain the changes in the softening of the brake disc during multiple brakings. Finally, based on the multi-frequency brake disc softening gradient data, analyze the displacement and deformation of the brake disc under external force impact. Using the dynamic analysis model established by the finite element method, simulate the displacement and deformation generated when an external impact force acts on the brake disc. To ensure the accuracy of the deformation analysis, a small time step is used for simulation, and friction effects, thermal expansion effects, and material yield behavior are considered. Through these simulation steps, the displacement and deformation data of the brake disc under external force impact are obtained.

[0058] Step S3: Define the load-bearing boundary of the vehicle brake based on the displacement and deformation data of the brake disc under external force impact and the vehicle brake structure data to obtain the load-bearing boundary data of the brake; optimize the structural performance of the vehicle brake structure based on the load-bearing boundary data of the brake to obtain the optimized structural performance data of the vehicle brake;

[0059] In the embodiments of the present invention, based on the displacement and deformation data of the brake disc under external force impact, first define the load-bearing boundary of the brake. Using the boundary condition optimization method, determine which parts are affected by large external forces and the impact of these parts on the overall performance of the brake through numerical simulation analysis. The specific operation is to input the displacement and deformation data into the finite element model and use the contact force analysis method to determine the load transfer path and force-bearing area between components. Through these analyses, the load-bearing boundary data of the brake are obtained, including the load distribution and boundary constraint conditions between components. Subsequently, use these load-bearing boundary data to optimize the structural performance of the vehicle brake. The optimization process includes improving the load-bearing capacity of the brake by modifying structural parameters (such as wall thickness, aperture, support position, etc.). For this purpose, use structural optimization algorithms, such as genetic algorithms, particle swarm optimization algorithms, etc., to perform iterative calculations within a range of multiple design variables. By comparing the performance indicators of different design schemes (such as maximum load-bearing capacity, deformation, temperature rise, etc.), finally obtain the optimized structural performance data of the vehicle brake.

[0060] Step S4: Design a parametric simulation architecture based on the vehicle brake structure performance optimization data to obtain a structure performance parameter optimization simulation architecture; send the structure performance parameter optimization simulation architecture to the cloud platform to execute the parametric simulation design method for the vehicle brake structure.

[0061] In the embodiment of the present invention, in this step, first, use the vehicle brake structure performance optimization data to design a parametric simulation architecture. This simulation architecture is based on the optimized structure data, sets different simulation parameters for different usage conditions (such as temperature, pressure, etc.), and forms a multi-dimensional simulation analysis framework. The technical method adopted is multi-parameter automatic tuning, and a flexible simulation architecture is established using parametric design software (such as CATIA, SolidWorks Simulation, etc.). This architecture can dynamically adjust the input parameters to adapt to different design requirements. When constructing the simulation architecture, for the key performance indicators (such as braking efficiency, thermal load, stiffness, etc.) found in the design process, reasonable simulation variables are set, and through repeated calculations by the optimization solver, ensure that each performance indicator meets the expected requirements. Finally, upload the completed simulation architecture to the cloud platform for high-performance computing. The cloud platform executes the simulation task through distributed computing resources, processes complex calculations, generates accurate simulation results, and provides decision-making support for subsequent actual production.

[0062] Preferably, step S1 includes the following steps:

[0063] Step S11: Obtain the vehicle brake structure data;

[0064] Step S12: Conduct a morphological analysis among different components of the vehicle brake structure data to obtain the vehicle brake component morphological data;

[0065] Step S13: Extract the geometric dimensions among different components of the vehicle brake structure data to obtain the vehicle brake component geometric dimension data;

[0066] Step S14: Construct a three-dimensional virtual model of the vehicle brake based on the vehicle brake component morphological data and the vehicle brake component geometric dimension data to obtain a three-dimensional virtual model of the vehicle brake.

[0067] In the embodiments of the present invention, in step S11, first, detailed structural data of the vehicle brake is obtained. These data are sourced from brake design documents, engineering drawings, and known engineering standards. The required structural data includes the geometric dimensions, assembly positions, material types, and force characteristics of each component. To ensure data accuracy, precise measuring tools such as coordinate measuring machines (CMMs) are used to obtain the dimensions of actual components and compare them with the design drawings. The obtained structural data should include, but not be limited to, the diameter and thickness of the brake disc, the dimensions and mounting hole positions of the brake caliper, and the clearance between the caliper and the brake disc. If there are actual component samples, surface data can be directly extracted through 3D scanning technology. The 3D surface profile of the component is captured using a scanner, and then the data is trimmed to remove noise points, and finally, accurate 3D geometric data is generated. All structural data must meet industrial design standards and usage requirements to ensure data validity. In step S12, based on the obtained vehicle brake structural data, morphological analysis is performed between different components. The focus of the analysis is on the relative position relationships, mutual cooperation methods, and assembly structures among the components. First, geometric analysis methods are used to determine the morphological characteristics of each component of the brake, including its shape, surface structure, contact area, and assembly holes. To accurately identify the morphological relationships between components, contour line extraction technology is adopted to extract the outer contours of each component and conduct comparative analysis. This process ensures that the assembly methods and mutual contact areas of components can be accurately judged during the simulated assembly process. For example, the contact surface between the brake caliper and the brake disc, and the cooperation relationship between the brake disc and the brake pads. For components with complex morphologies, the multi-point matching algorithm can be used to accurately fit the surface to identify the contact patterns and force distributions between components. Through morphological analysis, the morphological data of the vehicle brake components obtained includes information such as the outer shapes, contact surfaces, and assembly fits of the components. These data provide a basis for subsequent structural design and simulation analysis. In step S13, through detailed analysis of the vehicle brake structural data, the geometric dimension data of each component is extracted to ensure the accuracy of the dimension information of all components. These geometric dimension data include basic geometric parameters such as the length, width, thickness, hole diameter, angle, and clearance of the components. In specific operations, first, the components are segmented and calibrated, and the required geometric data is extracted one by one through the dimension information in the drawing annotations or scanned data. For components with complex geometric shapes (such as brake calipers and brackets), geometric modeling technology is used to mesh their surfaces, and then the specific dimensions of each geometric grid unit are extracted. Through the finite element modeling method, the contacts, interferences, and fits between different components are identified, and the geometric parameters of the overall brake assembly are extracted, such as the clearance between the brake disc and the brake caliper, the thickness of the friction pad, and the accuracy of the assembly holes. In this step, special attention also needs to be paid to the manufacturing tolerances of the components to ensure that the extracted geometric dimension data conforms to the tolerance range in the actual manufacturing process.In addition, the interface dimensions of different components must be accurately extracted, such as the dimensions of connection parts like fixing holes and guide holes. These data are crucial for subsequent assembly and structural optimization. Through these extractions, accurate geometric dimension data of the vehicle brake assembly are obtained. In step S14, using the morphological data and geometric dimension data of the vehicle brake assembly obtained in steps S12 and S13, a three-dimensional virtual model of the vehicle brake is constructed. First, based on the morphological data, the geometric contours and surface morphologies of each component are defined. By combining the geometric dimension data of each component with the morphological data, it is ensured that the morphology and dimensions of the components are accurately reproduced in the virtual model. Specifically, in the implementation, the assembly module in 3D modeling software (such as SolidWorks, CATIA) is used. By inputting the dimension and morphology information of each component, each component is precisely assembled into a complete brake structure model. During the modeling process, special attention needs to be paid to the mating relationships between components. For example, the mating tolerances between the brake disc and the brake caliper, and the precise positioning of the hole positions, etc. By using assembly constraints and mating relationships, it is ensured that each component can be assembled reasonably and precisely during the simulation process. During the construction process, factors such as material properties, surface roughness, and assembly errors also need to be considered to ensure that the three-dimensional virtual model can truly reflect the performance and structure of the actual brake. After the model is completed, model inspection is carried out to ensure that there are no problems such as missing components or inconsistent dimensions, and finally a complete and accurate three-dimensional virtual model of the vehicle brake is generated.

