High-speed heavy-duty gear transmission system heat-flow bidirectional coupling calculation method considering complex heat boundary

Abstract

The invention discloses a high-speed heavy-duty gear transmission system heat-flow bidirectional coupling calculation method considering a complex thermal boundary, and belongs to the field of high-speed heavy-duty gear transmission multi-field coupling simulation. The method comprises the following steps: firstly, constructing a high-fidelity grid containing a fluid / solid domain by a CAD (Computer Aided Design) model; the analysis of an initial field and a dynamic grid rotating flow field is completed in Fluent, and a stable transient flow field is stored; gear meshing, bearing friction and oil gas viscosity heat generation energy source items are loaded through secondary development of the UDF; and fluid-solid bidirectional coupling is realized by using a connode coupling wall surface, an energy equation is solved to a residual error 1e-8, and an accurate temperature field is obtained. The method is suitable for various lubrication working conditions such as oil injection, oil mist and splashing, and the gear temperature prediction precision under the complex thermal boundary can be remarkably improved.

Description

Technical Field

[0001] This invention belongs to the field of multi-field coupling simulation of high-speed heavy-load gear transmission, and in particular relates to a thermal-fluid bidirectional coupling calculation method for high-speed heavy-load gear transmission systems that considers complex thermal boundaries. Background Technology

[0002] High-speed, heavy-duty gear transmission systems, as core components of power transmission in high-end equipment, are widely used in aerospace, shipbuilding, and rail transportation. The temperature conditions during operation significantly impact the reliability and service performance of these systems. Gear transmission systems often face harsh conditions such as high speeds (speed > 10000 r / min), heavy loads (contact stress reaching MPa levels), and complex lubrication conditions (oil depletion, oil shortage), resulting in significant two-phase flow characteristics within the gearbox. The combined effects of heat generation, transfer, and dissipation channels among components, along with strong coupling between these factors, make temperature changes difficult to predict, leading to thermal imbalances in the transmission system. High temperatures alter gear backlash and bearing clearance, affecting the stability of power transmission. In extreme cases, this can even cause gear seizure, bearing lock-up, and high-temperature annealing, resulting in reduced equipment reliability and functional degradation in service performance. Therefore, to meet the long-life, high-robust design requirements of gear transmission devices, it is necessary to develop a new temperature analysis method for gear transmission systems to accurately predict gear temperatures and provide a reference for efficient gear lubrication and cooling technologies.

[0003] Most existing gear temperature analysis methods are based on experience, using empirical formulas to consider gear heat generation and transfer, and establishing thermal network models to calculate gear temperature. However, due to the complex combinations of transmission system configurations, operating conditions, and lubrication methods, empirical formulas often fail to accurately describe the gear heat generation and dissipation states, resulting in significant deviations between calculated and actual temperature values, and insufficient prediction accuracy. In transmission system thermal analysis, while numerical simulation-based heat-fluid coupling methods can finely characterize complex thermal boundary conditions during operation, current techniques often employ a sequential coupling strategy due to the significant differences in the time scales of heat transfer between the flow field and the solid field: first, the flow field is calculated independently to obtain the flow and heat dissipation boundary conditions, and then these are mapped to the solid field for temperature analysis. However, this step-by-step calculation method differs fundamentally from the actual heat transfer process. Under real cooling conditions, when a low-temperature fluid exchanges heat with a high-temperature solid surface, it absorbs heat, causing its own temperature to rise. This process not only changes the fluid's thermal properties (such as thermal conductivity and specific heat capacity) but also reduces the temperature gradient in the near-wall region, resulting in a dynamic change in heat transfer efficiency and forming a typical bidirectional strongly coupled heat transfer mechanism. Because existing sequential coupling methods cannot reflect this bidirectional interaction, the temperature results calculated in simulations deviate significantly from actual operating conditions. Therefore, constructing a bidirectional strongly coupled heat flux simulation model that can accurately reproduce the actual physical process has become a key technical approach to improve the accuracy of thermal analysis of transmission systems. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method for calculating the thermal-fluid bidirectional coupling of a high-speed, heavy-load gear transmission system considering complex thermal boundaries, comprising:

[0005] Obtain the geometric model of the gear transmission system from the 3D CAD model;

[0006] A high-fidelity mesh model containing fluid and solid domains is obtained based on the geometric model.

[0007] The transient flow field information under gear rotation is obtained based on the high-fidelity mesh model.

