A temperature rise simulation method and system of a multi-plate friction clutch

Abstract

This invention provides a method and system for simulating the temperature rise of a multi-plate friction clutch. The method includes: acquiring time-varying parameters during clutch engagement based on a preset friction pair simulation model; determining the peak moment when the clutch's sliding friction power reaches its maximum during engagement based on the time-varying parameters, and extracting the engagement pressure value, relative rotational speed value of the driving and driven plates, and friction coefficient value corresponding to the peak moment; constructing an equivalent steady-state heat flux density function distributed only along the radial direction of the friction plates based on the assumption of uniform pressure distribution, whereby the equivalent steady-state heat flux density function is proportional to the product of the engagement pressure value, relative rotational speed value, friction coefficient value, and friction plate radius corresponding to the peak moment; loading the equivalent steady-state heat flux density function onto each friction surface of the friction pair simulation model, and performing conjugate heat transfer calculations using a steady-state flow field simulation method to obtain the temperature field distribution of the clutch. The temperature rise simulation method of this invention has the advantages of balancing computational accuracy and efficiency while exhibiting good stability.

Description

Technical Field

[0001] This invention belongs to the field of thermal analysis technology for multi-plate friction clutches, specifically relating to a method and system for simulating the temperature rise of a multi-plate friction clutch. Background Technology

[0002] Multi-plate wet clutches are core components of high-end transmission systems such as helicopter tail thrust systems. Their thermodynamic behavior during engagement directly determines the reliability, efficiency, and service life of the transmission. During clutch engagement, a large amount of Joule heat is generated between the friction pairs due to sliding friction. If this heat cannot be dissipated in time by the lubricating oil, it will lead to a sharp increase in local temperature, causing a series of chain failures such as thermal degradation of the friction material, lubricating oil failure, thermal deformation of the mating steel plates, and even adhesion failure. Therefore, accurate temperature rise prediction and thermal management optimization of the clutch during the research and development stage are of paramount importance. With the maturity of computational fluid dynamics and conjugate heat transfer numerical simulation technology, virtual thermal analysis based on three-dimensional solid models has become an important means to replace expensive experimental testing. In existing technologies, the mainstream approach adopts a transient dynamic simulation framework: directly simulating the relative rotational motion between the friction plates and the mating steel plates through dynamic mesh technology, applying a time-varying heat flux density load on the moving boundary, and simultaneously solving the transient Navier-Stokes equations and solid thermal conductivity equations to achieve bidirectional conjugate heat transfer calculation between the fluid-solid domain.

[0003] However, when faced with the complex "5+6" multi-plate configuration and micro-waffle groove friction plates (whose groove scale is typically on the sub-millimeter scale) used in aircraft tail thrust clutches, the aforementioned transient dynamic meshing method suffers from the following insurmountable drawbacks: Geometric complexity makes mesh generation extremely difficult. To accurately analyze the flow of lubricating oil and heat transfer within the microgrooves, extremely fine meshes must be deployed at minute features. The overlapping structure of multiple plates easily results in a total mesh number of tens of millions or even hundreds of millions of elements, far exceeding the capacity of conventional engineering computing platforms. Simultaneously, dynamic meshing suffers from low computational stability and efficiency. Implementing mesh movement in a domain containing complex and minute features can easily lead to deterioration of mesh element quality and the appearance of negative volumes, causing computational iterations to diverge. The extremely small time step required to ensure computational stability results in transient simulations of a single engagement process taking weeks to months, failing to meet the needs of rapid design iterations. Furthermore, the simulation success rate heavily depends on mesh generation strategies, dynamic mesh parameter settings, and solver debugging experience, leading to high uncertainty in the calculation results and significantly insufficient robustness and repeatability of the method.

[0004] Therefore, it is necessary to propose a simulation method for the temperature rise of a multi-plate friction clutch that can balance computational accuracy and efficiency while maintaining good stability. Summary of the Invention

[0005] This invention provides a method and system for simulating the temperature rise of a multi-plate friction clutch that can balance computational accuracy and efficiency with good stability, in order to solve the problems of difficult mesh generation, low stability and efficiency of dynamic mesh calculation, and high uncertainty of calculation results in transient dynamic mesh methods.

[0006] To achieve the above objectives, this invention provides a method for simulating the temperature rise of a multi-plate friction clutch, comprising: Based on a preset friction pair simulation model, time-varying parameters during the clutch engagement process are obtained, including engagement pressure, relative rotational speed of the driving and driven plates, and friction coefficient. Based on the time-varying parameters, the peak moment when the clutch reaches its maximum sliding friction power during engagement is determined, and the engagement pressure value, relative speed value of the driving and driven plates, and friction coefficient value corresponding to the peak moment are extracted. Based on the assumption of uniform pressure distribution, an equivalent steady-state heat flux density function is constructed that is distributed only along the radial direction of the friction plate. The equivalent steady-state heat flux density function is proportional to the product of the engagement pressure value, the relative rotational speed of the driving and driven plates, the friction coefficient value, and the radius of the friction plate at the peak time. The equivalent steady-state heat flux density function is used as the heat source boundary condition and applied to each friction surface of the friction pair simulation model. The conjugate heat transfer is calculated using the steady-state flow field simulation method to obtain the temperature field distribution of the clutch.

[0007] In one embodiment, determining the peak moment when the clutch reaches its maximum slip power during engagement includes: Establish the function of the joint pressure changing with time. The function of the relative rotational speed of the master and slave plates as a function of time. and the function of the friction coefficient with sliding speed According to the formula for friction power Calculate the curve of friction power changing with time, and solve for... The time corresponding to the maximum value ,in, Let be the area of ​​the infinitesimal element of the friction pair.