[0068] Preferably, step S2 includes the following steps:

[0069] Step S21: Based on the three-dimensional virtual model of the vehicle brake, perform multi-frequency rapid braking response simulations to obtain multi-frequency rapid braking response data;

[0070] Step S22: Extract the material properties of the brake disc according to the vehicle brake structure data to obtain brake disc material property data;

[0071] Step S23: Based on the multi-frequency rapid braking response data, identify the multi-frequency brake disc softening gradient for the brake disc material property data to obtain multi-frequency brake disc softening gradient data;

[0072] Step S24: According to the multi-frequency brake disc softening gradient data, perform an analysis of the displacement deformation of the brake disc under external force impact to obtain displacement deformation data of the brake disc under external force impact.

[0073] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0074] Step S21: Based on the three-dimensional virtual model of the vehicle brake, perform multi-frequency rapid braking response simulations to obtain multi-frequency rapid braking response data;

[0075] In the embodiment of the present invention, in step S21, based on the three-dimensional virtual model of the vehicle brake obtained in step S14, a multi-frequency rapid braking response simulation is carried out. First, appropriate physical theories and numerical methods are selected for the simulation, such as the combination of elasticity mechanics and heat conduction model to simulate the thermal and mechanical responses during braking. Through the dynamic analysis of each component of the braking system, the finite element method (FEM) is used to discretize the structure of the brake to ensure that the responses of each component are accurately simulated. During the simulation, a series of braking input conditions are given to simulate the rapid braking process of the brake disc and the brake caliper. The specific operations include applying different braking torques and rapid accelerations to simulate the responses under different braking frequencies. Under these conditions, the surface of the brake disc and the brake caliper will be affected by huge frictional forces and heat changes, so it is necessary to introduce a thermal-mechanical coupling model. Through numerical solution, response data such as the temperature distribution, stress change, and deformation amount on the surface of the brake disc during the multi-frequency braking process are obtained. Finally, the multi-frequency rapid braking response data obtained through the simulation includes information such as the temperature change, force distribution, and deformation of the brake disc, which provides a basis for subsequent material softening identification and displacement deformation analysis.

[0076] Step S22: Extract the material properties of the brake disc according to the vehicle brake structure data to obtain the brake disc material property data;

[0077] In the embodiment of the present invention, in step S22, according to the vehicle brake structure data obtained in step S11, the material properties of the brake disc are extracted. The specific operation is to first identify the specific material of the brake disc in the vehicle brake, such as cast iron, carbon fiber composite material, or ceramic, etc. According to the different types of materials, the thermal, mechanical, and tribological properties of the material are extracted by referring to material manuals, experimental data, or engineering standards. The key material properties to be extracted include: thermal conductivity, specific heat capacity, Young's modulus, yield strength, coefficient of thermal expansion, friction coefficient, etc. These material properties are crucial for the thermal stress, thermal deformation, friction and wear, etc. behaviors of the brake disc during rapid braking. For example, the thermal conductivity of the material directly affects the heat accumulation and distribution, while the friction coefficient affects the frictional heat generated during braking. All material properties need to consider the influence of temperature on the material performance, so the temperature-dependent properties within the temperature range (such as 500 °C to 1000 °C) also need to be extracted. Through these properties, a thermal-mechanical behavior model of the brake disc in the actual working environment can be established, providing basic data for subsequent softening gradient analysis.

[0078] Step S23: Identify the multi-frequency brake disc softening gradient based on the multi-frequency rapid braking response data for the brake disc material property data to obtain the multi-frequency brake disc softening gradient data;

[0079] In the embodiment of the present invention, in step S23, based on the multi-frequency rapid braking response data obtained in step S21 and the brake disc material property data obtained in step S22, the softening gradient of the brake disc is identified. The softening gradient refers to the gradient distribution of the reduction in the material hardness of the brake disc with the increase in temperature under high temperature and frequent rapid braking conditions. For this purpose, it is first necessary to analyze the temperature distribution and stress change of the brake disc during each rapid braking process in combination with the thermo-mechanical coupling model. Using the finite element method, the temperature field of the brake disc is accurately solved, and considering the temperature-dependent properties of the material, the hardness change of the material at different temperatures is calculated. By comparing the multiple response results under different braking frequencies, the softening gradient of the brake disc at different positions and different working states is obtained. Specifically, when operating, a method combining thermal expansion analysis and elastoplastic mechanics analysis can be adopted. First, the temperature distribution on the surface and inside of the brake disc at each time point is solved, and then the stress-strain behavior of each region is calculated using the material property data, and further the softening effect is deduced. Through these calculations, a multi-frequency brake disc softening gradient data set is obtained, which reflects the softening degree of different positions of the brake disc under high-frequency braking conditions.

[0080] Step S24: Perform an analysis on the displacement deformation of the brake disc under external force impact based on the multi-frequency brake disc softening gradient data to obtain the displacement deformation data of the brake disc under external force impact.

[0081] In the embodiment of the present invention, in step S24, based on the multi-frequency brake disc softening gradient data obtained in step S23, an analysis on the displacement deformation of the brake disc under external force impact is performed. The specific operation is as follows: First, based on the softening gradient data, the material property differences in different regions of the brake disc when subjected to external force impact are determined, and an elastic-plastic mechanics model of the local region is established based on these data. By establishing a finite element model and applying an external force impact (such as the rapid contact of the brake pads or other sudden external forces), the displacement and deformation conditions of the brake disc when subjected to the impact are simulated. According to different impact forces and directions, combined with the softening behavior of the brake disc material at different temperatures, an impact response analysis is performed. During this analysis process, the displacements, strains, and deformation amounts of each point will be solved, especially the deformation conditions in the high-softening region. Through this analysis, the displacement deformation data of the brake disc after external force impact are obtained, mainly including information such as the deformation amount, stress distribution, and local displacement of the brake disc during the impact process. These data can provide a basis for the subsequent performance evaluation and structural optimization of the brake.