[0008] Based on the transient flow field information and the high-fidelity mesh model, obtain the heat source data of gears, bearings, and oil-gas viscosity heat generation;

[0009] The temperature field distribution of the gear transmission system is obtained based on the heat source data and flow field information.

[0010] Optionally, the high-fidelity mesh model is obtained by importing the CAD model into Fluent Meshing for mesh generation. The mesh generation process includes:

[0011] A shared topology is used to handle common nodes at the interface between the solid and fluid domains;

[0012] A tetrahedral or hexahedral core transition mesh is used for the moving boundary region of the dynamic mesh, and a boundary layer is drawn on the fluid-structure interaction surface.

[0013] Optionally, the high-fidelity mesh model further includes: radially scaling the gear meshing area by 0.98 to 0.99 or stretching it by 0.5 to 2 mm.

[0014] Optionally, the process of obtaining transient flow field information under gear rotation based on a high-fidelity mesh model includes:

[0015] The initial flow field under oil injection, oil mist, or splash lubrication is obtained based on the initial field analysis;

[0016] Based on the initial flow field, the gear rotation motion is defined using the DEFINE_CG_MOTION macro to obtain transient flow field information.

[0017] Optionally, the transient flow field information is obtained through the Fluent solver, and the solution process includes:

[0018] Use the VOF model to obtain the state of the oil-gas two-phase flow;

[0019] Use the RNG k-ε model to obtain the turbulent flow state;

[0020] The Coupled algorithm is used to solve the rotating flow field of the gear.

[0021] Optionally, the heat source data includes heat generated by gear meshing friction, heat generated by bearing friction, and heat generated by oil-gas viscosity, and the acquisition methods include:

[0022] The gear friction heat source is obtained based on the gear meshing contact stress, sliding speed, and friction coefficient.

[0023] The bearing friction heat source is obtained based on the SKF bearing loss model;

[0024] The viscous heat source is obtained based on the shear stress of oil and gas flow.

[0025] Optionally, the temperature field distribution is obtained through the following steps:

[0026] Save transient flow field information after the flow field stabilizes;

[0027] Load the energy source item based on the heat source data;

[0028] Solve the energy equation until the residual converges to 1e -8 To obtain a stable temperature field.

[0029] Optionally, the temperature field distribution achieves high-precision bidirectional coupling heat transfer between the solid and the fluid through Fluent common-node coupling walls.

[0030] On the other hand, the present invention also provides an electronic device including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0031] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0032] Compared with the prior art, the present invention has the following advantages and technical effects:

[0033] This invention, based on the finite volume method and using Fluent software, establishes a high-fidelity bidirectional thermal-fluid coupling model of a gear transmission system encompassing both fluid and solid domains. It applies a heat source using secondary development techniques in the form of energy source terms, enabling the calculation of the flow and temperature fields of a high-speed gear transmission system considering complex thermal boundaries. The finite volume method preserves the original structure and fluid domain morphology of the gear transmission system to the greatest extent possible. Combined with dynamic mesh technology, it calculates the rotational flow field of the gears, thereby obtaining heat dissipation boundaries that conform to the flow state and achieving precise consideration of flow-induced heat dissipation. Fluent's common-node coupled walls enable high-precision bidirectional coupled heat transfer between solids and between solids and fluids. The secondary development technique using energy source terms allows for the calculation of heat source conditions such as frictional heat generation from gears and bearings, and viscous heat generation from wind resistance churning of oil fluids, thus considering complex heat source boundaries. Attached Figure Description

[0034] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0035] Figure 1 This is a diagram illustrating the implementation steps of the thermal-fluid bidirectional coupling method according to an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of a CAD model of a gearbox according to an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the tetrahedral mesh division and hexahedral core mesh division of the gearbox according to an embodiment of the present invention;

[0038] Figure 4 This is a schematic diagram of the load distribution during the bearing loading process according to an embodiment of the present invention;

[0039] Figure 5 A schematic diagram of the operating logic of the gear heat source UDF in this embodiment of the invention is provided.

[0040] Figure 6 A schematic diagram of the operating logic for the bearing heat source UDF and the oil-gas viscosity heat generation UDF in this embodiment of the invention is provided.

[0041] Figure 7 This is a schematic diagram of the simulated temperature distribution inside the gearbox, the convergence residual of the energy equation in the example, and the gear temperature monitoring in an embodiment of the present invention. Detailed Implementation

[0042] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0043] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0044] Example 1

[0045] like Figure 1 As shown, this embodiment provides a method for calculating the thermal-fluid bidirectional coupling of a high-speed, heavy-load gear transmission system considering complex thermal boundaries, including:

[0046] Obtain the geometric model of the gear transmission system from the 3D CAD model;

[0047] A high-fidelity mesh model containing fluid and solid domains is obtained based on the geometric model.