[0008] In one embodiment, the equivalent steady-state heat flux density function Represented as: , in The heat distribution coefficient, The friction coefficient value at the peak time is [value missing]. The average joint pressure value at the peak time. , The total engagement pressure value at the peak time. Let be the outer radius of the friction plate. Let the inner radius of the friction plate be . The value represents the relative rotational speed of the master and slave plates at the peak moment. The range of values ​​is .

[0009] In one embodiment, before obtaining the time-varying parameters during the clutch engagement process, the method further includes: Based on the actual structural parameters of the multi-plate friction clutch, the friction pair is isolated, and a three-dimensional geometric model of the friction pair is established. The fluid domain is extracted and the boundary is named on the three-dimensional geometric model to obtain an initial friction pair simulation model. The initial friction pair simulation model is meshed to generate a friction pair mesh file for the solver. The physical property parameters of the friction pair mesh file are set to obtain a friction pair simulation model for simulation analysis.

[0010] In one embodiment, when meshing the friction pair simulation model, an unstructured mesh is used, with a minimum mesh size of 7.986 × 10⁻⁶. -5 The maximum grid size is 0.002m, and the grid growth rate is 1.2. The size function adopts the method of combining curvature with adjacent size functions. The grid quality index includes skewness and orthogonality quality, and the grid quality is greater than 0.2.

[0011] In one embodiment, the friction pair simulation model adopts a periodic symmetric model, with the 1 / 4 structure of the clutch as the computational domain.

[0012] In one embodiment, the equivalent steady-state heat flux density function is loaded onto each friction surface of the friction pair simulation model through a user-defined function; The method of using steady-state flow field simulation for conjugate heat transfer calculation includes using a steady-state multi-reference system model for conjugate heat transfer calculation, wherein the steel sheet connected to the input shaft is set as a rotating reference system, and the components and fluid domain connected to the output shaft are set as a stationary reference system. In the conjugate heat transfer calculation, the SST k-ω turbulence model is used to solve the turbulence characteristics in the fluid domain. The conjugate heat transfer calculation adopts a loose coupling method to realize the bidirectional transfer of temperature and heat flux density between the fluid domain and the solid domain. The boundary conditions of the conjugate heat transfer calculation include: setting the position of the shaft hole of the clutch as the velocity inlet, and setting the axial outlet and the circumferential top oil slinger outlet as pressure outlets.

[0013] Based on the same inventive concept, this invention also proposes a temperature rise simulation system for a multi-plate friction clutch, comprising: The parameter acquisition module is used to acquire time-varying parameters during the clutch engagement process based on a preset friction pair simulation model. The time-varying parameters include engagement pressure, relative rotational speed of the driving and driven plates, and friction coefficient. The peak value determination module is used to determine the peak moment when the slip friction power of the clutch reaches its maximum during engagement based on the time-varying parameters, and to extract the engagement pressure value, the relative speed value of the driving and driven plates, and the friction coefficient value corresponding to the peak moment. The heat source construction module is used to construct an equivalent steady-state heat flux density function that is distributed only along the radial direction of the friction plate based on the assumption of uniform pressure distribution. The equivalent steady-state heat flux density function is proportional to the product of the engagement pressure value, the relative rotational speed of the master and slave plates, the friction coefficient value, and the radius of the friction plate at the peak time. The simulation calculation module is used to apply the equivalent steady-state heat flux density function as a heat source boundary condition to each friction surface of the friction pair simulation model, and to perform conjugate heat transfer calculation using a steady-state flow field simulation method to obtain the temperature field distribution of the clutch.

[0014] Based on the same inventive concept, the present invention also proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the temperature rise simulation method as described in any of the preceding claims.

[0015] Based on the same inventive concept, embodiments of the present invention also propose a computer storage medium storing at least one executable instruction that causes a processor to execute the temperature rise simulation method as described in any of the preceding claims.

[0016] Compared with existing technologies, the beneficial effects of this invention are as follows: by decoupling the dynamic thermal process, a new paradigm of steady-state flow field + time-varying heat source is used instead of the traditional transient flow field + transient heat source paradigm, thereby effectively solving the engineering difficulties of complex models being difficult to simulate and poor simulation stability. Since no analytical motion is required, a coarser mesh than the traditional dynamic mesh method can be used, which greatly reduces the computational threshold. The minimum groove height currently verified is 0.35mm, and it is also applicable to larger sizes. Theoretically, as long as the mesh quality requirements are met, the calculation can be performed, which effectively improves the computational efficiency and accuracy of thermal analysis of multi-plate friction clutches. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the temperature rise simulation method for a multi-plate friction clutch in one embodiment of the present invention. Figure 2 Figure 1 shows a schematic diagram of a multi-plate friction clutch for aviation. Figure 2 shows a partial schematic diagram of the multi-plate friction clutch for aviation, with arrow α indicating the direction of oil supply to the shaft. Figure 3 shows a schematic diagram of a simplified friction pair structure separated from Figure 4. Figure 4 shows a schematic diagram of the flow channel structure of the simplified friction pair shown in Figure 4. Figure 5 shows a schematic diagram of the friction plate structure of the simplified friction pair shown in Figure 4. Figure 3 To simplify the friction pair, a schematic diagram is shown where the friction plate and the mating steel plate are arranged in a 1 / 4-section periodically symmetrical manner; where Figure (a) shows the friction plate and Figure (b) shows the mating steel plate. Figure 4 Schematic diagrams of the fluid domain model and solid domain model for simplifying the friction pair; where Figure (a) represents the fluid domain and Figure (b) represents the solid domain; Figure 5 This is a schematic diagram for calculating the friction work using a micro-unit. Figure 6 This is a schematic diagram of the friction pair engagement process; Figure 7 for Figure 1 The diagram shows the boundary condition settings in the temperature rise simulation method for a multi-plate friction clutch; where arrow β1 indicates the oil inlet and arrow β2 indicates the oil outlet. Figure 8 This is a flowchart of the simulation analysis in the temperature rise simulation method for a multi-plate friction clutch. Figure 9 This is a schematic diagram of the temperature rise simulation system for a multi-plate friction clutch in an embodiment of the present invention; Figure 10 This is a schematic diagram of an electronic device in an embodiment of the present invention.

