Method and apparatus for tire curing adjustment

Abstract

The application discloses a kind of tire vulcanization adjustment method and device, it is related to tire vulcanization technical field, including obtaining initial temperature rising rate and initial mold filling pressure and corresponding constraint condition;Initial temperature rising rate and initial mold filling pressure are randomly disturbed in the range of constraint condition, and are randomly combined, generate several control parameter sets;The heat-force coupling simulation model of tire vulcanization is constructed, and is respectively parallel simulated based on control parameter set, obtains the thermal behavior data under each group of control parameter set;Obtain the feature allocation proportion weight in each kind of characteristic in thermal behavior data to tire demand data to be vulcanized and weighted, and obtain control parameter set evaluation index;According to control parameter set evaluation index and control parameter set, construct screening display model, and carry out surface analysis, and screen out optimal control parameter set to tire vulcanization control, to solve the problem of uneven vulcanization, high defect rate and energy waste.

Description

Technical Field

[0001] This invention relates to the field of tire vulcanization technology, and more specifically, to a tire vulcanization adjustment method and apparatus. Background Technology

[0002] The "vulcanization process" in tire manufacturing is the final and critical step in the entire production process, which directly determines the final performance of the tire, such as strength, elasticity, wear resistance, and heat resistance.

[0003] Vulcanization is the process by which unvulcanized raw rubber undergoes heat, pressure, and time to form a cross-linked structure between rubber molecular chains, thereby endowing the rubber with excellent physical and mechanical properties.

[0004] The vulcanization process is the final and most crucial step in tire manufacturing. Its purpose is to induce a cross-linking reaction between rubber molecules through heating and pressurization, thereby endowing the tire with the required elasticity, strength, and wear resistance. In practice, the tire blank is placed in a heated mold, where an inflatable bladder applies pressure to keep the tire tightly against the mold cavity. Simultaneously, the mold is heated, rapidly raising the temperature to the vulcanization temperature zone. After a set vulcanization time, the rubber transforms from a plastic state into a highly elastic three-dimensional network structure. Throughout the process, factors such as the heating rate, pressure curve, vulcanization time, and venting control are precisely coordinated to ensure clear tire tread patterns, dimensional stability, and a dense structure, ultimately achieving the finished tire and its performance specifications.

[0005] For example, the invention patent announcement CN117850235A discloses a data-driven learning control method for the temperature of a rubber mixing chamber, belonging to the field of rubber production. This invention primarily addresses challenges in the rubber mixing temperature process, such as different initial states, non-repetitive uncertainties, variable batch lengths, and the inability to obtain accurate models. The control scheme is as follows: establishing a thermodynamic model of the rubber mixing temperature process with actuator constraints; establishing an equivalent iterative linear data model along the batch direction; designing an iterative linear prediction model to compensate for output temperatures that do not reach the desired operating length; designing an iterative extended state observer to estimate different initial states and non-repetitive uncertainties; and designing an iterative adaptive update law and an iterative learning control law for uncertainty compensation to achieve temperature regulation in the mixing process. The iterative learning temperature control method disclosed in this invention comprehensively considers the aforementioned challenging problems, possessing good temperature tracking accuracy and strong anti-interference capabilities, meeting the temperature control requirements of the rubber mixing process.

[0006] For example, the invention patent announcement CN116184807A discloses a method and system for controlling the furnace temperature of a steel rolling mill walking beam reheating furnace. The method includes: using an RBF neural network to identify online sub-models of the first, second, and soaking sections of the reheating furnace; these sub-models together constitute the furnace temperature model; for any sub-model, a two-degree-of-freedom PID controller is sequentially connected to the sub-model; a hybrid optimization algorithm module is used to tune the PID parameters of the two-degree-of-freedom PID controller to obtain the optimal solution; the optimal solution is used to control the sub-model, thereby controlling the furnace temperature model to output the optimal furnace temperature for each section. This invention uses a hybrid optimization algorithm module to tune the parameters of the two-degree-of-freedom PID controller. By setting judgment criteria and implementing a hybrid of simulated annealing algorithm and least squares method, the global optimization performance and efficient local optimization capabilities of both are combined to tune the parameters, enabling the system to quickly track the target value and output stably, thus improving the controller quality.

[0007] The aforementioned disclosed technical solutions have at least the following technical problems: During tire vulcanization, the matching relationship between the heating rate and the applied pressure plays a decisive role in the quality of the final product. If the heating rate is too fast, the rubber surface will prematurely vulcanize, forming a dense structure that hinders internal heat conduction, resulting in "external curing and internal stunting," leading to insufficient structural strength. Conversely, if the heating rate is too slow, it will prolong the molding cycle, reduce production efficiency, and may lead to incomplete vulcanization. Regarding pressure, if applied too early or too high, residual gas in the mold cavity will be difficult to expel, forming defects such as bubbles, scorching, or unclear tread patterns. Conversely, if the pressure is too low or applied too late, the rubber may not be able to tightly adhere to the mold cavity, resulting in blurred tread patterns or rubber material misalignment.