[0048] The transient flow field information under gear rotation is obtained based on the high-fidelity mesh model.

[0049] Based on the transient flow field information, obtain the heat source data of gears, bearings, and oil-gas viscous heat generation;

[0050] The temperature field distribution of the gear transmission system is obtained based on the heat source data and flow field information.

[0051] Specifically:

[0052] Step 1: Model and simplify the gear transmission system using 3D CAD software.

[0053] Step 2: Import the CAD model into Fluent Meshing to generate a mesh.

[0054] Step 3: Import the mesh into the Fluent solver to perform initial flow field analysis and write a dynamic mesh UDF to perform transient analysis of the gear rotation flow field.

[0055] Step 4: Write the heat source UDF for gear and bearing friction heat generation and oil-gas viscosity heat generation.

[0056] Step 5: Save the transient flow field information, load the heat source UDF, and solve the energy equation to calculate the temperature of the transmission system.

[0057] The 3D CAD software mentioned in step 1 includes mainstream 3D design software such as UG, SOLIDWORKS, and Pro / E. Appropriate simplification of the model includes features such as rounding, chamfering, and bolt holes, which have little impact on the flow field but significantly increase the cost of mesh generation. Furthermore, due to the small meshing clearance of the gears, to ensure smooth mesh generation, the gears are often scaled radially by 0.99–0.98, or stretched out by 0.5–2 mm. This ensures mesh generation quality while preserving as much of the original flow field characteristics as possible.

[0058] Figure 2 A 3D CAD model of a high-speed, heavy-duty gearbox was created using UG, including gears, bearings, housing, end caps (solid and fluid domains). Features such as rounded corners, chamfers, and bolt holes were simplified, while lubrication oil supply channels were preserved. Gears were scaled radially by 0.98 to avoid meshing failure at the meshing points.

[0059] The mesh generated according to step 2 includes a solid domain mesh and a fluid domain mesh. At the interfaces between solids and fluids, and between solids themselves, a shared topology is used to achieve shared-node mesh generation, reducing numerical interpolation errors. Due to the use of dynamic meshing technology, the mesh type can be either tetrahedral or hexahedral core mesh. When using a hexahedral core mesh, it is necessary to ensure that the moving boundary is completely covered by the tetrahedron. When using a hexahedral core mesh, its mesh size can be reduced by approximately 20% to 40% compared to a tetrahedral mesh. Boundary layers need to be plotted at the fluid-structure interaction surfaces to ensure high-precision capture of the near-wall flow and temperature fields. The initial boundary layer thickness and number of layers are determined by the near-wall Y+ value and the turbulence model.

[0060] Figure 3 The example of mesh generation for the research object contains a fluid domain and a solid mesh, where the fluid-solid interface is meshed with shared nodes in the form of a shared topology. Figure 3 The left side shows a tetrahedral mesh model. Figure 3 The right side shows a hexahedral core mesh model, whose peeling layer (the mesh transitioning from tetrahedron to hexahedron) must completely cover the motion range of the boundary. Boundary layers are defined at all mesh boundaries to capture near-wall flow characteristics.

[0061] The initial field analysis described in step 3 refers to simulating the process of oil injection or splashing into the transmission system when the gear transmission system is not rotating. This is commonly seen in oil spray lubrication, oil mist lubrication, splash lubrication, and mixed lubrication methods. Performing the initial field analysis before the gear rotation flow field analysis is beneficial for model convergence and reduces computational costs. After the initial field analysis is completed, the moving mesh boundary is defined according to the gear rotation motion condition, and the moving mesh deformation criterion is defined using the spring smoothing method and the local mesh reconstruction method. The VOF model is used to simulate the oil-gas two-phase flow encountered by the transmission system. The RNG k-ε model is used to simulate the fluid turbulence effect during the rotation process. The Coupled algorithm is used as the solution algorithm, employing a first-order upwind approach to solve for momentum, turbulent dissipation, and turbulent kinetic energy.

[0062] The gear friction heat generation described in step 4 is calculated using a gear friction heat generation calculation model based on the meshing principle, as shown in equation (1). This model is mainly related to the contact stress, relative sliding speed, and friction coefficient during gear meshing. The contact stress is calculated based on Hertzian contact theory, as shown in equation (2). The friction coefficient is evaluated using equation (3).

