Fluid optimization method and system for hydraulic torque converter

Abstract

The invention discloses a fluid optimization method for a hydraulic torque converter, which comprises the following steps of: constructing a geometric model of the hydraulic torque converter, generating a hydraulic torque converter model, and further performing grid division on the hydraulic torque converter model; setting a preset fluid model, setting fluid attributes of the preset fluid model, and further setting a preset boundary condition and an initial flow field condition; calculating an internal flow field of the hydraulic torque converter by adopting a preset solving method, analyzing a flow field result and identifying an abnormal region with energy loss exceeding a preset range; carrying out preset structure optimization on the hydraulic torque converter, generating a hydraulic torque converter optimization model, carrying out fluid dynamic simulation, and verifying an optimization result; and circulating the optimization process until the optimization model of the hydraulic torque converter meets a preset optimization requirement. According to the fluid optimization method for the hydraulic torque converter, the distribution of the flow field in the hydraulic torque converter can be deeply researched through analogue simulation, an energy loss source is found out, and a targeted optimization scheme is put forward.

Description

Technical Field

[0001] The present invention relates to the technical field of hydraulic transmission devices, and in particular to a method, system, computer medium and computer for optimizing fluid in a hydraulic torque converter. Background Art

[0002] A hydraulic torque converter is a hydraulic transmission device used to transmit power. It is widely used in passenger cars, construction machinery and commercial vehicles because of its good adaptive performance, vibration reduction performance, low-speed stability and comfort. A hydraulic torque converter usually consists of three parts: a pump wheel (the input end is connected to the engine), a turbine (the output end is connected to the transmission) and a guide wheel (fixed or one-way connection). When working, the pump wheel is driven by the engine to convert mechanical energy into liquid kinetic energy. The liquid circulates inside the torque converter and transmits and adjusts torque and speed through interaction with the turbine and guide wheel.

[0003] At present, although torque converters perform well in many application scenarios, their efficiency is reduced due to the large amount of eddy currents, separated flows and energy dissipation in the liquid flow path. In addition, the fluid energy transfer between the turbine and the pump wheel is not efficient enough, and part of the energy is dissipated in the form of heat energy.

[0004] Therefore, there is an urgent need for an optimization method that can conduct in-depth research on the flow field distribution inside the torque converter through simulation, find out the source of energy loss and propose targeted optimization solutions. Summary of the invention

[0005] Purpose of the invention: In order to overcome the above shortcomings, the purpose of the present invention is to provide a method and system for optimizing fluid in a torque converter.

[0006] In order to solve the above technical problems, the present invention provides a method for optimizing fluid in a torque converter, comprising:

[0007] Step S1: constructing a geometric model of the torque converter according to the torque converter parameters, generating a torque converter model, and then meshing the torque converter model;

[0008] Step S2: according to the torque converter model, setting a preset fluid model and setting fluid properties of the preset fluid model, and then setting preset boundary conditions and initial flow field conditions according to the preset fluid model;

[0009] Step S3: according to the torque converter model, a preset solution method is used to calculate the internal flow field of the torque converter, and then according to the internal flow field of the torque converter, the flow field results are analyzed and abnormal areas where energy loss exceeds a preset range are identified;

[0010] Step S4: optimizing the preset structure of the torque converter according to the flow field results and the abnormal area, generating an optimization model of the torque converter, and then performing fluid dynamics simulation according to the optimization model of the torque converter to verify the optimization result;

[0011] Step S5: Repeat steps S3 to S4 until the torque converter optimization model meets the preset optimization requirements.

[0012] As a preferred embodiment of the present application, in step S1, the method comprises the following steps:

[0013] Step S10: according to the torque converter parameters, geometric models of the pump wheel, turbine wheel and guide wheel of the torque converter are respectively established, and then the geometric models of the pump wheel, turbine wheel and guide wheel are assembled to generate a torque converter model;

[0014] Step S11: Generate a global grid according to the torque converter model and preset grid division parameters and perform local grid refinement in a preset area to generate a boundary layer grid.