[0008] Existing technologies often use fixed parameters to control pressure and heating rate, lacking a dynamic coordination mechanism that takes into account the tire structure and mold cavity exhaust characteristics. This can easily lead to problems such as uneven vulcanization, high defect rate, and energy waste. Summary of the Invention

[0009] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a tire vulcanization adjustment method and apparatus, which solves the problems of uneven vulcanization, high defect rate, and energy waste by coordinating adaptive analysis and control of heating rate and pressure.

[0010] To achieve the above objectives, the present invention provides the following technical solution:

[0011] A tire vulcanization adjustment method includes: obtaining the initial heating rate and initial filling pressure and their corresponding constraints; randomly perturbing the initial heating rate and initial filling pressure within the constraint range to generate multiple sets of control parameters; performing parallel simulations based on each set of control parameters to obtain corresponding thermodynamic behavior data; assigning weights to the characteristics of the thermodynamic behavior data according to tire demand data, and calculating the evaluation index of each set of control parameters; performing surface analysis based on the set of control parameters and their evaluation index to select the optimal set of control parameters for tire vulcanization regulation.

[0012] In the above scheme, the specific method for obtaining the initial heating rate is as follows: based on the thermal equilibrium requirements of the vulcanization start-up stage, a thermal simulation model of the initial heating process of the rubber compound is constructed to simulate the temperature distribution of the mold cavity under different heating rates and evaluate the uniformity of the temperature field at each moment; under the constraints of equipment response speed and rubber compound thermal stability, the heating rate with the largest temperature field uniformity is selected as the initial heating rate.

[0013] In the above scheme, the method for obtaining the initial filling pressure is as follows: construct a non-Newtonian flow model of the rubber material during the filling process of the mold cavity; simulate the flow and deformation behavior of the rubber material under different filling pressures, and obtain the stress distribution and strain rate distribution at the end of the filling process; calculate the stress distribution uniformity and strain rate gradient index; under the constraints of rubber material shear stability and equipment structural strength, select the filling pressure with the most uniform stress distribution and the lowest strain rate gradient as the initial filling pressure.

[0014] In the above scheme, the method for obtaining the heating rate constraint is as follows: obtain the maximum allowable heating rate of the vulcanizing equipment; obtain the highest safe heating rate of the rubber compound during the heating process; and take the smaller value between the maximum allowable heating rate and the highest safe heating rate as the heating rate constraint.

[0015] In the above scheme, the set of control parameters also includes mold filling pressure. The specific method for obtaining the constraint condition of the mold filling pressure is as follows: determine the first pressure upper limit based on the flow characteristics of the rubber material; determine the second pressure upper limit based on the structural strength of the equipment; and take the smaller value between the first pressure upper limit and the second pressure upper limit as the mold filling pressure constraint condition.

[0016] In the above scheme, the parallel simulation based on each set of control parameters specifically involves: constructing a two-dimensional simulation model of the tire cross section and setting boundary conditions and material properties; using the heating rate as the thermal boundary change rate input and the filling pressure as the boundary driving pressure input; establishing a joint simulation model based on the principle of thermo-mechanical-fluid multiphysics coupling; and inputting multiple sets of control parameters containing different heating rates and filling pressures into the joint simulation model for simulation.

[0017] In the above scheme, the feature allocation weight of thermal behavior data based on tire demand data specifically includes: obtaining temperature distribution data of rubber material in the mold cavity; dividing the mold cavity into multiple temperature sensing areas and calculating the temperature statistics of each area, wherein the temperature statistics include the average temperature and standard deviation of each area; calculating the area temperature difference coefficient based on the temperature statistics of each area; and performing a weighted average of the temperature difference coefficients of all areas to obtain the temperature distribution characteristic value that characterizes the uniformity of the overall temperature distribution.

[0018] In the above scheme, the temperature distribution data includes equivalent stress distribution features. The method for extracting the equivalent stress distribution features is as follows: based on the thermo-mechanical coupling non-Newtonian flow model, obtain the equivalent stress distribution data of the rubber material in the mold cavity at the time of mold filling termination; divide the mold cavity into multiple regions and calculate the average equivalent stress of each region; calculate the range of the average equivalent stress of each region and use it as the equivalent stress distribution feature value characterizing the uniformity of stress distribution.

[0019] In the above scheme, the step of performing surface analysis based on the set of control parameters and their evaluation indices to select the optimal set of control parameters for tire vulcanization control specifically involves: constructing a two-dimensional parameter plane with the heating rate and filling pressure as coordinate axes; constructing a three-dimensional screening and display model with the evaluation indices of each set of control parameters as height coordinates; performing surface fitting on the discrete points in the three-dimensional screening and display model to extract the extreme points of the fitted surface; and outputting the heating rate and filling pressure parameters corresponding to the extreme points as the optimal control set.