[0063] q g =P N v t f(1)

[0064]

[0065] In the formula: q g The frictional heat flux density at a point on the meshing tooth surface of the gear is expressed in W / mm². 2 ;P N The average contact pressure at a point on the meshing tooth surface, in MPa; v t Let be the relative sliding velocity of the driving and driven gears at a point on the meshing tooth surface, in m / s; f be the coefficient of friction at a point on the meshing tooth surface; F n ρ1 and ρ2 are the normal contact force on the tooth surface, N; ρ1 and ρ2 are the radii of curvature at the contact point on the tooth surface of the driven gear, m; μ1 and μ2 are the Poisson's ratio of the driven gear material, μ1 and μ2 are the primaries; E1 and E2 are the elastic modulus of the driven gear material, MPa; L is the total contact line length on the tooth surface, m; b is the gear contact tooth width, m; μ0 is the dynamic viscosity of the lubricating oil, mPa·s; v t V is the relative sliding velocity, in m / s; T The value is the rolling speed, in m / s.

[0066] According to the bearing friction heat generation described in step 4, the SKF friction power loss model is used. For a deep groove ball bearing without a seal, its power loss consists of three parts: rolling friction loss, sliding friction loss and churning friction loss, as shown in equations (4)-(7).

[0067] M rr =Φish Φ rs G rr (νn bearing ) 0.6 (4)

[0068] M sl =G sl μ sl (5)

[0069]

[0070] Where: M rr Φ is the rolling friction torque of the bearing, N·mm; ish Φ is the inlet shear thermal shrinkage coefficient; rs For power supplement coefficient; G rr n is the variable representing the rolling friction of the bearing. bearing V represents the inner ring speed of the bearing, in r / min; v represents the kinematic viscosity of the lubricating oil, in mm. 2 / s;M sl G represents the sliding friction torque of the bearing, in N·mm. sl Sliding friction variable; μ sl sliding friction factor; V M The churning factor is affected by the oil level and the average diameter of the bearing; K ball For the calculation constants of the ball bearing; M drag The frictional torque of the shaft churning oil is expressed in N·mm; d m n is the average diameter of the ball bearing, in mm; n is the bearing speed, in r / min; f t R is the variable representing the oil level height. s For variables related to bearing geometry; P bearing The total power loss of the bearing is W; w bearing The bearing's operating angular velocity is expressed in rad / s.

[0071] Based on the load analysis during bearing operation and Hertzian contact theory of roller raceways, the bearing heat flux density distribution equation is derived. The bearing power loss is distributed according to the contact relationship in a 1:2:1 ratio among the inner raceway, rollers, and outer raceway. The frictional heat source on the inner raceway and rollers is uniformly distributed, while the heat source on the outer raceway needs to be distributed according to the load distribution. The load on the outer raceway during bearing operation is described in [the diagram]. Figure 4 The maximum load of the roller and the load distribution of the outer raceway are obtained by calculation using equations (8)-(9). Further analogy yields the bearing heat flux density distribution, as shown in equation (10).

[0072]

[0073]

[0074] In the formula: Q max For the maximum roller load, N; F r F is the radial force acting on the bearing, expressed in N (Newtons). a Z represents the axial force acting on the bearing, in N; Z represents the number of rolling elements; J represents the number of rolling elements. r (ε) is the radial integral of the load distribution; J a (ε) represents the axial integral of the load distribution; ε is the load distribution range parameter; Q φ Rolling element load at any position, N; q is the angle at the loading point, in rad; b q represents the frictional heat flux density at any position on the outer raceway of the bearing, in W / m². bmax The maximum frictional heat flux density of the outer raceway of the bearing, W / m2; θ is the limit angle under load, in rad; l is the contact length of the roller raceway, in m; r is the contact width of the roller raceway, in m.

[0075] Based on the oil and gas viscosity heat generation described in step 4, the fluid internal energy increase term due to viscous shear force is derived from the flow equation and energy equation as shown in equation (11).

[0076]

[0077] In the formula: τ ij Surface shear force, N / m; μ eff The effective dynamic viscosity is expressed in mPa·s. is the velocity vector of the multiphase flow, in m / s; u, v, w are the velocities in the x, y, and z directions, in m / s; This represents the work done by the viscous shear force per unit volume of a infinitesimal element, expressed in W / m. 3 .