[0082] Preferably, step S23 includes the following steps:

[0083] Step S231: Perform a non-linear regression analysis on the temperature-stress relationship of the brake disc material property data based on the multi-frequency rapid braking response data to obtain non-linear regression data of the temperature-stress relationship;

[0084] Step S232: Continuously estimate the multi-frequency braking distance differences for the multi-frequency rapid braking response data to obtain multi-frequency braking distance difference data;

[0085] Step S233: Calculate the intervention braking force increment based on the multi-frequency braking distance difference data and the non-linear regression data of the temperature-stress relationship to obtain the intervention braking force increment data;

[0086] Step S234: Conduct a thermal friction coefficient attenuation analysis on the brake disc material property data based on the non-linear regression data of the temperature-stress relationship and the multi-frequency braking distance difference data to obtain the thermal friction coefficient attenuation data;

[0087] Step S235: Identify the multi-frequency brake disc softening gradient based on the non-linear regression data of the temperature-stress relationship, the intervention braking force increment data, and the thermal friction coefficient attenuation data to obtain the multi-frequency brake disc softening gradient data.

[0088] In the embodiment of the present invention, in step S231, first, using the multi-frequency rapid braking response data obtained in step S21 and combining with the brake disc material property data obtained in step S22, a non-linear regression analysis of the temperature-stress relationship is carried out. The temperature-stress relationship describes the connection between the temperature change and the stress change of the brake disc during rapid braking. First, in the known multi-frequency braking responses, the temperature and stress data of the brake disc at each frequency are extracted. To perform non-linear regression analysis, an appropriate non-linear regression model needs to be selected, such as an exponential function, a power function, or a high-degree polynomial regression model. The relationship between temperature and stress is fitted according to the experimental data. The parameters of the regression equation are solved using the Least Squares Method to minimize the fitting error. By analyzing each data point, the optimal fitting parameters are determined. This regression analysis can accurately reflect the stress response behavior of the brake disc material at different temperatures and provide a basis for subsequent analysis of the thermal friction coefficient attenuation and identification of the softening gradient. Finally, the non-linear regression data of the temperature-stress relationship obtained provides the required basic data for the subsequent steps. In step S232, based on the multi-frequency rapid braking response data obtained in step S21, an estimation of the difference in continuous multi-frequency braking distances is carried out. First, the braking distances at the start and end times of braking are extracted from each rapid braking response simulation. The braking distance is usually related to the braking response time, the braking force, and the thermal characteristics of the brake disc. By statistically analyzing the braking time, the force during the deceleration process, and the corresponding distance changes during multiple rapid braking processes, the distance differences for each braking process are obtained. To obtain the continuous multi-frequency braking distance difference data, the performance change of the braking system under continuous operation can be estimated by calculating the braking distance differences between adjacent rapid brakings. Specifically, considering the accumulation of frictional heat and the brake disc softening effect, based on the temperature data and stress data, the distance changes during the deceleration process at each stage of the braking process are estimated, and the difference data between each braking is calculated through a difference estimation method. These data help to evaluate the thermal attenuation of the brake disc and the change in the braking distance under multi-frequency rapid braking conditions, and finally obtain a multi-frequency braking distance difference data set. In step S233, based on the multi-frequency braking distance difference data obtained in step S232 and the non-linear regression data of the temperature-stress relationship obtained in step S231, an intervention braking force increment calculation is carried out. The intervention braking force increment reflects the impact of factors such as thermal attenuation and material softening on the braking performance during continuous braking, and thus additional braking force is required to maintain the braking effect. First, the multi-frequency braking distance difference data is used to evaluate the performance change of the brake disc in each braking, and then the intervention braking force increment required for the braking system is estimated. By combining the non-linear regression data of the temperature-stress relationship, the impact of the temperature change during each braking process on the braking performance is calculated.The higher the temperature, the more obvious the softening effect of the material, resulting in a weakened braking effect. Therefore, it is necessary to increase the braking force to compensate for the performance decay. In step S234, based on the non-linear regression data of the temperature-stress relationship obtained in step S231 and the multi-frequency braking distance difference data obtained in step S232, the attenuation analysis of the thermal friction coefficient of the brake disc material is carried out. The thermal friction coefficient is a key factor affecting braking performance, and its value changes with the increase of temperature. Excessive temperature usually leads to a decrease in the friction coefficient, thus affecting the braking effect. The steps of the attenuation analysis first include extracting the friction coefficient data of the brake disc material at different temperatures. Combining the temperature-stress relationship, the change of the friction coefficient can be analyzed by establishing a relationship model between the friction coefficient and temperature. Through the analysis of the multi-frequency braking distance difference data, it can be further estimated how the friction coefficient of the brake disc material decays with the increase of temperature at different working temperatures. Based on the regression model, the thermal friction coefficient attenuation data are calculated through calculation, and these data are used to describe the performance change of the brake disc under multiple brakings. In step S235, based on the data obtained in steps S231, S233 and S234, the identification of the multi-frequency brake disc softening gradient is carried out. First, by combining the non-linear regression data of the temperature-stress relationship with the intervention braking force increment data, the performance decay of the brake disc at multiple braking frequencies is calculated. Then, by combining the thermal friction coefficient attenuation data with the above data, the softening effect caused by the temperature rise and the change of the friction coefficient during the continuous braking process of the brake disc is further described. Using these data, a softening gradient model is established to describe the softening degree of the brake disc in different regions (such as the edge of the brake disc, the central part, etc.). By gradually superimposing the influencing factors such as temperature, stress, and friction coefficient during the braking process, the softening gradient of the brake disc is calculated. Finally, the obtained multi-frequency brake disc softening gradient data can reflect the local softening phenomenon of the brake disc under multiple rapid brakings, providing data support for optimizing the brake design.

[0089] Preferably, step S233 includes the following steps:

[0090] Perform stress heteroscedasticity analysis on the non-linear regression data of the temperature-stress relationship to obtain stress heteroscedasticity data;

[0091] Calculate the thermal energy stress density of the brake disc according to the stress heteroscedasticity data and the multi-frequency braking distance difference data to obtain the thermal energy stress density of the brake disc;

[0092] Perform thermal energy aging change analysis based on the thermal energy stress density of the brake disc to obtain thermal energy stress aging change data;

[0093] Calculate the intervention braking force increment according to the thermal energy stress density of the brake disc and the thermal energy stress aging change data to obtain the intervention braking force increment data.