[0020] An apparatus for adjusting tire vulcanization includes: an initial data acquisition module for acquiring initial heating rate and initial filling pressure and their corresponding constraints; a control parameter set generation module for randomly perturbing the initial heating rate and initial filling pressure within the constraints to generate multiple control parameter sets; a behavior simulation module for parallel simulation based on each control parameter set to obtain corresponding thermodynamic behavior data; an evaluation module for assigning weights to the characteristics of the thermodynamic behavior data according to tire demand data and calculating evaluation indices for each control parameter set; and a control module for performing surface analysis based on the control parameter sets and their evaluation indices to select the optimal control parameter set for tire vulcanization regulation.

[0021] This invention optimizes the heating rate and mold filling pressure during tire vulcanization, ensuring uniformity of the temperature field and stability of stress distribution, effectively improving the thermal equilibrium of the rubber compound and the fluidity of the mold filling process. Furthermore, by combining the constraints of the equipment and the rubber compound, multiple sets of control parameters are randomly generated and subjected to parallel simulation, from which the optimal combination of process parameters is selected, achieving precise control of the vulcanization process. This technology not only improves the efficiency and stability of the production process but also optimizes the quality of the tire vulcanization process, possessing high engineering application value. Attached Figure Description

[0022] Figure 1 This is a schematic flowchart of a tire vulcanization adjustment method according to the present invention.

[0023] Figure 2 This is a schematic diagram of the structure of a tire vulcanization adjustment device according to the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] Example 1, Figure 1 The present invention provides a tire vulcanization adjustment method, comprising the following steps:

[0026] S1, obtain the initial heating rate and initial mold filling pressure and their corresponding constraints, specifically:

[0027] Based on the thermal equilibrium requirements of the vulcanization start-up stage, a two-dimensional heat conduction model of the initial heating process of the rubber compound is constructed to simulate the temperature distribution of the mold cavity under different heating rates and evaluate the uniformity of the temperature field at each moment.

[0028] Under the premise of meeting the limitations of equipment response speed and rubber thermal stability, the heating rate with the largest uniformity of temperature field is selected and determined as the initial heating rate.

[0029] It should be noted that the two-dimensional heat conduction model for the initial heating process of the rubber compound is constructed by setting a two-dimensional planar region of the tire rubber compound cross section and constructing a transient two-dimensional heat conduction equation.

[0030] Assuming that the boundary temperature increases linearly with the heating rate, this boundary condition is applied to the contact boundary of the mold cavity, while the other boundaries are adiabatic boundaries.

[0031] The finite difference method is used to discretize time and space, and the two-dimensional temperature field distribution at different times is obtained. The standard deviation of the temperature field distribution at a certain target time is used as the uniformity of the temperature field.

[0032] The feasible transient two-dimensional heat conduction equation is as follows:

[0033]

[0034] In the formula, For the density of the rubber compound, For specific heat capacity, The temperature distribution at location (x, y) and time t, is the thermal conductivity.

[0035] It should be noted that assuming the boundary temperature increases linearly with the heating rate and applying this boundary condition to the mold cavity contact boundary, while setting the other boundaries as adiabatic boundaries, aims to accurately simulate the actual heat transfer path during the initial stage of vulcanization. This means that the main heating behavior of the mold cavity on the rubber compound occurs only at the contact surface, and the heat conduction to the interior is constrained by the thermal conductivity of the material itself, rather than by the non-realistic heat conduction from other boundaries, thus achieving reasonable boundary closure of heat conduction behavior. This also offers the following advantages:

[0036] The heating method of the mold cavity temperature control system is usually linear control. Therefore, using a linear heating boundary can accurately correspond to the process characteristics. Setting the non-contact boundary as an adiabatic boundary can effectively avoid the non-physical dissipation of heat on the non-heated surface and improve the accuracy of temperature distribution simulation. The temperature field obtained under this setting is more representative and helps to calculate the real impact of the heating rate on the thermal uniformity of the rubber compound, providing highly reliable heat conduction simulation results for the optimization of the heating rate parameter.

[0037] It should be noted that, to solve the temperature distribution during the initial heating process of vulcanization under set boundary conditions, the finite difference method is used to numerically solve the two-dimensional heat conduction control equations. The time and spatial domains are discretized into several small units, and a system of discrete difference equations in explicit or implicit schemes is constructed. Iterative calculations are performed under initial and boundary conditions to gradually obtain the temperature distribution field corresponding to different time steps. This method can intuitively reflect the diffusion path of temperature and the heat transfer trend within the rubber cross-section, and is suitable for dynamic response modeling of the effect of heating rate changes on thermal equilibrium analysis. Since the finite difference method is widely used in heat conduction problems and the algorithm is mature, related details will not be elaborated further.

[0038] S2, within the constraint conditions, randomly perturbs the initial heating rate and initial filling pressure to generate multiple sets of control parameters, including:

[0039] S21: Determine the initial mold filling pressure based on the stress distribution uniformity and flowable strain rate of the rubber compound;

[0040] In this embodiment, the initial mold filling pressure is determined based on the stress distribution uniformity and flowable strain rate of the adhesive compound, specifically as follows:

[0041] A non-Newtonian flow model of the rubber material during the mold cavity filling process was constructed. Boundary driving pressures were set under different filling pressure conditions. The fluid-structure interaction finite element method was used to simulate the flow and deformation behavior of the rubber material in the mold cavity.