[0019] Explanation of reference numerals in the attached diagram: 1 Input shaft mating steel plate, 2 Output shaft friction plate, 3 Lubricating oil inlet, 4 Lubricating oil outlet, 5 Piston, 6 Baffle, 7 Heat source interface. Detailed Implementation

[0020] To make the objectives, technical solutions and advantages of this disclosure clearer, the following detailed description is provided in conjunction with specific embodiments and with reference to the accompanying drawings.

[0021] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this disclosure pertains. The terms "first," "second," and similar terms used in the embodiments of this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0022] See also Figure 1-8 This invention provides a method for simulating the temperature rise of a multi-plate friction clutch, comprising the following steps: S1: Based on the preset friction pair simulation model, obtain the time-varying parameters during the clutch engagement process. The time-varying parameters include engagement pressure, relative speed of the driving and driven plates, and friction coefficient. S2: Based on the time-varying parameters, determine the peak moment when the clutch reaches its maximum slip friction power during engagement, and extract the engagement pressure value, relative speed value of the driving and driven plates, and friction coefficient value corresponding to the peak moment; S3: Based on the assumption of uniform pressure distribution, an equivalent steady-state heat flux density function is constructed that is distributed only along the radial direction of the friction plate. The equivalent steady-state heat flux density function is proportional to the product of the engagement pressure value, the relative rotational speed of the master and slave plates, the friction coefficient value, and the radius of the friction plate at the peak time. S4: The equivalent steady-state heat flux density function is used as the heat source boundary condition and applied to each friction surface of the friction pair simulation model. The conjugate heat transfer is calculated using the steady-state flow field simulation method to obtain the temperature field distribution of the clutch.

[0023] In this embodiment, before step S1, model preprocessing operations such as model simplification of the friction clutch system, separation of friction pairs, 3D modeling, fluid domain / solid domain extraction, and mesh generation are required.

[0024] Specifically, such as Figure 2As shown, the simulation analysis in this embodiment applies to a high-speed multi-plate wet friction clutch for aviation, employing a complex "5+6" multi-plate configuration. This includes 5 output shaft friction plates 2, 6 input shaft mating steel plates 1, a lubricating oil flow channel, a lubricating oil inlet 3, a lubricating oil outlet 4, a piston 5, and a baffle 6. The oil supply method is shaft-driven lubrication, where lubricating oil is delivered through the input shaft and then flung into the friction clutch by centrifugal force. The lubricating oil flows out circumferentially through the waffle-textured grooves on the friction plate surface, achieving lubrication. The waffle grooves are orthogonal grid-like oil groove structures, with a groove height of only 0.35 mm and a width of 1.25 mm, and each side has 28 orthogonal grooves arranged horizontally and vertically. Based on this, the input shaft unit of this multi-plate wet friction clutch is simplified to a hole input, and the friction pairs (i.e., the friction plates and mating steel plates) are analyzed independently.

[0025] First, the friction pair is separated based on the actual structural parameters of the multi-plate friction clutch. Then, a three-dimensional geometric model of the friction pair is established based on the actual structural parameters of the friction pair, namely the friction plate waffle groove model and the dual steel plate model.

[0026] Specifically, the model is created using the 3D modeling software Solidworks. Then, as... Figure 3 As shown, based on the symmetrical structure of the friction plate and steel plate, a periodic symmetric model is adopted, selecting 1 / 4 of its structure as the computational domain for periodic symmetric calculations. This approach can reduce the number of nodes and elements by several times or even orders of magnitude, thereby significantly shortening the computation time and allowing for the use of finer meshes in the retained model parts to improve accuracy. Simultaneously, unnecessary input shafts, output shafts, and non-core components such as pistons and baffles are simplified, while retaining the main lubricating oil channel structure. Then, the friction plate waffle groove model is assembled with the dual steel plate model to obtain the overall friction clutch model.

[0027] Then, the fluid domain is extracted and the boundaries are named from the three-dimensional geometric model to obtain the initial friction pair simulation model.

[0028] like Figure 4As shown, a solid domain model and a fluid domain model are extracted based on the friction clutch model. These two models together constitute the initial friction pair simulation model, exported in ".x_t" format. The fluid domain model is extracted using Boolean operations in AnsysWorkbench. The solid domain model includes solid components such as the friction plates and their counterparts, while the fluid domain model includes the waffle grooves on the friction plate surface and the lubricating oil channels between the friction plates and the steel plates. In this embodiment, the friction clutch system is disassembled to separate the friction pair, and the fluid domain is extracted from the solid domain using Boolean operations. Finally, a clutch lubrication and heat generation analysis model containing both solid and fluid domains is established, i.e., the initial friction pair simulation model. Then, the initial friction pair simulation model is named, with the inlet boundary, outlet boundary, heat source interface, and wall surface of the friction pair named and labeled. In this embodiment, the initial friction pair simulation model is imported into DesignModeler for boundary editing. DesignModeler assists Fluent Meshing in boundary processing, allowing for pre-setting of the boundaries. The boundaries are complex, and Fluent Meshing alone will make mistakes in automatic determination.

[0029] Then, based on the initial friction pair simulation model, mesh generation is performed to generate the friction pair mesh file for the solver.