[0094] In the embodiment of the present invention, in step S233, first, using the non-linear regression data of the temperature-stress relationship obtained in step S231 and combining with the multi-frequency braking distance difference data obtained in step S232, the calculation of the intervention braking force increment is carried out. The core of this step is to evaluate the performance degradation of the brake disc caused by the thermal effect during multiple emergency braking processes, so as to calculate the necessary increased braking force to maintain the braking effect. First, the stress response characteristics of the brake disc at different temperatures are extracted according to the non-linear regression data of the temperature-stress relationship. Then, using the multi-frequency braking distance difference data, that is, the change in the braking distance of each emergency braking, by calculating the deceleration of each braking, the degradation degree of the brake disc under multi-frequency operation is evaluated. Especially under high-temperature conditions, the material softening effect is significant, resulting in braking performance degradation. Next, combining the temperature-stress relationship and the braking distance difference, the following formula is used for the calculation of the braking force increment: Where F i is the increment of the intervention braking force during the i-th emergency braking process, ∝ is the value of the braking times, D i is the braking distance difference in the i-th braking, is the derivative of the temperature-stress relationship; in step S231, first, stress response data is extracted from the non-linear regression data of the temperature-stress relationship. To evaluate the distribution law of stress under different temperature conditions, stress heteroscedasticity analysis is adopted. Heteroscedasticity analysis is used to test whether each stress response data in the data shows different fluctuation characteristics with the change of temperature. This analysis can reveal the stability and reliability of the material's response at different temperatures. By gradually grouping the stress data in temperature intervals and using statistical methods such as Weighted Least Squares (WLS) for analysis, the variance of the stress data is calculated, and the stress volatility within each interval is determined. For example, the stress data in different temperature segments (such as low temperature, medium temperature, high temperature) are classified, and then the standard deviation and variance of each category are calculated to test its heteroscedasticity. For the temperature segments with obvious heteroscedasticity, an adaptive weighting method is used to adjust the weight of the regression model according to the stress fluctuation in that temperature interval to optimize the model fitting accuracy. Finally, the obtained stress heteroscedasticity data characterizes the stress fluctuation characteristics under different temperature conditions, reflects the instability of the material properties, and provides a basis for the subsequent calculation of thermal energy stress density and braking force increment. In step S232, based on the stress heteroscedasticity data and the multi-frequency braking distance difference data, the thermal energy stress density of the brake disc is calculated. The thermal energy stress density is a measure that describes the stress change caused by the thermal effect during the operation of the brake disc, reflecting the combined effect of temperature and stress on the brake disc material. First, using the stress heteroscedasticity data and the multi-frequency braking distance difference data, the thermal energy stress density of the brake disc at different operating temperatures during each emergency braking process is calculated. The specific method is to calculate the thermal energy stress accumulated per unit volume in the brake disc during operation through a thermodynamic model combined with the heat conduction characteristics of the material. In step S234, based on the thermal energy stress density data of the brake disc, thermal energy aging change analysis is carried out. Thermal energy aging change describes the stress change caused by thermal expansion and contraction in the brake disc material after experiencing multiple thermal cycles. With the repeated action of thermal stress, the material will show hardening, embrittlement or softening phenomena, thus affecting the service life and performance of the brake disc. First, through the relationship between temperature and time, the thermal energy stress aging of the brake disc during multiple emergency braking processes is analyzed. According to the thermal energy stress density data, the stress change of the brake disc under multiple thermal cycles is simulated, and a stress relaxation model is used to predict the influence of thermal stress on the brake disc material. In particular, the time-temperature superposition principle (TTSP) is used to consider the influence of temperature change on thermal energy aging. Then, the degree of hardening or softening of the brake disc under multiple thermal cycles is calculated to obtain the thermal energy stress aging change data. In step S235, combining the thermal energy stress density data of the brake disc obtained in step S232 and the thermal energy stress aging change data obtained in step S234, the intervention braking force increment is calculated.Based on the thermal energy effect during multiple rapid braking processes, the additional braking force required for the brake disc after the braking performance decays can be calculated. By combining the thermal energy stress density and the data of thermal energy aging changes, and through comprehensive calculation of the thermal energy effect of each rapid braking, the braking force increment required for each braking is obtained, thus providing accurate data support for the optimization of the braking system.

[0095] Preferably, step S24 includes the following steps:

[0096] Step S241: Analyze the fluctuation of the softening degree of the multi-frequency brake disc softening gradient data to obtain the softening degree fluctuation data;

[0097] Step S242: Quantify the stress same-frequency points of the brake disc according to the softening degree fluctuation data to obtain the stress same-frequency points of the brake disc softening;

[0098] Step S243: Simulate the interface contact response state based on the stress same-frequency points of the brake disc softening to obtain the interface contact response state data;

[0099] Step S244: Analyze the displacement deformation of the brake disc under external force impact according to the stress same-frequency points of the brake disc softening and the interface contact response state data to obtain the displacement deformation data of the brake disc under external force impact.

[0100] In the embodiment of the present invention, in step S241, first, according to the multi-frequency brake disc softening gradient data, the fluctuation analysis of the brake disc softening degree is carried out. The purpose of the softening degree fluctuation analysis is to evaluate the fluctuation of the brake disc softening phenomenon with time and temperature changes during multiple rapid braking processes. For this purpose, the time-domain analysis method is used to segment the softening degree during each braking process, and calculate the softening gradient change in each stage. The specific method is to calculate the fluctuation amplitude of the softening gradient in each stage through the recording of temperature and stress changes during the multi-frequency braking process, and use the weighted average method to smooth the softening gradient after each rapid braking. Then, by calculating the standard deviation and variance of each stage, the fluctuation of the softening degree is evaluated. For the softening gradient data, the discrete Fourier transform (DFT) is used to analyze its spectrum to identify the main frequency components of the softening fluctuation. The softening degree fluctuation data obtained through these analyses characterizes the softening characteristics of the brake disc in multiple braking cycles, providing a basis for subsequent stress analysis. This fluctuation analysis can further reveal the performance instability of the brake disc caused by factors such as thermal load changes and material aging during the working process. In step S242, based on the softening degree fluctuation data obtained in step S241, the stress of the brake disc is quantified at the same frequency points. The stress quantification at the same frequency points is to analyze the fluctuation of the softening degree, identify the stress response generated by the brake disc at a specific frequency, and further understand the performance of the brake disc under different working conditions. First, the Fourier transform is applied to perform frequency-domain analysis on the softening degree fluctuation data to obtain the spectral characteristics of the softening degree. Subsequently, by comparing the spectrum of the softening degree with the stress response data of the brake disc, the corresponding stress changes at the same frequency point are identified. The correlation analysis (such as the Pearson correlation coefficient) is used to calculate the relationship between the softening degree and the stress response at each frequency point, and the softening stress same-frequency points are determined, that is, at a specific frequency, the points where the softening degree and the stress change are highly correlated. In step S243, based on the brake disc softening stress same-frequency point data obtained in step S242, the interface contact response state simulation is carried out. The purpose of the interface contact response state simulation is to study the response of the brake disc softening stress during the braking process, especially on the contact surface. Through this simulation process, it can be predicted how the contact surface will change due to the action of softening and stress during the long-term use of the brake disc, thereby affecting the braking effect and service life. First, based on the softening stress same-frequency point data, the finite element analysis (FEA) method is used to model the contact area on the brake disc surface. According to the simulation model, by applying different external loads and temperature boundary conditions, the displacement and stress responses of the contact points are calculated. During this process, the effects of temperature distribution, material softening degree, and stress distribution are considered, and the contact theory (such as the Hertz contact theory) is used to simulate the contact deformation under different contact pressures.Secondly, during the simulation, a dynamic analysis method is adopted to consider the vibration response of the brake disc at different frequencies, and the friction coefficient of the contact area is dynamically adjusted by softening the stress at the same frequency point. Through the simulation of the contact surface response, the stress, displacement, and deformation of the contact area after multiple brakings are obtained, and finally the interface contact response state data is obtained. In step S244, based on the brake disc softening stress same-frequency point data obtained in step S242 and the interface contact response state data obtained in step S243, the displacement and deformation analysis of the brake disc under external force impact is carried out. The purpose of this analysis is to simulate the surface deformation of the brake disc caused by external force impact or uneven friction during multiple brakings and predict its impact on the overall performance. First, based on the softening stress same-frequency point and the interface contact response state data, a dynamic model including all contact points is established. The nonlinear thermodynamics characteristics of the brake disc material, the influence of the softening process, and the impact of external loads (such as the frictional force between the wheel and the brake disc) on the brake disc are considered in the model. Using the dynamic finite element analysis (FEA) method, by applying external force impacts (such as sudden hard braking or unbalanced braking forces), the displacement and deformation of the brake disc under different impact conditions are simulated. During the analysis process, by dynamically tracking the stress state of each contact point and combining with a nonlinear material model (such as the Johnson-Cook model) and contact mechanics analysis, the deformation of the brake disc at each time step is calculated. Finally, the obtained external force impact brake disc displacement and deformation data characterize the deformation characteristics of the brake disc under external force impact, including the microscopic deformation of the contact area and the change in the overall displacement. These data provide an important basis for evaluating the fatigue life, wear behavior, etc. of the brake disc in actual use.