[0042] Obtain the equivalent stress distribution diagram and equivalent strain rate distribution diagram of the rubber compound at the moment of mold filling termination under different pressure conditions;

[0043] Calculate the stress standard deviation and the maximum strain rate gradient;

[0044] Under the premise of satisfying the shear stability of the rubber compound and the structural strength constraints of the equipment, the pressure value with the smallest stress distribution standard deviation and the lowest strain rate gradient is selected as the initial filling pressure.

[0045] It should be noted that the rubber compound typically exhibits non-Newtonian flow behavior during the molding process, which can be characterized using the following Power-Law model:

[0046]

[0047] In the formula, For shear stress, The flow consistency coefficient, For shear rate, The liquidity index;

[0048] The flow and deformation of the rubber compound were simulated using the fluid-structure interaction finite element method, which can be expressed as follows:

[0049]

[0050] In the formula, For fluid velocity, For fluid pressure, The dynamic viscosity of the fluid. It is an external volume force.

[0051] The maximum gradient of strain rate can be expressed by the following formula:

[0052] ,

[0053] In the formula, Let x represent the strain rate, and y represent the coordinates of the equivalent strain rate distribution diagram.

[0054] Under the constraints of satisfying the shear stability of the rubber compound and the structural strength of the equipment, the stress standard deviation and the maximum strain rate gradient under different pressure conditions were analyzed, and the pressure value with the smallest stress distribution standard deviation and the lowest strain rate gradient was selected. Finally, the initial mold filling pressure was determined.

[0055] It should be noted that during the mold filling process, the boundary driving pressure of the mold cavity changes with time. The mold filling pressure is simulated by gradually increasing the boundary driving pressure to simulate the flow and deformation behavior of the rubber material. The above conditions are set as the mold filling pressure boundary conditions.

[0056] It should be noted that the flow index determines the non-Newtonian properties of the fluid; when n is 1, it is a Newtonian fluid.

[0057] S22: Obtain the heating rate constraint and the mold filling pressure constraint, and randomly perturb the initial heating rate and the initial mold filling pressure within the constraint range, and randomly combine them to generate a set of several control parameters.

[0058] The set of control parameters includes a filling pressure and a heating rate.

[0059] In this embodiment, the heating rate constraint includes equipment response speed limitation and rubber thermal stability limitation; wherein, the mold filling pressure constraint includes rubber shear stability limitation and equipment structural strength limitation;

[0060] It should be noted that the heating rate constraint is obtained as follows: based on the test data of the heating element characteristics of the vulcanizing equipment, the maximum temperature rise rate that the equipment can achieve is obtained as the upper limit of the equipment response speed; at the same time, based on the thermal stability test of the rubber compound, the highest safe heating rate that does not cause thermal degradation behaviors such as scorching or premature crosslinking during the heating process is determined, and finally the smaller value of the two is taken as the heating rate constraint.

[0061]

[0062] in, This is the upper limit of the heating rate. This represents the upper limit of the device's response speed. This is the highest safe heating rate.

[0063] It should be noted that the method for obtaining the mold filling pressure constraint is as follows: by using the shear viscosity-strain rate relationship curve of the rubber compound, combined with its non-Newtonian model parameters, the maximum safe shear rate of the rubber compound without shear structural failure is determined, and the corresponding maximum mold filling pressure is then calculated; secondly, based on the finite element mechanical simulation results of the mold cavity structure, the maximum structural pressure that the equipment can withstand under safe operating conditions is determined.

[0064] Ultimately, the smaller of the two values ​​is taken as the mold filling pressure constraint.

[0065] Within the constraints, the initial heating rate and initial filling pressure are randomly perturbed and combined to generate several sets of control parameters.

[0066] S3, based on parallel simulation of each set of control parameters, obtains the corresponding thermodynamic behavior data. Specifically, it constructs a thermo-mechanical-fluid coupled simulation model of tire vulcanization and performs parallel simulations based on the set of control parameters to obtain the thermodynamic behavior data under each set of control parameters.

[0067] In this embodiment, a thermo-mechanical-fluid coupled simulation model of tire vulcanization is constructed, and parallel simulations are performed based on a set of control parameters, specifically as follows:

[0068] A two-dimensional simulation model of the tire cross section was constructed, and boundary conditions and material properties were set. The heating rate was used as the thermal boundary change rate input, and the filling pressure was used as the boundary driving pressure input.

[0069] A heat conduction model is used to describe the temperature field change of the rubber compound, and a fluid-structure interaction model is used to describe the non-Newtonian flow behavior and structural stress response of the rubber compound during the molding process. The influence of the thermal field on the viscosity of the rubber compound is introduced into the flow equation to achieve joint simulation of multiple physics fields including thermo-mechanical-fluid.