[0030] Specifically, the initial friction pair simulation model with named boundaries is imported into Fluent Meshing. After import, geometric defects in the initial friction pair simulation model are checked and repaired. Then, boundary labels, such as inlet and wall, are defined and assigned, and local size functions are set to control the mesh density of key areas. Fluent Meshing has a mesh filtering function that can automatically identify key areas with poor meshes, which are generally narrow areas such as friction plate grooves and flow channels. Next, surface meshes are created using wrapping or surface mesh generation methods, and volume meshes are generated using multi-region scanning or Poly-Hexcore methods. Finally, mesh quality checks and smoothing optimizations are performed to improve meshes with a quality lower than 0.2, ensuring that skewness, orthogonality, and other indicators meet the computational requirements. Finally, a mesh file that can be used in the Fluent solver is exported.

[0031] The friction pair was meshed using an unstructured grid with three boundary layers in Fluent Meshing. The growth rate was 1.2 and the transition ratio was 0.272. This module did not require setting the first layer height, and the overall objective was a minimum mesh size of 7.986 × 10⁻⁶. -5The maximum mesh size is 0.002m, the mesh growth rate is 1.2, and the size function combines curvature and neighboring size functions. This approach perfectly captures the model's geometry while ensuring sufficiently fine mesh resolution in key physical regions, achieving fully automatic, high-quality, and high-efficiency mesh generation. The total number of meshes is 4,197,538, significantly less than the overall mesh size for the friction pair, and can be reasonably calculated using everyday computers. Mesh quality is evaluated using orthogonal quality. Mesh cells with orthogonal quality below 0.2 are optimized and reconstructed. After optimization, the orthogonal quality of all cells is greater than 0.2, meeting the computational accuracy requirements. Specifically, meshes with quality below 0.2 are re-meshed. In this embodiment, based on Fluent Meshing's mesh filtering function, meshes with quality below 0.2 are automatically filtered out and re-meshed. In other embodiments, the mesh can be refined and re-divided in local low-quality areas to improve the cell shape; the mesh generation algorithm and parameter settings (such as optimizing cell type, smoothing and size transition control) can be adjusted to improve mesh orthogonality; at the same time, complex geometric areas can be appropriately simplified or rounded to reduce the adverse effects of sharp corners and high curvature areas on mesh quality.

[0032] Finally, the physical property parameters of the friction pair mesh file are set to obtain the friction pair simulation model for simulation analysis.

[0033] Specifically, the friction pair mesh file was imported into Ansys Fluent, and the material parameters were set in the corresponding material modules. The material parameters (physical properties) of the lubricating oil included density, thermal conductivity, specific heat capacity, and dynamic viscosity; all were selected as typical values ​​under 80℃ conditions. Relevant data were obtained from lubricating oil product technical manuals and literature. Considering the limited temperature variation range under the operating conditions in this study, isothermal physical property parameters were used for numerical simulation. In this embodiment, the friction plate was selected as a composite material of two sintered together, with a high-temperature resistant paper-based material on the outer side, and the paired steel plate material was heat-treated alloy steel; at the same time, the material parameters of the input shaft, output shaft, piston, and baffle were set, and each material was edited and then imported.

[0034] In this embodiment, the equivalent steady-state heat flux density function Represented as: ; in The heat distribution coefficient, This represents the friction coefficient at its peak value. This represents the average joint pressure value at the peak time. , This represents the total engagement pressure at peak time. Let be the outer radius of the friction plate. Let the inner radius of the friction plate be . This represents the relative rotational speeds of the master and slave plates at peak time. The range of values ​​is .

[0035] The equivalent steady-state heat flux density function in this embodiment The derivation process is as follows.

[0036] In this embodiment, when the multi-plate wet friction clutch engages, the input shaft mating steel plate 1 and the output shaft friction plate 2 are pressed against each other by the pressure supplied by the piston. The relative speed difference between them generates a frictional torque on the surface of the friction pair, thereby driving the input and output shafts to move together. This frictional torque also generates frictional work, thus generating heat. Assuming that the pressure between the friction pairs is uniformly distributed, and considering that the radial linear velocity of the friction pair varies with the radius, the frictional torque at different radii will also differ, thus affecting the distribution of heat flux density on the mating steel plates and friction plates. For ease of calculation, the friction pair region is divided into integrable infinitesimal elements in the radial direction, specifically as follows: Figure 5 As shown.

[0037] Based on the above conditions, the frictional work on the dA ring at the radius of the friction pair can be approximately calculated as follows: (1) In the formula, This is a function of the total engagement pressure of the friction pair, in N. , denoted by , and by , respectively, the inner and outer radii of the friction pair, in meters; dA is the area of ​​the integrable infinitesimal friction pair element divided along the radial direction on the friction surface. , The range of values ​​is is a variable, representing any radial coordinate variable on the friction plate between the inner and outer diameters. for The infinitesimal increment, Let be a function of the friction coefficient of the mating surfaces. Let be the relative rotational speed function of the friction plate and the mating steel plate.

[0038] Based on the assumption of uniform heat flux distribution in a circular ring, the radius of the friction pair is... Heat flux density function at The calculation formula is: (2) In the formula, The average joint pressure varies with time. .

[0039] From the above formulas, it can be seen that when the pressure is uniformly distributed, the heat flux density is related to the average joint pressure, the coefficient of friction, the relative rotational speed of the driving and driven plates, and radius Proportional, that is: (3) It is known that the average engagement pressure, friction coefficient, and relative rotational speed of the driving and driven plates all vary at different times. Therefore, the heat flux density generated at different times also varies. Under normal operating conditions, engineers are most concerned with the highest temperature under the most severe operating conditions. The highest temperature usually occurs at the moment of maximum sliding friction power, or slightly later due to thermal inertia. Therefore, [the following is selected]... The operating parameters at the peak of the friction power are the most reasonable and direct physical equivalent method for predicting the highest steady-state temperature field.