[0101] Preferably, step S244 includes the following steps:

[0102] Perform multi-parameter coupling decomposition on the brake disc softening stress same-frequency point and interface contact response state data to obtain brake disc stress-interface contact multi-parameter decomposition data;

[0103] Perform external force impact multi-point contact feedback analysis on the brake disc stress-interface contact multi-parameter decomposition data to obtain external force impact multi-point contact feedback data;

[0104] Based on the brake disc softening stress same-frequency point and the external force impact multi-point contact feedback data, evaluate the local stiffness attenuation of the brake disc to obtain brake disc local stiffness attenuation data;

[0105] According to the brake disc local stiffness attenuation data and the external force impact multi-point contact feedback data, perform external force impact brake disc displacement and deformation analysis to obtain external force impact brake disc displacement and deformation data.

[0106] In the embodiments of the present invention, through multi-parameter coupled decomposition of the data of the same-frequency points of the softening stress of the brake disc and the data of the interface contact response state, the multi-parameter decomposition data of the brake disc stress-interface contact is obtained. This step aims to comprehensively consider the mutual influence of the softening stress and the interface contact state, and deeply analyze the stress-contact response coupling characteristics of the brake disc under working conditions. First, the Fourier transform is used to perform frequency-domain decomposition on the data of the same-frequency points of the softening stress of the brake disc to obtain the stress amplitudes of each frequency component. Then, based on the data of the interface contact response state, principal component analysis (PCA) is used to perform dimensionality reduction processing on it, and the most representative contact mode is extracted. Through these processes, the influence of noise can be effectively eliminated, and the contact response data can be mapped to the space related to stress. Subsequently, the multi-linear regression method is used to couple the data of the same-frequency points of the softening stress and the data of the interface contact response state to establish a non-linear relationship between the two. This process takes into account the frictional force on the contact surface, the distribution of contact pressure, and the elastic-plastic behavior of the material to ensure the accuracy of the coupled analysis. Finally, after the coupled decomposition, the obtained multi-parameter decomposition data of the brake disc stress-interface contact describes the interaction and its change trend between the softening stress and the contact state under different braking conditions, providing accurate basic data for subsequent analysis. Through the external force impact multi-point contact feedback analysis on the obtained multi-parameter decomposition data of the brake disc stress-interface contact, it aims to simulate the multi-point contact feedback situation of the brake disc under the action of external force impact, and further evaluate its performance under extreme working conditions. First, according to the multi-parameter decomposition data of the brake disc stress-interface contact, a discrete model containing multiple contact points is constructed. This model reflects the changes in different regions of the brake disc surface under the stress state. Next, by applying external force impacts (such as sudden braking or uneven friction) to the contact area of the brake disc, and using the contact mechanics analysis method to simulate the feedback response of each contact point, the stress, deformation, and displacement of each contact point are obtained. In order to accurately simulate the influence of external force impacts, the multi-point contact algorithm is used to perform feedback analysis on multiple contact points of the brake disc. In this analysis process, the Hertz contact theory is combined to calculate the distribution of compressive stress between contact points, and by analyzing the feedback response point by point, the change in frictional force of different contact points under the action of external force impact is obtained. By solving the friction factor and deformation amount of each contact point, the multi-point contact feedback data of the brake disc under external force impact is comprehensively obtained. These data can accurately reflect the local influence of external force impacts on the brake disc, providing detailed data support for the subsequent evaluation of local stiffness attenuation. Based on the data of the same-frequency points of the softening stress of the brake disc and the external force impact multi-point contact feedback data, the local stiffness attenuation of the brake disc is evaluated. This step aims to quantitatively evaluate the influence of external force impacts and softening effects on the local stiffness of the brake disc during the use of the brake disc, so as to predict the fatigue life and performance degradation of the brake disc. First, by combining the data of the same-frequency points of the softening stress and the external force impact multi-point contact feedback data, the stiffness change of each local area of the brake disc is calculated according to the update rule of the stiffness matrix.The calculation method of the stiffness matrix is based on the elastic modulus of the material, the friction coefficient of the contact points, and the deformation conditions. The surface of the brake disc is meshed using the finite element analysis (FEA) method to obtain the stiffness matrix of each grid element. During the evaluation of local stiffness decay, the initial stiffness value of each contact point is first calculated. Then, based on the external force impact feedback data, the stiffness of each contact point is adjusted, taking into account the effects of softening effect, temperature change, and material yield. Specifically, a non-linear correction algorithm based on the thermodynamic damage evolution model is used to dynamically update the stiffness according to the changes in temperature and stress. Based on the updated stiffness matrix, the local stiffness decay data is calculated. This data reflects the stiffness changes in different regions of the brake disc during long-term braking, providing an important basis for the subsequent analysis of the displacement and deformation of the brake disc under external force impact. Based on the local stiffness decay data of the brake disc and the multi-point contact feedback data of external force impact, the displacement and deformation analysis of the brake disc under external force impact is carried out. The purpose of this step is to evaluate the deformation and displacement of the brake disc caused by local stiffness decay under external force impact, and further understand the durability and performance of the brake disc. First, by inputting the local stiffness decay data of the brake disc and the multi-point contact feedback data of external force impact into the finite element analysis model, the influence of external force impact on the overall deformation of the brake disc is simulated. During this process, considering the stiffness changes, temperature distribution, and stress state in different regions of the brake disc, a dynamic analysis method is used to calculate the displacement and deformation after external force impact. In the deformation analysis, an incremental dynamic analysis method is used to solve the displacement and stress changes at each moment according to the time step. By applying an external force impact (such as a sudden braking stop or an external impact) in the model, the strain, displacement, and deformation conditions of the brake disc in different regions are calculated to obtain the displacement and deformation data of the brake disc under external force impact.