[0070] For each set of control parameters, a set of heating rates and filling pressures are input into the simulation model for parallel simulation calculations. The results of temperature field distribution, equivalent stress field distribution, and equivalent strain rate distribution corresponding to each set of control parameters are output.

[0071] It should be noted that the thermal field has a significant impact on the viscosity of the rubber compound. Increased temperature leads to a decrease in viscosity, which in turn affects its flowability and mold-filling behavior. Therefore, when constructing the thermo-mechanical-fluid coupled model, temperature is introduced as a control variable for viscosity into the flow equation, allowing the flow characteristics to dynamically respond to temperature changes. Specifically, by establishing a temperature-viscosity relationship function (such as an Arrhenius-type exponential relationship or an empirical fitting relationship), the local temperature field results are applied to the non-Newtonian fluid viscosity model, achieving dynamic control of the thermal field on the force and flow fields. This allows for accurate simulation of the multi-physics coupling behavior of heat, force, and flow throughout the vulcanization process. The following is a feasible temperature-viscosity relationship expression:

[0072] ,

[0073] In the formula, For the viscosity of the rubber compound, The initial viscosity at the reference temperature. To activate energy, This is the universal gas constant. This represents the local temperature field value.

[0074] This embodiment optimizes the heating rate and mold filling pressure during tire vulcanization using a precise thermo-mechanical-fluid coupled simulation model. A two-dimensional heat conduction model and fluid-structure interaction finite element method ensure the uniformity of the temperature field and the stability of the stress distribution, effectively improving the thermal equilibrium of the rubber compound and the fluidity of the mold filling process. Furthermore, considering the constraints of the equipment and the rubber compound, multiple sets of control parameters are randomly generated and simulated in parallel. The optimal combination of process parameters is then selected, achieving precise control of the vulcanization process. This technology not only improves the efficiency and stability of the production process but also optimizes the quality of the tire vulcanization process, demonstrating high engineering application value.

[0075] S4, based on the tire demand data, assign weights to the characteristics of the thermodynamic behavior data, and calculate the evaluation index for each set of control parameters using a weighted average.

[0076] In this embodiment, the thermodynamic behavior data includes temperature distribution characteristics, equivalent stress distribution characteristics, and equivalent strain rate characteristics;

[0077] Temperature distribution characteristics refer to the temperature field distribution of the rubber compound within the mold cavity over time during tire vulcanization. These characteristics reflect the uniformity of the heating process, thus affecting the vulcanization effect and the final tire performance. Specifically, temperature distribution characteristics are typically quantified by statistical measures such as the standard deviation and maximum temperature difference of temperature values ​​at different locations within the mold cavity to assess temperature uniformity. A more uniform temperature distribution helps improve the consistency of the vulcanization process, reduces the risk of localized overheating or uneven cooling, and thereby enhances the structural stability and performance of the tire.

[0078] Analyzing temperature distribution characteristics has the following advantages for screening and evaluating control parameter sets to address the lack of a dynamic coordination mechanism for tire structure and mold cavity exhaust characteristics:

[0079] Temperature distribution characteristics can help assess the heating uniformity of the rubber compound within the mold cavity. By accurately monitoring and optimizing the temperature distribution, localized overheating or excessive temperature differences can be avoided, reducing variations in rubber compound performance or structural defects caused by uneven temperature, improving thermal uniformity control, and thus enhancing the overall quality of the tire.

[0080] Monitoring and optimizing temperature distribution helps regulate the gas emission pattern within the mold cavity during vulcanization, reducing heat buildup and gas retention. By better coordinating venting characteristics with temperature field changes, and enhancing the coordination between mold cavity venting and heat conduction, pressure fluctuations or uneven deformation caused by poor gas flow or temperature inconsistencies can be avoided.

[0081] As different types of tires have different vulcanization requirements, changes in temperature distribution characteristics can serve as a basis for dynamically adjusting the set of control parameters. By analyzing the temperature distribution characteristics at different times and under different conditions, control parameters such as heating rate and mold filling pressure can be adjusted more precisely, supporting dynamic adjustment and optimization of the set of control parameters to ensure the adaptability and efficiency of different tires in the vulcanization process.

[0082] Optimized temperature distribution characteristics can effectively reduce time waste and energy consumption during the vulcanization process, while ensuring the consistency of vulcanization effect and reducing the negative impact of temperature fluctuations on the performance of rubber compounds, thereby improving production efficiency and the consistency of the final product.

[0083] In this embodiment, the specific method for obtaining the temperature distribution characteristics is as follows:

[0084] Based on the established two-dimensional heat conduction model, the temperature distribution of the rubber compound in the tire mold cavity under different control conditions was simulated.

[0085] The temperature distribution is divided into several sensing regions, and the average value of all temperature data in each sensing region is calculated.

[0086] Calculate the standard deviation of the temperature value in each sensing area, and divide the standard deviation of each sensing area by the average temperature of the corresponding sensing area to obtain the temperature difference coefficient.