[0015] As a preferred embodiment of the present application, in step S2, the method comprises the following steps:

[0016] Step S20: setting an incompressible fluid model in the torque converter model, and then setting matching fluid properties according to the incompressible fluid model, wherein the fluid properties include density, viscosity, specific heat capacity and thermal conductivity;

[0017] Step S21: setting the boundary conditions of the inlet velocity, outlet pressure and wall according to the torque converter model and the incompressible fluid model;

[0018] Step S22: using the full-field initialization method or the partition initialization method to set the initial velocity field, initial pressure field and initial turbulence parameters.

[0019] As a preferred embodiment of the present application, in step S3, the method comprises the following steps:

[0020] Step S30: Calculating the internal flow field of the torque converter using a pressure implicit operator separation method;

[0021] Step S31: setting residual limits of continuity, momentum or energy equations;

[0022] Step S32: Set a preset number of iteration steps and set monitoring points to monitor changes in pressure and speed variables.

[0023] Step S33: perform iterative calculations, monitor the residual, iteration steps and monitoring point variable changes in real time, and then generate flow field results.

[0024] As a preferred embodiment of the present application, in step S3, the method further comprises the following steps:

[0025] Step S34: Calculate the velocity distribution, pressure distribution, turbulent kinetic energy and turbulent dissipation rate distribution in the preset area of ​​the torque converter model according to the flow field results;

[0026] Step S35: Calculate the velocity gradient according to the velocity distribution, and identify the high velocity gradient and eddy current area;

[0027] Step S36: Calculate the pressure loss according to the pressure distribution and identify the high pressure loss area;

[0028] Step S37: Analyze the turbulence intensity and turbulence generation area according to the turbulence kinetic energy and turbulence dissipation rate distribution.

[0029] As a preferred embodiment of the present application, in step S4, the method comprises the following steps:

[0030] Step S40: Optimizing the inlet velocity distribution and outlet pressure conditions of the torque converter model;

[0031] Step S41: Optimizing the blade angle of the torque converter model;

[0032] Step S42: Optimizing the blade shape of the torque converter model;

[0033] Step S43: Optimizing the number of flow channel structures of the torque converter model;

[0034] Step S44: Optimizing the flow channel structure position and size of the torque converter model.

[0035] As a preferred embodiment of the present application, in step S4, the method further comprises the following steps:

[0036] Step S45: according to the optimization result, geometric models of the pump wheel, turbine wheel and guide wheel of the torque converter are respectively established, and then the optimized geometric models of the pump wheel, turbine wheel and guide wheel are assembled to generate an optimized model of the torque converter;

[0037] Step S46: re-gridding according to the torque converter optimization model;

[0038] Step S47: performing fluid dynamics simulation according to the torque converter optimization model, and then extracting velocity distribution, pressure distribution, turbulent kinetic energy and turbulent dissipation rate distribution of a preset area of ​​the torque converter optimization model;

[0039] Step S48: Calculate velocity gradient, pressure loss, turbulence intensity and turbulence generation area based on the extracted data.

[0040] As a preferred embodiment of the present application, in step S5, the method further comprises the following steps:

[0041] Step S50: comparing the velocity fields, pressure fields and turbulence characteristics of the multiple optimization schemes, and then comparing the improvement effects of the multiple optimization schemes according to their efficiencies and pressure losses, to generate the best optimization scheme;

[0042] Step S51: performing a preset number of fluid dynamics simulations on the best optimization solution, monitoring the convergence of each fluid dynamics simulation, and generating simulation results;

[0043] Step S52: fine-tune the torque converter optimization model and boundary conditions according to the simulation results. After a preset number of rounds of fine-tuning, determine the final optimization solution and record the key parameters and adjustment measures of the final optimization solution.

[0044] The present application also provides a torque converter fluid optimization system using the torque converter fluid optimization method, comprising:

[0045] Torque converter;

[0046] The cooling device comprises a cooling unit and a circulation unit, wherein the cooling unit wraps the torque converter and is filled with cooling liquid; two ends of the circulation unit are respectively connected to the cooling unit to provide water cooling circulation for the coolant in the cooling unit;

[0047] The control unit is connected with the torque converter, the cooling unit and the circulation unit to provide fluid optimization and temperature reduction control.