[0107] Preferably, step S3 includes the following steps:

[0108] Step S31: Normalize the displacement and deformation data of the brake disc under external force impact to obtain the normalized deformation data of the brake disc under external force impact;

[0109] Step S32: Define the bearing boundary of the vehicle brake structure based on the normalized deformation data of the brake disc under external force impact and the softening gradient data of the brake disc under multiple braking to obtain the bearing boundary data of the brake;

[0110] Step S33: Optimize the structural performance of the vehicle brake structure based on the bearing boundary data of the brake to obtain the optimized structural performance data of the vehicle brake.

[0111] In the embodiment of the present invention, in step S31, first, the displacement deformation data of the brake disc under external force impact is normalized to facilitate subsequent analysis and calculation. The purpose of normalization is to eliminate differences in different units or scales, enabling all data to be compared and evaluated under a unified standard. The first step of the processing is to perform maximum-minimum normalization on the displacement deformation data of the brake disc. For a given dataset of the displacement deformation of the brake disc, first calculate the maximum and minimum values of all data points. This normalization method maps all data values to the range between 0 and 1, ensuring the balance of the data and eliminating the inconsistencies caused by different data ranges. Then, the Z-score standardization processing method is used to further process the normalized data. This method converts the data into a standard normal distribution by calculating the mean and standard deviation of the data. In step S32, based on the normalized data of the brake disc deformation under external force impact and the multi-frequency brake disc softening gradient data, the load-bearing boundary of the vehicle brake is defined. The purpose of this process is to accurately determine the working boundary of the brake when it is subjected to external forces, so as to reasonably optimize the structure design. First, the definition of the brake load-bearing boundary depends on the comprehensive analysis of the external force impact response and softening gradient of the brake disc. The normalized data of the brake disc deformation under external force impact provides the deformation characteristics of the brake disc under external forces, showing the displacement distribution and deformation degree of each region. The multi-frequency brake disc softening gradient data describes the characteristic of the brake disc gradually softening during multiple braking processes, revealing the hardness change under different working conditions. Through these data, a comprehensive analysis model containing multiple mechanical parameters can be constructed. In this model, the influence of the deformation caused by external force impact and the softening gradient on the load-bearing capacity of the brake disc is quantified. Using the finite element analysis (FEA) method, the deformation data and the softening gradient data are combined, and the load-bearing limit of each part of the brake under stress is calculated through the mechanical analysis of nodes and elements. Specifically, mechanical parameters such as shear force and normal force can be used to describe the stress conditions at each contact point. By analyzing the contact force distribution under different working conditions, the load-bearing capacity of each contact point is calculated. According to this load-bearing capacity, the load-bearing boundary of the brake under different working conditions is determined, and finally the brake load-bearing boundary data is obtained. In step S33, based on the brake load-bearing boundary data obtained in step S32, the structure data of the vehicle brake is further optimized, aiming to improve the performance of the brake and ensure its efficient and stable operation under complex working conditions. First, the structural performance optimization process starts from a mechanical perspective, considering the stress conditions of each part of the brake under different working conditions, and uses the load-bearing boundary data to evaluate the stress and deformation distribution of each structural part. Through these evaluations, the regions with insufficient load-bearing capacity are identified as the key objects for optimization. The optimization method uses the topology optimization algorithm. This algorithm gradually adjusts the distribution of materials in the design space through an iterative method, and finally obtains the optimal structure that meets the load-bearing requirements.In terms of specific operations, the uneven force distribution and insufficient stiffness areas can be improved by adjusting the geometric shapes of the brake disc, the support structure, and each connecting component. At the same time, considering the influence of the multi-frequency brake disc softening gradient on the structure, the softening effect should also be taken into account during the design adjustment to ensure that the durability of the structure is not significantly affected during long-term use. During the optimization process, structural analysis based on the stress-strain relationship is used to calculate and update the mechanical properties of each component. Especially when the local bearing limit reaches the critical point, the structural parameters should be adjusted in a timely manner to avoid premature material damage. Such optimization can not only improve the performance of the brake but also effectively extend its service life. Finally, through a series of iterative calculations, the optimized data of the brake structure performance are obtained. These data demonstrate the mechanical properties of the optimized structure under different working conditions, such as fatigue resistance, wear resistance, and thermal effects, providing a theoretical basis for the design and manufacture of the brake.

[0112] Preferably, step S32 includes the following steps:

[0113] Step S321: Calculate the deformation transient response peak index for the normalized data of the brake disc deformation under external force impact to obtain the deformation transient response peak index;

[0114] Step S322: Evaluate the difference in the softening distribution of the brake disc for the multi-frequency brake disc softening gradient data to obtain the brake disc softening distribution difference data;

[0115] Step S323: Define the bearing boundary of the vehicle brake based on the deformation transient response peak index and the brake disc softening distribution difference data to obtain the brake bearing boundary data.