[0087] The temperature distribution characteristics are obtained by weighting the difference coefficients of each sensing area, where the weight of the weighted average of the difference coefficients is the proportion of each area.

[0088] Equivalent stress distribution characteristics refer to the distribution of stress states experienced by tire rubber compounds at different locations during vulcanization. By simulating the stress changes experienced by the rubber compound within the mold cavity during filling, stress distribution maps can be obtained in different areas (such as the tread and sidewall). This distribution map reflects the stress concentration or dispersion in different parts of the tire and is a key indicator for evaluating the uniformity of stress experienced by the rubber compound during vulcanization. Equivalent stress distribution characteristics can effectively reveal the stress state of the rubber compound in various regions during molding, playing an important role in optimizing mold filling pressure and ensuring the uniformity of tire structure.

[0089] Analyzing the equivalent stress distribution characteristics is crucial for selecting and evaluating a set of control parameters to address the lack of a dynamic coordination mechanism for tire structure and mold cavity venting characteristics. By analyzing the equivalent stress distribution, the stress state in different regions within the mold cavity can be assessed, ensuring that the rubber compound experiences a uniform stress distribution during vulcanization, avoiding localized defects caused by stress concentration, and thus improving the overall performance and service life of the tire.

[0090] In addition, equivalent stress distribution characteristics can reveal the stress changes in different parts of the tire, helping to select the best filling pressure and heating rate from the set of control parameters to maintain the tire's structural stability, improve structural stability, and avoid tire deformation or cracking caused by uneven stress distribution.

[0091] Within the mold cavity, appropriate filling pressure and heating rate significantly influence the flowability of the rubber compound and the venting process. Analyzing the equivalent stress distribution characteristics can effectively address the specific venting features of the mold cavity, ensuring dynamic coordination between gas venting and rubber compound flow, thereby improving production efficiency and product quality, and enhancing the compatibility between venting and structural design.

[0092] Equivalent stress distribution characteristics, as a quantifiable indicator, can provide data support for screening the optimal set of control parameters, ensuring that the selected control parameters (such as mold filling pressure and heating rate) can meet the tire performance requirements while optimizing the thermo-mechanical-fluid coupling effect in the production process, and providing a quantitative basis for the screening of control parameters.

[0093] The specific method for obtaining the equivalent stress distribution characteristics in this embodiment is as follows:

[0094] A thermo-mechanical coupling non-Newtonian flow model of the rubber compound in the mold cavity was constructed. A fixed initial heating rate and filling pressure were set to simulate the flow and stress behavior of the rubber compound during the entire filling process.

[0095] At the moment of mold filling termination, the equivalent stress values ​​of the rubber material at each node in the mold cavity are extracted to generate an equivalent stress distribution map;

[0096] Based on the equivalent stress distribution map, the mold cavity region is divided, the average equivalent stress of each region is calculated, and the difference between the maximum and minimum values ​​is taken as the equivalent stress distribution feature.

[0097] The equivalent strain rate characteristic is used to characterize the flow activity of the rubber compound in local areas during mold filling. A higher value indicates a faster local deformation rate and stronger flowability. By extracting the equivalent strain rate field of the rubber compound at the moment of mold filling termination from a thermo-mechanical-fluid coupled simulation model, high-gradient regions within the mold cavity are identified, and the maximum gradient value of the equivalent strain rate is calculated as a core indicator for measuring flow continuity and mold cavity filling stability. This characteristic helps to identify potential uneven filling or gas stagnation areas, improving the adaptability of the control parameter set and molding quality.

[0098] Analyzing the equivalent strain rate characteristics is helpful for screening and evaluating the set of control parameters to address the lack of a dynamic coordination mechanism for tire structure and mold cavity venting characteristics. It can also intuitively reflect the flow continuity of the rubber compound in complex structural areas, identify potential flow stagnation or dead zones, and provide a basis for optimizing venting paths and filling strategies. By revealing the spatial distribution differences of the equivalent strain rate, the filling rhythm differences in different areas of the mold cavity can be disclosed, which facilitates the coordination between tire structural details and mold cavity ventilation characteristics.

[0099] Quantitatively evaluating the simulation results of different control parameter sets by combining strain rate characteristics helps to select the optimal combination of heating rate and mold filling pressure under the premise of ensuring flow balance and smooth venting, thereby improving the consistency and pass rate of vulcanization molding.

[0100] The specific method for extracting the equivalent strain rate feature in this embodiment is as follows:

[0101] A finite element model of the material flow during the mold cavity filling process is constructed, non-Newtonian flow characteristics are introduced, and the heating rate and filling pressure corresponding to the set of control parameters are set as boundary input conditions.

[0102] In the simulation of the mold filling process, the equivalent strain rate values ​​at each node in the mold cavity at the time of mold filling termination are extracted.

[0103] Based on global node data, the maximum gradient value of the equivalent strain rate is calculated to characterize the uniformity of the rubber flow in the mold cavity.

[0104] The maximum gradient value is used as the equivalent rate of change.