[0078] According to the UDF described in step 4, the heat source is loaded using the DEFINE_SOURCE macro, which defines the energy source item. For the gear heat source UDF, the main writing and running logic is as follows: Figure 5 As shown, UDF first traverses the cells in the computational domain. When the traversed cell is a tooth surface cell, it proceeds to the next step. If the distance between the cell and the center of the circle is within the range of the tooth tip circle radius and the meshing point radius, it proceeds to the next step. If the cell is located on the meshing side, it proceeds to the next step. Based on the positional geometry information of the cell, its corresponding heat flux density is calculated using formula (1-3), and it is converted into a volumetric energy source term and assigned to the cell.

[0079] The writing and operation logic of the bearing heat source UDF and the oil-gas viscosity heat generation UDF described in step 4 is similar, as follows: Figure 6As shown. The bearing heat source UDF first traverses the computational domain elements. When the traversed elements are the inner and outer raceways or the surface elements of the rollers, it proceeds to the next step. If the element is within the load distribution range, the energy source term is calculated and assigned according to equations (4)-(10) based on the element's positional geometry information. The oil-gas viscous heat generation UDF first traverses the computational domain elements, extracts the effective viscosity and velocity gradient information of the computational domain elements, and uses the element information to calculate the oil-gas viscous heat generation energy source term according to equation (11).

[0080] Saving the flow field information as described in step 5 refers to closing the solution to the flow equations, multiphase flow equations, and turbulence equations when the flow field calculation reaches a relatively stable state. At this point, the calculated flow field information will be saved and participate in subsequent iterations of the energy equation. The loading of the heat source UDF refers to loading the gear, bearing, and oil / gas heat generation UDF derived in step 4 within a specified computational domain. By solving the energy equation, the residual of the iterative energy equation is reduced to 1e. -8 The temperature changes in key components were monitored until they stabilized. The energy equation was solved using the Coupled algorithm, employing a first-order upwind steady-state solution until the residuals of the energy equation converged to 1e. -8 .

[0081] Figure 7 The diagram illustrates the internal temperature distribution, energy residual convergence, and gear temperature variation after the calculation stabilizes. The energy residual plot shows that when the residual is below 1e... -8 At that time, the temperature change of the gears is basically stable, and the temperature of the gearbox gears is the highest, which is dissipated through heat conduction and oil-gas convection.

[0082] Example 2

[0083] This embodiment provides a method for calculating the thermal-fluid bidirectional coupling of a high-speed, heavy-load gear transmission system considering complex thermal boundaries, including:

[0084] Step 1: Model and simplify the gear transmission system using 3D CAD software.

[0085] Step 2: Import the CAD model into Fluent Meshing to generate a mesh.

[0086] Step 3: Import the mesh into the Fluent solver to perform initial flow field analysis and write a user-defined function (UDF) to perform transient analysis of the gear rotation flow field.

[0087] Step 4: Write the heat source UDF for gear and bearing friction heat generation and oil-gas viscosity heat generation.

[0088] Step 5: Save the transient flow field information, load the heat source UDF, and solve the energy equation to calculate the temperature of the transmission system.

[0089] Furthermore, 3D CAD software includes mainstream 3D design software such as UG, SOLIDWORKS, and Pro / E. The aforementioned appropriate simplification includes features such as rounding and chamfering, which have little impact on the flow field but significantly increase the cost of mesh generation. In addition, due to the excessively small gear meshing clearance, to ensure smooth mesh generation, the gears are often scaled radially by 0.99–0.98 or stretched out by 0.5–2 mm. This ensures mesh generation quality while preserving the original flow field characteristics as much as possible.

[0090] Furthermore, the mesh generation includes solid domain meshes and fluid domain meshes. A shared topology is used between the computational domains to handle interface node sharing, reducing numerical interpolation errors. Due to the use of dynamic meshing technology, either tetrahedral or hexcore mesh types can be used. When using hexcore meshes, it is necessary to ensure that the moving boundary of the dynamic mesh is completely covered by tetrahedrons. Boundary layers need to be drawn at the fluid-structure interaction surface. The thickness and number of the first boundary layer are determined by the near-wall Y... + Values ​​and turbulence models were determined.

[0091] Furthermore, initial field analysis refers to simulating the process of lubricating oil being sprayed or splashed into the transmission system when the gear transmission system is not rotating. This is commonly seen in oil injection lubrication, oil mist lubrication, splash lubrication, and mixed lubrication methods. Performing initial field analysis before gear rotation flow field analysis is beneficial for model convergence and reduces computational costs. The flow field analysis requires enabling the VOF model to simulate oil-gas two-phase flow and the RNG k-ε model to simulate turbulence. The flow field solution process mainly involves solving the flow equations, multiphase flow equations, and turbulence equations. The dynamic mesh UDF mainly refers to the DEFINE_CG_MOTION macro in Fluent, used to define the mesh motion and the rotational speed of the gear.