[0040] Therefore, in step S1, the time-varying parameters during the clutch engagement process are first obtained, and the time-varying parameters include the total engagement pressure, the relative speed of the driving and driven plates, and the friction coefficient. In step S2, determining the peak moment when the clutch's slip friction power reaches its maximum during engagement includes: When the clutch engages, the hydraulic oil pushes the piston through the spring against the friction pair, causing the mating steel plates to move towards the friction plates. Therefore, the total engagement pressure between the friction pair and the mating steel plates can be assumed to be: (4) In the formula, Hydraulic oil pressure, The spring constant is... This represents the spring deformation. Based on this, the average pressure is... The function that changes with time is .

[0041] When the clutch friction pair engages, the piston pushes the mating steel plate at one end to move axially towards the friction plate, generating positive engagement pressure. Driven by friction, this produces torque, thereby driving the output shaft to move. Because the input shaft rotates at high speed, the output shaft speed abruptly changes to match the output speed during engagement. The engagement process is as follows: Figure 6 As shown.

[0042] Depend on Figure 6 It can be seen that the relative rotational speed of the master and slave plates changes as a linear function of time. It can be written as: (5) In the formula, For input shaft speed, This refers to the synchronization speed time.

[0043] During the engagement of a friction clutch, the friction coefficient is not a fixed material constant, but a parameter that dynamically changes with operating conditions. It can be understood as a system response characteristic rather than a simple inherent property; it is a multidimensional function that varies with speed, pressure, temperature, material, and lubrication state. In this embodiment, the friction coefficient is a function... Represented as: (6) In the formula, Let be the sliding velocity, and a, b, c, and d be empirical constants obtained by fitting experimental data. In this embodiment, the equivalent steady-state heat flux density function is loaded onto each friction surface of the friction pair simulation model through a user-defined function. Specifically, the heat of the friction pair is transformed into an equivalent steady-state heat flux density function of the friction ring that varies with its radius. Heat sources were applied to the friction surfaces (i.e., the 10 heat source interfaces 7) of the "5+6" multi-plate friction clutch, and the heat flux density function was set to vary with the radius of the ring. Ten files were written using UDF (User-Defined Function), compiled, and then loaded onto the 10 surfaces where the friction plates and the mating steel plates are joined, thus precisely loading the heat flux density function that varies with the radius onto the 10 friction contact surfaces.

[0044] Then, according to the formula for friction power Calculate the curve of friction power changing with time, and solve for... The moment corresponding to the maximum value is used to determine the moment corresponding to the peak value of the friction power. Extracting peak time Corresponding time-varying parameter values ; Then, based on the assumption of uniform pressure distribution and the formula for calculating heat flux density, a model is constructed along the radial direction of the friction plate. Equivalent steady-state heat flux density function of the distribution: (7) In the formula, The heat distribution coefficient is set to 1 in this simulation. The interface is shared by the friction plate and the steel plate, so it can be automatically distributed by software, such as using Fluent's default heat distribution method based on material properties.

[0045] In this embodiment, to determine the values ​​of parameters a, b, c, and d in the model, it is first necessary to obtain friction coefficient data under different working conditions through friction performance tests. Specifically, different sliding speeds are set on a friction test bench (such as an inertial test bench or a disc friction test machine). By measuring the corresponding instantaneous friction coefficient under normal pressure and temperature conditions, a set of discrete test data samples is obtained. Based on this, equation (6) is used as the objective function model, and the experimental data is fitted using the nonlinear least squares method. The objective function is to minimize the sum of squared errors between the model predictions and the experimental measurements. The optimal estimates of parameters a, b, c, and d are obtained by solving a numerical optimization algorithm (such as the Levenberg-Marquardt algorithm). After the fitting is completed, the fitting accuracy can be evaluated by the coefficient of determination (R²) or the mean square error (MSE), and verified by independent experimental data to ensure that the model parameters have good reliability and generalization ability.

[0046] Step S4 aims to perform steady-state heat source loading mapping, steady-state flow field boundary condition setting, and conjugate heat transfer solution calculation. In this embodiment, a steady-state multiple reference frame model is used for conjugate heat transfer calculation, where the dual steel plate connected to the input shaft is set as a rotating reference frame, and the component and fluid domain connected to the output shaft are set as a stationary reference frame. The SST k-ω turbulence model is used to solve for the turbulence characteristics in the fluid domain. The boundary conditions are set as follows: the axial hole is the velocity inlet, and the axial outlet and the circumferential top oil-throwing outlet are the pressure outlets. The aforementioned equivalent steady-state heat flux density function is loaded onto 10 friction contact surfaces through a user-defined function. The loosely coupled conjugate heat transfer option is enabled to realize heat exchange between the fluid domain and the solid domain. Each friction plate and the dual steel plate are selected as monitoring objects. After the iterative calculation converges, the temperature field distribution cloud map and data of each friction plate and the dual steel plate are output.

[0047] In the numerical simulation of this embodiment, the turbulent characteristics within the fluid domain are solved and analyzed. The k-ω two-equation turbulence model is used for numerical simulation in the viscous model interface. This model, by solving the two governing equations of turbulent kinetic energy k and specific dissipation rate ω, can better balance the computational accuracy of near-wall flow and mainstream turbulence, and is particularly suitable for flow fields with significant boundary layer separation or large pressure gradients. The SST (Shear Stress Transport) mode is selected in the sub-options to combine the advantages of the standard k-ε and k-ω models, achieving a smooth transition between high and low Reynolds number regions and improving the resolution of velocity and temperature gradients near the wall.