[0116] In the embodiment of the present invention, in step S321, the deformation transient response peak index of the normalized data of the brake disc deformation under external force impact is first calculated. The calculation is intended to evaluate the transient response characteristics of the brake disc under the external force impact and determine the limit value of its deformation. Specifically, the deformation transient response peak index is used to characterize the response intensity of the brake disc deformation, especially the deformation peak value of the brake disc under impact load. The calculation of the deformation transient response is based on the deformation time series in the experimental data or simulation data. First, the deformation value of each time step is extracted from the normalized deformation data. Then, the transient deformation amplitude in each time step is calculated, and the maximum deformation value, i.e., the peak value, is determined. If the ratio is high, it indicates that the deformation is severe in a short time, which will cause material fatigue and damage. The deformation transient response peak index finally obtained can be used to measure the performance of the brake disc under extreme working conditions, especially the load-bearing capacity when dealing with impact loads. In step S322, the brake disc softening distribution difference is evaluated, the purpose of which is to analyze the distribution difference of the softening phenomenon on the disc surface during multiple braking processes. This step identifies the change pattern of the softening gradient and evaluates its impact on the braking performance by statistically analyzing the multi-frequency brake disc softening gradient data. First, the multi-frequency brake disc softening gradient data is used to analyze the hardness change of the brake disc after different working cycles to calculate the change of the softening degree over time and space. Specifically, the softening gradient represents the rate of change of the hardness of the surface and internal materials of the brake disc after multiple braking cycles. At the end of each braking cycle, the softening gradient data is obtained by measuring the hardness of multiple points on the surface of the brake disc. In order to evaluate the difference in softening distribution, the brake disc softening gradient data is compared with the original hardness data. Through difference analysis, the softening degree of the brake disc in different areas can be obtained. For example, the inhomogeneity of the softening distribution can be quantified by calculating the variance of the hardness difference in different areas. In step S323, the vehicle brake load boundary is defined according to the deformation transient response peak index obtained in step S321 and the brake disc softening distribution difference data obtained in step S322. The purpose of this step is to comprehensively consider the deformation response and softening characteristics of the brake disc, determine the working limit of the brake structure when subjected to external force impact, and ensure that the brake design can withstand various working conditions. First, the deformation transient response peak index is combined with the softening distribution difference data, and a weighted sum is performed to obtain a comprehensive evaluation index, called the "bearing boundary definition index". Next, the brake structure is analyzed using the bearing boundary definition index. For the brake disc and its supporting structure, the bearing limit of each part is determined according to the bearing boundary index. Through the finite element analysis method (FEA), the stress state of the brake under different working conditions is simulated, the stress and deformation of each component are calculated, and the stability of the structure under external force is evaluated. For example, under high impact conditions, if the bearing boundary definition index of some parts is too low, it will lead to stress concentration or structural instability, and the design needs to be optimized.In this way, the brake bearing boundary data is finally obtained, providing an important basis for further design optimization and performance improvement.

[0117] Preferably, step S4 includes the following steps:

[0118] Step S41: Perform optimization logic learning on the vehicle brake structure performance optimization data to obtain structure performance optimization logic data;

[0119] Step S42: Based on the structure performance optimization logic data, conduct parametric simulation architecture design to obtain a structure performance parameter optimization simulation architecture;

[0120] Step S43: Send the structure performance parameter optimization simulation architecture to the cloud platform to execute the parametric simulation design method for the vehicle brake structure.

[0121] In the embodiment of the present invention, in step S41, the structural performance optimization data of the vehicle brake is subjected to optimization logic learning to obtain the structural performance optimization logic data. The core of this step is based on the historical optimization records of the structural performance. By analyzing the performance of different design schemes under multiple working conditions, the laws of structural optimization are refined, so as to provide a basis for subsequent parametric design. First, collect the structural performance data from different design schemes and experimental results. These data include information on the mechanical properties, temperature changes, friction coefficients, stiffness, etc. of the brake structure. The data is organized in tabular form, where each record represents the performance of a design scheme. Then, apply the optimization algorithm based on gradient descent to analyze the performance data. Through the regression analysis of these data, the key factors affecting the structural performance are extracted, such as structural materials, geometric shapes, load conditions, etc. Further, by constructing a multi-dimensional performance optimization objective function, these influencing factors are coupled with the target performance (such as fatigue resistance, thermal stability, etc.), and optimization algorithms (such as particle swarm optimization, simulated annealing, etc.) are applied to deduce the optimization logic. These algorithms continuously adjust the design parameters to minimize the error and optimize the structural performance of the brake. The result of the optimization logic learning is a logical data set containing the relationship between the structural design parameters and the performance. Through this process, the obtained structural performance optimization logic data provides an accurate optimization path for the subsequent parametric simulation of the structural performance, and can help designers clarify which factors play a decisive role in improving the brake performance. In step S42, using the structural performance optimization logic data obtained in step S41, design the simulation architecture for optimizing the structural performance parameters of the vehicle brake. The purpose of this step is to design a simulation framework suitable for different design schemes according to the optimization logic data to support the subsequent parametric simulation process. First, according to the structural performance optimization logic data, select the appropriate range of design parameters. These design parameters usually include the geometric shape of the brake disc, material parameters, stress distribution, heat conductivity, friction characteristics, etc. After determining the range of these parameters, use them as input conditions to construct a parametric simulation model. Next, select a suitable simulation method (such as the finite element method, boundary element method, etc.) for the design of the simulation architecture. Use the key factors in the structural performance optimization logic data to set the boundary conditions and initial conditions of the simulation model. For example, according to the response to different load conditions in the optimization data, design the corresponding loading method; according to the heat conduction characteristics, determine the distribution conditions of the temperature field. Each parameter and constraint condition in the model will directly come from the optimization logic in step S41 to ensure that the simulation architecture can fully reflect the actual working environment and design requirements. At the same time, when designing the simulation architecture, the coupling relationship of multiple factors needs to be considered, such as the interaction between thermal effects and mechanical properties. During the design process of the simulation architecture, use the information in the optimization logic data to comprehensively consider multiple performance objectives.Each performance metric (such as the thermal stability of the brake disc, fatigue resistance, etc.) will be quantified through simulation results and provide feedback for structural optimization. Ultimately, the optimized simulation framework for structural performance parameters obtained can, during subsequent simulation processes, quickly adjust and optimize the design parameters of the brake according to different design inputs, providing guidance for further design iterations. In step S43, the optimized simulation framework for structural performance parameters obtained in step S42 is sent to the cloud platform to execute the parametric simulation design method for the vehicle brake structure. The core of this step is to transfer the simulation framework from the local environment to the cloud platform and utilize cloud computing resources to perform large-scale parametric simulations to obtain more accurate and efficient design optimization results. First, format the simulation framework designed in step S42 to ensure it can run on the cloud platform. This includes standardizing all input parameters, boundary conditions, and constraint conditions in the simulation model and converting them into a format supported by the cloud platform. The cloud platform typically adopts a cluster computing architecture and can execute simulation tasks in parallel on multiple computing nodes to achieve efficient computing. Then, upload the formatted simulation framework and its related data to the cloud platform. On the cloud platform, multiple simulation tasks will be executed in parallel to perform parametric simulations for different combinations of design parameters. Through the computing power of the cloud platform, a large number of simulation tasks can be executed in a relatively short time, and the performance results of different design schemes can be quickly obtained. The calculation results of the cloud platform will be returned in the form of data files, which contain the simulation result data under different parameter combinations, including the mechanical properties, thermal properties, friction properties, etc. of the brake. Based on these results, designers can evaluate the advantages and disadvantages of different design schemes and further adjust the design parameters according to the simulation data to achieve the optimization design goal. Ultimately, the simulation data returned by the cloud platform provides a reliable basis for the parametric design of the vehicle brake and can support multiple rounds of optimization iterations for the brake design to ensure that the design scheme can meet the performance requirements and actual application needs.

[0122] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the application document are intended to be encompassed within the present invention.