[0105] In this embodiment, the weighting of various features in the thermodynamic behavior data based on the demand data of the tires to be vulcanized is specifically as follows:

[0106] The demand data for tires to be vulcanized includes Category A, Category B, and Category C demand.

[0107] Based on the demand data of tires to be vulcanized, corresponding allocation weights are set according to experience, and weighted summation is performed to obtain the corresponding set of control parameters and evaluation indicators.

[0108] It should be noted that Category A requirements emphasize temperature control accuracy and structural consistency, such as high-performance passenger car tires, which focus on temperature uniformity and stress distribution; Category B requirements require high molding strength and rubber shear stability, such as off-road tires, which focus on stress distribution and strain rate gradient; Category C requirements emphasize structural safety and process stability, such as commercial heavy-duty tires, which should be considered in a balanced way and allocated relatively equal weights.

[0109] S5, based on the set of control parameters and their evaluation indices, performs surface analysis to select the optimal set of control parameters for tire vulcanization regulation, specifically:

[0110] The control parameter set is used as the horizontal and vertical axes to construct the base of the screening and display model, and the output of the corresponding control parameter set evaluation index is used as the variable to construct the screening and display model.

[0111] The points in the selected display model are fitted into a surface, and the set of control parameters corresponding to the vertices of the surface is used as the optimal set of control parameters to regulate tire vulcanization.

[0112] This application optimizes the control of temperature distribution, stress distribution, and strain rate characteristics during tire vulcanization by constructing a set of evaluation indicators for control parameters and weighting the characteristics in thermodynamic behavior data based on tire demand data. Specifically, temperature distribution characteristics help improve the heating uniformity of the rubber compound, avoiding local overheating or excessive temperature differences, thereby improving the consistency of the vulcanization process and the structural stability of the tire. Stress distribution characteristics help optimize the filling pressure and heating rate, avoiding stress concentration that leads to local defects, and improving the overall performance and service life of the tire. Equivalent strain rate characteristics effectively identify uneven filling or gas retention areas, optimizing the stability of mold cavity filling. By adjusting the weighting of the control parameter set according to the demand data of different types of tires, dynamic adjustment of control parameters is achieved, improving the adaptability, efficiency, and product consistency of the vulcanization process. Furthermore, by using screening and display models and surface analysis techniques, the optimal set of control parameters can be accurately selected, further improving the accuracy and stability of tire vulcanization control.

[0113] This invention optimizes the control of temperature distribution, stress distribution, and strain rate characteristics during tire vulcanization by constructing a set of evaluation indicators for control parameters and weighting features in thermodynamic behavior data based on tire demand data. Specifically, temperature distribution characteristics help improve the heating uniformity of the rubber compound, avoiding local overheating or excessive temperature differences, thereby improving the consistency of the vulcanization process and the structural stability of the tire. Stress distribution characteristics help optimize the filling pressure and heating rate, avoiding stress concentration that leads to local defects, and improving the overall performance and service life of the tire. Equivalent strain rate characteristics effectively identify uneven filling or gas retention areas, optimizing the stability of mold cavity filling. By adjusting the weighting of the control parameter set according to the demand data of different types of tires, dynamic adjustment of control parameters is achieved, improving the adaptability, efficiency, and product consistency of the vulcanization process. Furthermore, by using a screening and display model and surface analysis technology, the optimal control parameter set can be accurately selected, further improving the accuracy and stability of tire vulcanization control.

[0114] Example 2, Figure 2 A tire vulcanization adjustment device is presented, including an initial data acquisition module, a control parameter set generation module, a behavior simulation module, and a control module:

[0115] The initial data acquisition module is used to acquire the initial heating rate, initial mold filling pressure, and corresponding constraints.

[0116] The control parameter set generation module is used to randomly perturb the initial heating rate and the initial filling pressure within the constraint conditions, and randomly combine them to generate several control parameter sets.

[0117] The behavior simulation module is used to build a thermo-mechanical coupling simulation model of tire vulcanization and simulate it in parallel based on the control parameter set to obtain thermo-mechanical behavior data under each control parameter set.

[0118] The evaluation module is used to obtain the weighted proportions of various features in the thermodynamic behavior data based on the demand data of the tires to be vulcanized, and then weight them to obtain the set of control parameters and evaluation indicators.

[0119] The control module is used to construct a screening and display model based on the evaluation index and control parameter set, and to perform surface analysis to select the optimal control parameter set for tire vulcanization regulation.

[0120] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0121] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0122] In the embodiments provided in this disclosure, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0123] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0124] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A tire vulcanization conditioning method, characterized in that, include: Obtain the initial heating rate and initial mold filling pressure, along with their corresponding constraints; Within the constraints, the initial heating rate and initial filling pressure are randomly perturbed to generate multiple sets of parameter control parameters. Parallel simulation based on various control parameter sets is used to obtain corresponding thermodynamic behavior data; Based on the tire demand data, the characteristics of the thermal behavior data are assigned weights, and the evaluation index of each set of control parameters is obtained by weighted calculation. Surface analysis is performed based on the set of control parameters and their evaluation indices to select the optimal set of control parameters for tire vulcanization regulation.