[0048] In the model constants section, the system's default turbulence constants are retained, including the far-field turbulent thermal diffusivity. Turbulent dissipation rate and diffusion coefficient turbulent viscosity model constants Turbulent viscosity limiting factor These parameters, and the coefficients they represent, are empirical correction values ​​used to ensure the stability of turbulent kinetic energy and dissipation rate under different flow conditions. Furthermore, internal and external... The values ​​are set to 0.075 and 0.0828 respectively, representing the Prandtl numbers for internal and external turbulent kinetic energy. The values ​​are 1.176 and 1.0 respectively, to maintain the physical consistency of turbulent energy diffusion and heat diffusion.

[0049] In the k-omega options, Low-Re correction is not selected, indicating the use of the standard high Reynolds number form, suitable for cases where the wall has been reinforced. The wall function part uses the "correlation" form, which can correct turbulent shear stress through the wall function relationship. "Curvature Correction" and "Strain / Curvature Correction" are enabled in the options, along with "Production Kato-Launder" and "Production Limiter" to limit excessive growth of turbulent production terms, thereby improving numerical stability and avoiding numerical divergence caused by excessive local energy. In the curvature correction option, the CCURV model coefficients are set to a constant of 1, indicating that the default correction strength is maintained.

[0050] In the boundary condition settings for the simulation: a steady-state multi-reference frame model is used for conjugate heat transfer calculations. The steel plate connected to the input shaft is set as a rotating reference frame, with the rotation center being the axis (coinciding with the Z-axis), rotating clockwise. The components connected to the output shaft and the fluid domain are set as stationary reference frames. Specifically, a steady-state MRF solution method is used, setting corresponding rotational speeds for the rotating input shaft and the paired steel plate connected to the input shaft. The lubricating fluid rotates at the same speed as the output shaft, while the shaft and output shaft remain relatively stationary, creating a relative speed difference.

[0051] like Figure 7 As shown, the inlet boundary of the friction clutch is set to the position of the shaft bore, and the outlet boundary is set to 7 locations: the left and right axial outlet positions and the circumferential top oil slinger outlet position. The inlet of the shaft bore is set as a velocity inlet, with a given oil flow rate and inlet temperature. The outlet of the shaft bore is set as a pressure outlet, and to prevent oil backflow, the outlet temperature is also set to the inlet temperature value. Then, the boundary surfaces of the friction pair are located, and UDF heat sources are added to the shadow locations of the 10 interfacial surfaces. In Ansys Fluent, the interface (the contact surface between the friction plate and the mating steel plate) generates two boundaries: one called "wall" and the other called "wall_shadow". The heat sources are applied to these two boundaries, allowing heat to be transferred simultaneously to both the friction plate and the mating steel plate.

[0052] In the task settings, a steady-state MRF solution is used. The pseudo-timescale part is set to Automatic mode to ensure stability during time progression, with the time scaling factor set to 1. The length-scale method uses the "Conservative" mode to ensure stable flow field changes during convergence. The iteration parameter is set to 5000 iterations, with a reporting interval of 20, meaning residual monitoring results are output every 20 iterations. A stable state is determined when the residual value changes insignificantly, and the monitored friction plates, steel plates, and other temperatures no longer change. If the residual does not meet the criteria after 5000 iterations, or diverges, it generally indicates unreasonable boundary conditions. In this case, the number of iterations can be increased first, followed by modifying the mesh quality. The profile data update interval is also set to 20 to update the flow field information in real time.

[0053] Simultaneously, the "Loosely Coupled Conjugate Heat Transfer" option is enabled to achieve thermal coupling calculations between the fluid and solid domains. This means that temperature and heat flux can be transferred between the two boundaries, enabling the analysis of heat-fluid-solid coupling effects. The initial temperature is set to the lubricating oil temperature; other settings can remain at their defaults. Conjugate heat transfer is a method that simultaneously solves the temperature fields in both the fluid and solid domains, automatically satisfying continuous temperature and heat flux at the interface. In the solution execution section, selecting "Start Calculation" will initiate the iterative process.

[0054] In the results settings interface, each friction plate and its counterpart steel plate can be selected in advance as the main monitoring objects, and their interface temperature cloud map and data output can be set respectively. Then, the temperature rise due to heat flux coupling of the friction pair is simulated and calculated, and the temperature rise result cloud map and data are exported for verification. By comparing the simulation calculation values ​​of this embodiment with the experimental limit parameters, it can be determined whether burnout has occurred. The limit values ​​can generally be determined experimentally. This simulation calculation can be completed in approximately 8 hours using a computer with a 14900KF processor, 64G of memory, and 24 cores.

[0055] In summary, this Fluent setup uses the SST k-ω turbulence model to solve for the turbulence characteristics in the fluid domain. By combining wall functions, curvature correction, and thermal-fluid coupling solution strategies, it can accurately capture the turbulence structure, temperature distribution, and heat transfer characteristics in friction pairs or complex flow fields, providing a stable and reliable turbulence foundation for thermal-fluid-structure interaction simulation.

[0056] Traditional dynamic meshing methods, when processing a model with the same 4.19 million mesh elements, require at least 2 to 5 days of computation on a 14900KF, 64GB RAM, and 24-core computer. Furthermore, dynamic meshing is generally a transient calculation, highly prone to errors, and has poor compatibility with UDFs. In contrast, the simulation method in this embodiment can stably load 10 UDFs. To verify the accuracy of this method, bench tests were conducted on the German ZK test bench at Hangzhou Hongqi Friction Co., Ltd. The results show that the maximum error between the simulation and experimental results is only 6.97%. Regarding computational efficiency, steady-state calculations mainly require a certain number of iterations; too few steps can lead to computational instability, but typically 5000 steps are not needed; 2000 to 3000 steps are sufficient to achieve stable convergence. If the calculation diverges, it is usually due to poor boundary conditions or poor mesh quality, which is a significant advantage over dynamic meshing. Regarding structural parameters, the main factor affecting mesh quality is the current verified minimum trench height of 0.35mm, and it is also applicable to larger sizes. Theoretically, as long as the mesh quality requirements are met, calculations can proceed. This method does not impose a particular limitation on the number of friction plates and mating steel plates, and can be applied to various multi-plate combinations. This embodiment uses 5+6 plates as an example for illustration, but those skilled in the art should understand that, provided that mesh quality requirements are met and computational resources allow, this method is also applicable to other plate configurations.