[0092] Furthermore, the heat sources of the transmission system mainly include heat generated by gear meshing friction, bearing friction, and viscous heat generated by high-speed rotation of oil and gas. Gear meshing heat generation adopts a frictional heat generation model based on the meshing principle, bearing heat generation adopts the SKF bearing loss calculation model, and oil-gas viscous heat generation is derived by simultaneously applying flow equations and energy equations. For the gear, bearing frictional heat generation, and oil-gas viscous heat generation models, a DEFINE_SOURCE macro needs to be written to implement heat source loading for the defined source terms. The heat dissipation channels for the gear transmission system mainly involve circulating heat dissipation from the inflow and outflow of lubricating oil, conductive heat dissipation between the gear shaft and the housing, and convective heat transfer between the housing and the external environment.

[0093] Furthermore, preserving transient flow field information means stopping the solution of the flow equations, multiphase flow equations, and turbulence equations when the flow field calculation reaches a relatively stable state. At this point, the flow field calculation information will be preserved and participate in subsequent iterations of the energy equation. The loading of the heat source UDF refers to loading an energy source term within a specified computational domain. By solving the energy equation, the residual of the energy equation is iterated to 1e. -8 And monitor temperature changes in key areas until they stabilize.

[0094] On the other hand, this embodiment also provides an electronic device, including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0095] On the other hand, this embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0096] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A two-way thermal-fluid coupling calculation method for a high-speed, heavy-load gear transmission system considering complex thermal boundaries, characterized in that, include: Obtain the geometric model of the gear transmission system from the 3D CAD model; A high-fidelity mesh model containing fluid and solid domains is obtained based on the geometric model. The transient flow field information under gear rotation is obtained based on the high-fidelity mesh model. Based on the transient flow field information and the high-fidelity mesh model, obtain the heat source data of gears, bearings, and oil-gas viscosity heat generation; The temperature field distribution of the gear transmission system is obtained based on the heat source data and flow field information.

2. The method according to claim 1, characterized in that, The high-fidelity mesh model is obtained by importing the CAD model into FluentMeshing and performing mesh generation. The generation process includes: A shared topology is used to handle common nodes at the interface between the solid and fluid domains; A tetrahedral or hexahedral core transition mesh is used for the moving boundary region of the dynamic mesh, and a boundary layer is drawn on the fluid-structure interaction surface.

3. The method according to claim 1, characterized in that, The high-fidelity mesh model also includes: radial scaling of the gear meshing area by 0.98 to 0.99 or stretching it by 0.5 to 2 mm.

4. The method according to claim 1, characterized in that, The process of obtaining transient flow field information under gear rotation based on a high-fidelity mesh model includes: The initial flow field under oil injection, oil mist, or splash lubrication is obtained based on the initial field analysis; Based on the initial flow field, the gear rotation motion is defined using the DEFINE_CG_MOTION macro to obtain transient flow field information.

5. The method according to claim 4, characterized in that, The transient flow field information is obtained through the Fluent solver, and the solution process includes: Use the VOF model to obtain the state of the oil-gas two-phase flow; Use the RNG k-ε model to obtain the turbulent flow state; The Coupled algorithm is used to solve the rotating flow field of the gear.

6. The method according to claim 1, characterized in that, The heat source data includes heat generated by gear meshing friction, heat generated by bearing friction, and heat generated by oil-gas viscosity, and the acquisition methods include: The gear friction heat source is obtained based on the gear meshing contact stress, sliding speed, and friction coefficient. The bearing friction heat source is obtained based on the SKF bearing loss model; The viscous heat source is obtained based on the shear stress of oil and gas flow.

7. The method according to claim 1, characterized in that, The temperature field distribution is obtained through the following steps: Save transient flow field information after the flow field stabilizes; Load the energy source item based on the heat source data; Solve the energy equation until the residual converges to 1e -8 To obtain a stable temperature field.

8. The method according to claim 7, characterized in that, The temperature field distribution achieves high-precision bidirectional coupling heat transfer between solids and fluids through Fluent common-node coupling walls.

9. An electronic device comprising a memory, a processor, and a computing program stored in the memory and executable on the processor, characterized in that, When the processor executes the computing program, it implements the method of any one of claims 1-8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1-8.

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