2. The tire vulcanization adjustment method according to claim 1, characterized in that, The specific method for obtaining the initial heating rate is as follows: Based on the thermal equilibrium requirement of the vulcanization start-up stage, a thermal simulation model of the initial heating process of the rubber compound is constructed to simulate the temperature distribution of the mold cavity under different heating rates and evaluate the uniformity of the temperature field at each moment. Under the constraints of equipment response speed and rubber thermal stability, the heating rate with the largest temperature field uniformity is selected as the initial heating rate.

3. The tire vulcanization adjustment method according to claim 2, characterized in that, The method for obtaining the initial filling pressure is as follows: Construct a non-Newtonian flow model of the rubber compound during the mold cavity filling process; The flow and deformation behavior of the rubber compound under different filling pressures were simulated to obtain the stress distribution and strain rate distribution at the end of filling. Calculate the stress distribution uniformity and strain rate gradient index; Under the constraints of rubber shear stability and equipment structural strength, the initial filling pressure is selected as the filling pressure with the most uniform stress distribution and the lowest strain rate gradient.

4. The tire vulcanization adjustment method according to claim 3, characterized in that, The set of control parameters includes the heating rate; the method for obtaining the constraints on the heating rate is as follows: Obtain the maximum permissible heating rate of the vulcanizing equipment; To obtain the highest safe heating rate of the rubber compound during the heating process; The smaller value between the maximum allowable heating rate and the maximum safe heating rate is taken as the heating rate constraint.

5. The tire vulcanization adjustment method according to claim 4, characterized in that, The set of control parameters also includes the filling pressure, and the constraint conditions for the filling pressure are obtained by the following method: The first pressure limit is determined based on the flow characteristics of the rubber compound. The second pressure limit is determined based on the structural strength of the equipment. The smaller value between the first pressure limit and the second pressure limit is taken as the mold filling pressure constraint condition.

6. The tire vulcanization adjustment method according to claim 5, characterized in that, The parallel simulation based on each set of control parameters specifically includes: Construct a two-dimensional simulation model of the tire cross section and set boundary conditions and material properties; The heating rate is used as the thermal boundary change rate input, and the mold filling pressure is used as the boundary driving pressure input. A joint simulation model was established based on the principle of thermo-mechanical-fluid multiphysics coupling. Multiple sets of control parameters, including different heating rates and filling pressures, are input into the joint simulation model for simulation.

7. The tire vulcanization adjustment method according to claim 6, characterized in that, The specific steps for assigning weights to the features of thermal behavior data based on tire demand data are as follows: Obtain temperature distribution data of the rubber compound within the mold cavity; The mold cavity is divided into multiple temperature sensing zones, and temperature statistics for each zone are calculated. The temperature statistics include the average temperature and standard deviation of each zone. The temperature difference coefficient of each zone is calculated based on the temperature statistics of each zone. The temperature difference coefficients of all zones are weighted and averaged to obtain the temperature distribution characteristic value that characterizes the uniformity of the overall temperature distribution.

8. The tire vulcanization adjustment method according to claim 7, characterized in that, The temperature distribution data includes equivalent stress distribution features, and the method for extracting the equivalent stress distribution features is as follows: Based on a thermo-mechanical coupling non-Newtonian flow model, the equivalent stress distribution data of the rubber material in the mold cavity at the moment of mold filling termination are obtained; The mold cavity is divided into multiple regions and the average equivalent stress of each region is calculated. The range of the average equivalent stress in each region is calculated and used as the characteristic value of the equivalent stress distribution that characterizes the uniformity of stress distribution.

9. The tire vulcanization adjustment method according to claim 8, characterized in that, The method involves performing surface analysis based on the set of control parameters and their evaluation indices to select the optimal set of control parameters for tire vulcanization regulation. Specifically: A two-dimensional parametric plane is constructed with heating rate and filling pressure as coordinate axes; The evaluation indicators of each set of control parameters are used as height coordinates to construct a three-dimensional screening and display model; Perform surface fitting on discrete points in the 3D screening and display model, and extract the extreme points of the fitted surface; The heating rate and filling pressure parameters corresponding to the extreme point are output as the optimal control set.

10. An apparatus using the tire vulcanization conditioning method as described in any one of claims 1-9, characterized in that, The initial data acquisition module is used to acquire the initial heating rate and initial mold filling pressure and their corresponding constraints. The control parameter set generation module is used to generate multiple control parameter sets by randomly perturbing the initial heating rate and initial filling pressure within the constraint conditions. The behavior simulation module is used to perform parallel simulations based on various control parameter sets to obtain corresponding thermodynamic behavior data; The evaluation module is used to assign weights to the characteristics of the thermodynamic behavior data based on the tire demand data, and to calculate the evaluation index of each set of control parameters by weighted calculation. The control module is used to perform surface analysis based on the set of control parameters and their evaluation indicators, and to select the optimal set of control parameters for tire vulcanization regulation.

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