[0057] This embodiment presents a temperature rise simulation method for a multi-plate friction clutch. Addressing the engineering challenges of complex 3D meshes, low transient simulation efficiency, and poor stability in multi-plate friction pairs of helicopter tail-thrust clutches, this method proposes an efficient thermal simulation strategy based on the steady-state MRF method. The breakthrough lies in mapping the time-varying heat source parameters during dynamic engagement to the steady-state flow field calculation based on the peak moment of the highest sliding friction power. This successfully avoids the computational bottlenecks and uncertainties inherent in traditional dynamic meshing techniques, thus achieving efficient analysis of the temperature field of complex multi-plate structures while maintaining accuracy. In this embodiment, the clutch system is a high-power, high-speed tail-thrust clutch for aviation. Its friction pair consists of 5 friction plates coupled to 6 paired steel plates, simultaneously accompanied by heat source loading and conjugate heat transfer from lubricating oil. Given that the selected friction plate groove type is a waffle groove, the groove height of this model is only 0.35mm, the width is 1.25mm, and each side has 28 orthogonal grooves horizontally and vertically. This presents a significant challenge for mesh generation, making it difficult for general computers to simulate this model. Therefore, within the time limit, a steady-transient model is used to incorporate parameters such as time, radius, friction surface contact pressure, and relative rotational speed of the driving and driven plates into the heat variation. Simultaneously, these parameters are applied to the heat source interface and loaded onto the friction contact wall via a UDF function using the Fluent module in ANSYS simulation software. The heat source loading is set to vary with the radius based on the peak value of the highest sliding friction power. This proposes a new calculation method for the overall simulation of the friction pair. This method can effectively simulate the relative rotation of the friction plates and simultaneously exchange heat with the lubricating oil, thus simulating the overall temperature rise of the friction pair. Methodologically, it solves the problem of computational divergence caused by the large number of meshes in complex multi-plate friction systems, which is difficult to address with traditional transmission meshes. This provides good guidance for temperature rise control in aerospace friction systems.

[0058] In other embodiments, the multi-plate friction clutch can also be other multi-plate combination forms or other high-power, high-density friction clutches such as those used in high-speed ships and automobiles; the waffle groove type of the clutch friction plates involved can also be other complex groove types such as radial composite grooves and double circular arc grooves.

[0059] The foregoing has described specific embodiments of the present invention. In some cases, the actions or steps described in the embodiments of the present invention may be performed in a different order than that shown in the embodiments and the desired results may still be achieved. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0060] Based on the same concept, embodiments of the present invention also provide a temperature rise simulation system for a multi-plate friction clutch. This system is applied to servers. Figure 9As shown, the temperature rise simulation system for a multi-plate friction clutch includes: a parameter acquisition module 10, a peak value determination module 20, a heat source construction module 30, and a simulation calculation module 40. Among them, The parameter acquisition module 10 is used to acquire time-varying parameters during the clutch engagement process based on a preset friction pair simulation model. The time-varying parameters include engagement pressure, relative speed of the driving and driven plates, and friction coefficient.

[0061] The peak value determination module 20 is used to determine the peak moment when the clutch reaches its maximum sliding friction power during engagement based on time-varying parameters, and to extract the engagement pressure value, the relative speed value of the driving and driven plates, and the friction coefficient value corresponding to the peak moment.

[0062] The heat source construction module 30 is used to construct an equivalent steady-state heat flux density function that is distributed only along the radius of the friction plate based on the assumption of uniform pressure distribution. The equivalent steady-state heat flux density function is proportional to the product of the engagement pressure value, the relative rotation speed of the driving and driven plates, the friction coefficient value, and the radius of the friction plate at the peak time.

[0063] The simulation calculation module 40 is used to apply the equivalent steady-state heat flux density function as the heat source boundary condition to each friction surface of the friction pair simulation model, and to perform conjugate heat transfer calculation using the steady-state flow field simulation method to obtain the temperature field distribution of the clutch.

[0064] For ease of description, the above system is described by dividing it into various modules based on their functions. Of course, in implementing the embodiments of the present invention, the functions of each module can be implemented in one or more software and / or hardware.

[0065] The system described in the above embodiments is applied to the corresponding method in the foregoing embodiments and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0066] Based on the same inventive concept, embodiments of the present invention also provide an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the temperature rise simulation method as described in any of the above embodiments.

[0067] This invention provides a non-volatile computer storage medium storing at least one executable instruction that can execute the temperature rise simulation method described in any of the above embodiments.

[0068] Figure 10This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 501, a memory 502, an input / output interface 503, a communication interface 504, and a bus 505. The processor 501, memory 502, input / output interface 503, and communication interface 504 are interconnected internally via the bus 505.

[0069] The processor 501 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention.

[0070] The memory 502 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 502 can store the operating system and other application programs. When the technical solution provided by the method embodiment of the present invention is implemented by software or firmware, the relevant program code is stored in the memory 502 and is called and executed by the processor 501.

[0071] Input / output interface 503 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

[0072] Communication interface 504 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0073] Bus 505 includes a pathway for transmitting information between various components of the device (e.g., processor 501, memory 502, input / output interface 503, and communication interface 504).

[0074] It should be noted that although the above-described device only shows the processor 501, memory 502, input / output interface 503, communication interface 504, and bus 505, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of the present invention, and does not necessarily include all the components shown in the figures.