[0123] The above description is only a specific implementation manner of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A parametric simulation design method for a vehicle brake structure, characterized in that: The following steps are involved: Step S1: obtaining vehicle brake structure data; Constructing a three-dimensional virtual model of the vehicle brake based on the vehicle brake structure data to obtain a three-dimensional virtual model of the vehicle brake; Step S2: performing multi-frequency rapid braking response simulation based on the three-dimensional virtual model of the vehicle brake to obtain multi-frequency rapid braking response data; performing multi-frequency brake disc softening gradient identification based on the multi-frequency rapid braking response data to obtain multi-frequency brake disc softening gradient data; performing external force impact brake disc displacement deformation analysis based on the multi-frequency brake disc softening gradient data to obtain external force impact brake disc displacement deformation data; Step S3: defining the brake load boundary according to the external force impact brake disc displacement deformation data and the vehicle brake structure data to obtain the brake load boundary data; optimizing the structure performance of the vehicle brake structure data based on the brake load boundary data to obtain the vehicle brake structure performance optimization data; Step S4: performing parameterized simulation architecture design based on the vehicle brake structure performance optimization data to obtain a structure performance parameter optimization simulation architecture; The structural performance parameter optimization simulation architecture is sent to the cloud platform to execute the parametric simulation design method of the vehicle brake structure.

2. The parametric simulation design method for a vehicle brake structure according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: obtaining vehicle brake structure data; Step S12: performing morphological analysis between different components of the vehicle brake structure data to obtain vehicle brake component morphological data; Step S13: extracting geometric dimensions of different components of the vehicle brake structure data to obtain geometric dimension data of the vehicle brake components; Step S14: constructing a three-dimensional virtual model of the vehicle brake based on the vehicle brake component morphology data and the vehicle brake component geometric dimension data to obtain a three-dimensional virtual model of the vehicle brake.

3. The parametric simulation design method for a vehicle brake structure according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: performing a multi-frequency rapid braking response simulation based on the three-dimensional virtual model of the vehicle brake to obtain multi-frequency rapid braking response data; Step S22: extracting brake disc material properties according to the vehicle brake structure data to obtain brake disc material property data; Step S23: performing multi-frequency brake disc softening gradient identification on the brake disc material property data based on the multi-frequency rapid braking response data to obtain multi-frequency brake disc softening gradient data; Step S24: performing an external force impact brake disc displacement deformation analysis based on the multi-frequency brake disc softening gradient data to obtain the external force impact brake disc displacement deformation data.

4. The parametric simulation design method for a vehicle brake structure according to claim 3, characterized in that: Step S23 includes the following steps: Step S231: performing temperature-stress relationship nonlinear regression analysis on brake disc material property data based on multi-frequency rapid braking response data to obtain temperature-stress relationship nonlinear regression data; Step S232: performing continuous multi-frequency braking distance difference estimation on the multi-frequency rapid braking response data to obtain multi-frequency braking distance difference data; Step S233: performing intervention braking force increment calculation according to the multi-frequency braking distance difference data and the temperature-stress relationship nonlinear regression data to obtain intervention braking force increment data; Step S234: performing thermal friction coefficient attenuation analysis on the brake disc material property data based on the temperature-stress relationship nonlinear regression data and the multi-frequency braking distance difference data to obtain thermal friction coefficient attenuation data; Step S235: performing multi-frequency brake disc softening gradient identification according to the temperature-stress relationship nonlinear regression data, the intervention braking force increment data and the thermal friction coefficient attenuation data to obtain multi-frequency brake disc softening gradient data.

5. The parametric simulation design method for a vehicle brake structure according to claim 4, characterized in that: Step S233 includes the following steps: The stress heteroscedasticity analysis is performed on the nonlinear regression data of temperature-stress relationship to obtain stress heteroscedasticity data; The thermal energy stress density of the brake disc is calculated based on the stress heteroscedasticity data and the multi-frequency braking distance difference data to obtain the thermal energy stress density of the brake disc; Based on the thermal energy stress density of the brake disc, the thermal energy time-dependent change analysis is performed to obtain the thermal energy stress time-dependent change data; The intervention braking force increment is calculated based on the brake disc thermal energy stress density and thermal energy stress time-dependent change data to obtain the intervention braking force increment data.

6. The parametric simulation design method for a vehicle brake structure according to claim 3, characterized in that: Step S24 includes the following steps: Step S241: performing softening degree fluctuation analysis on the multi-frequency brake disc softening gradient data to obtain softening degree fluctuation data; Step S242: quantifying the brake disc stress isofrequency point according to the softening degree fluctuation data to obtain the brake disc softening stress isofrequency point; Step S243: simulating the interface contact response state based on the same frequency point of the brake disc softening stress to obtain interface contact response state data; Step S244: performing an external force impact brake disc displacement deformation analysis based on the brake disc softening stress isofrequency point and interface contact response state data to obtain external force impact brake disc displacement deformation data.

7. The parametric simulation design method for a vehicle brake structure according to claim 6, characterized in that: Step S244 includes the following steps: The brake disc softening stress and interface contact response state data are decomposed by multi-parameter coupling to obtain the brake disc stress-interface contact multi-parameter decomposition data; Perform external force impact multi-point contact feedback analysis on brake disc stress-interface contact multi-parameter decomposition data to obtain external force impact multi-point contact feedback data; Based on the brake disc softening stress same frequency point and external force impact multi-point contact feedback data, the brake disc local stiffness attenuation is evaluated to obtain the brake disc local stiffness attenuation data; The displacement and deformation analysis of the brake disc under external force impact is performed based on the local stiffness attenuation data of the brake disc and the multi-point contact feedback data of the external force impact, and the displacement and deformation data of the brake disc under external force impact is obtained.

8. The parametric simulation design method for a vehicle brake structure according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: normalizing the displacement deformation data of the brake disc due to external force impact to obtain normalized deformation data of the brake disc due to external force impact; Step S32: defining the brake load boundary of the vehicle brake structure data according to the normalized data of the brake disc deformation caused by the external force impact and the multi-frequency brake disc softening gradient data to obtain the brake load boundary data; Step S33: Optimizing the structural performance of the vehicle brake structure data based on the brake load boundary data to obtain vehicle brake structure performance optimization data.

9. The parametric simulation design method for a vehicle brake structure according to claim 8, characterized in that: Step S32 includes the following steps: Step S321: calculating the deformation transient response peak index of the normalized data of the brake disc deformation under external force impact, and obtaining the deformation transient response peak index; Step S322: evaluating the brake disc softening distribution difference on the multi-frequency brake disc softening gradient data to obtain brake disc softening distribution difference data; Step S323: defining the brake load boundary of the vehicle brake structure data according to the deformation transient response peak index and the brake disc softening distribution difference data to obtain the brake load boundary data.

10. The parametric simulation design method for a vehicle brake structure according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing optimization logic learning on the vehicle brake structure performance optimization data to obtain structure performance optimization logic data; Step S42: performing parameterized simulation architecture design based on the structure performance optimization logic data to obtain a structure performance parameter optimization simulation architecture; Step S43: Send the structural performance parameter optimization simulation framework to the cloud platform to execute the parametric simulation design method of the vehicle brake structure.

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