[0075] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of the different aspects of this application as described above, which are not provided in detail for the sake of brevity.

[0076] This application is intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the embodiments of this invention. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this invention should be included within the protection scope of this application.

Claims

1. A method for simulating the temperature rise of a multi-plate friction clutch, characterized in that, include: Based on a preset friction pair simulation model, time-varying parameters during the clutch engagement process are obtained, including engagement pressure, relative rotational speed of the driving and driven plates, and friction coefficient. Based on the time-varying parameters, the peak moment when the clutch reaches its maximum sliding friction power during engagement is determined, and the engagement pressure value, relative speed value of the driving and driven plates, and friction coefficient value corresponding to the peak moment are extracted. Based on the assumption of uniform pressure distribution, an equivalent steady-state heat flux density function is constructed that is distributed only along the radial direction of the friction plate. The equivalent steady-state heat flux density function is proportional to the product of the engagement pressure value, the relative rotational speed of the driving and driven plates, the friction coefficient value, and the radius of the friction plate at the peak time. The equivalent steady-state heat flux density function is used as the heat source boundary condition and applied to each friction surface of the friction pair simulation model. The conjugate heat transfer is calculated using the steady-state flow field simulation method to obtain the temperature field distribution of the clutch.

2. The temperature rise simulation method for a multi-plate friction clutch according to claim 1, characterized in that, Determining the peak moment when the clutch reaches its maximum slip power during engagement includes: Establish the function of the joint pressure changing with time. The function of the relative rotational speed of the master and slave plates as a function of time. and the function of the friction coefficient with sliding speed According to the formula for friction power Calculate the curve of friction power changing with time, and solve for... The time corresponding to the maximum value ,in, Let be the area of ​​the infinitesimal element of the friction pair.

3. The temperature rise simulation method for a multi-plate friction clutch according to claim 1, characterized in that, The equivalent steady-state heat flux density function Represented as: , in The heat distribution coefficient, The friction coefficient value at the peak time is [value missing]. The average joint pressure value at the peak time. , The total engagement pressure value at the peak time. Let be the outer radius of the friction plate. Let the inner radius of the friction plate be . The value represents the relative rotational speed of the master and slave plates at the peak moment. The range of values ​​is .

4. The temperature rise simulation method for a multi-plate friction clutch according to claim 1, characterized in that, Before obtaining the time-varying parameters during the clutch engagement process, the method further includes: Based on the actual structural parameters of the multi-plate friction clutch, the friction pair is separated, and a three-dimensional geometric model of the friction pair is established. The fluid domain is extracted and the boundaries are named from the three-dimensional geometric model to obtain the initial friction pair simulation model; The initial friction pair simulation model is meshed to generate a friction pair mesh file for the solver; By setting the physical property parameters of the friction pair mesh file, a friction pair simulation model for simulation analysis is obtained.

5. The temperature rise simulation method for a multi-plate friction clutch according to claim 4, characterized in that, When meshing the friction pair simulation model: An unstructured mesh is used, with a minimum mesh size of 7.986 × 10⁻⁶. -5 m, maximum grid size not exceeding 0.002m, grid growth rate of 1.2; The size function uses curvature combined with neighboring size functions; Mesh quality metrics include skewness and orthogonality, and both mesh quality is greater than 0.

2.

6. The temperature rise simulation method for a multi-plate friction clutch according to any one of claims 1-5, characterized in that, The friction pair simulation model adopts a periodic symmetric model, with the 1 / 4 structure of the clutch as the computational domain.

7. The temperature rise simulation method for a multi-plate friction clutch according to any one of claims 1-5, characterized in that, The equivalent steady-state heat flux density function is loaded onto each friction surface of the friction pair simulation model through a user-defined function; The method of using steady-state flow field simulation for conjugate heat transfer calculation includes using a steady-state multi-reference system model for conjugate heat transfer calculation, wherein the steel sheet connected to the input shaft is set as a rotating reference system, and the components and fluid domain connected to the output shaft are set as a stationary reference system. In the conjugate heat transfer calculation, the SST k-ω turbulence model is used to solve the turbulence characteristics in the fluid domain. The conjugate heat transfer calculation adopts a loose coupling method to realize the bidirectional transfer of temperature and heat flux density between the fluid domain and the solid domain. The boundary conditions of the conjugate heat transfer calculation include: setting the position of the shaft hole of the clutch as the velocity inlet, and setting the axial outlet and the circumferential top oil slinger outlet as pressure outlets.

8. A temperature rise simulation system for a multi-plate friction clutch, characterized in that, include: The parameter acquisition module is used to acquire time-varying parameters during the clutch engagement process based on a preset friction pair simulation model. The time-varying parameters include engagement pressure, relative rotational speed of the driving and driven plates, and friction coefficient. The peak value determination module is used to determine the peak moment when the slip friction power of the clutch reaches its maximum during engagement based on the time-varying parameters, and to extract the engagement pressure value, the relative speed value of the driving and driven plates, and the friction coefficient value corresponding to the peak moment. The heat source construction module is used to construct an equivalent steady-state heat flux density function that is distributed only along the radial direction of the friction plate based on the assumption of uniform pressure distribution. The equivalent steady-state heat flux density function is proportional to the product of the engagement pressure value, the relative rotational speed of the master and slave plates, the friction coefficient value, and the radius of the friction plate at the peak time. The simulation calculation module is used to apply the equivalent steady-state heat flux density function as a heat source boundary condition to each friction surface of the friction pair simulation model, and to perform conjugate heat transfer calculation using a steady-state flow field simulation method to obtain the temperature field distribution of the clutch.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1-7.

10. A computer storage medium, characterized in that, The storage medium stores at least one executable instruction that causes the processor to perform the method as described in any one of claims 1-7.

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