[0048] As a preferred embodiment of the present application, the control unit includes:

[0049] A model building module, used to build a geometric model of the hydraulic torque converter according to the parameters of the hydraulic torque converter, generate a hydraulic torque converter model, and then perform meshing on the hydraulic torque converter model;

[0050] A condition establishment module is used to set a preset fluid model and set the fluid properties of the preset fluid model, and then set preset boundary conditions and initial flow field conditions according to the preset fluid model;

[0051] An abnormality analysis module, used to calculate the internal flow field of the torque converter using a preset solution method, and then analyze the flow field results and identify abnormal areas where energy loss exceeds a preset range based on the internal flow field of the torque converter;

[0052] Model optimization module, used to optimize the preset structure of the torque converter, generate the torque converter optimization model, and then perform fluid dynamics simulation based on the torque converter optimization model to verify the optimization results;

[0053] The loop optimization module is used to repeatedly execute the optimization process until the torque converter optimization model meets the preset optimization requirements.

[0054] The above technical solution of the present invention has the following advantages compared with the prior art:

[0055] 1. By setting the incompressible fluid model and its fluid properties (such as density, viscosity, specific heat capacity and thermal conductivity), and setting reasonable boundary conditions and initial flow field conditions according to the actual working conditions, it is ensured that the simulation process can accurately simulate the actual operating environment of the torque converter, so as to effectively evaluate the performance of the torque converter and provide reliable data support for subsequent optimization.

[0056] 2. By optimizing the key design parameters of the torque converter, such as blade angle, blade shape, number and position of flow channel structures, the energy loss in the flow field can be effectively reduced and the overall efficiency of the torque converter can be improved. Multiple rounds of simulation of the optimized model have verified the optimization effect and ensured the stability and reliability of the design.

[0057] 3. Through multiple rounds of fluid dynamics simulation and optimization comparison, abnormal areas in the flow field can be effectively identified and corrected, thereby improving the working efficiency and performance of the torque converter.

[0058] 4. The cooling device can effectively wrap the torque converter and fill it with coolant. The circulation of the coolant and the water cooling effect help to quickly dissipate heat when the torque converter is running, preventing the temperature from being too high, thereby extending the service life of the torque converter. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0060] Figure 1 Schematic diagram of an explosion of a hydraulic torque converter provided in an embodiment of the present invention.

[0061] Figure 2 It is a flow chart of a method for optimizing fluid in a torque converter provided in an embodiment of the present invention.

[0062] Figure 3 It is a flow chart of the model generation and mesh division method provided by an embodiment of the present invention.

[0063] Figure 4 It is a flow chart of a fluid model setting method provided by an embodiment of the present invention.

[0064] Figure 5 It is a flow chart of a simulation calculation method provided by an embodiment of the present invention.

[0065] Figure 6 It is a flow chart of the flow field path optimization method provided by an embodiment of the present invention.

[0066] Figure 7 It is a flow chart of a simulation result verification method provided by an embodiment of the present invention.

[0067] Figure 8 It is an exploded schematic diagram of a hydraulic torque converter and a cooling device provided in an embodiment of the present invention.

[0068] Fig. 9 It is a connection diagram of a hydraulic torque converter and a cooling device provided in an embodiment of the present invention.

[0069] Fig.10 It is a schematic diagram of module connection of a torque converter fluid optimization system provided in an embodiment of the present invention.

[0070] Description of the Figures in the Specification:

[0071] 10. Torque converter, 100. Pump wheel, 101. Guide wheel, 102. Turbine, 110. Cold shortage unit, 111. Circulation pump, 112. Heat exchanger, 120. Model construction module, 121. Condition establishment module, 122. Abnormal analysis module, 123. Model optimization module, 124. Circulation optimization module. DETAILED DESCRIPTION

[0072] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0073] The torque converter 10 is a hydraulic transmission device that uses liquid (usually transmission oil) to transmit and amplify torque. It is widely used in motor vehicle automatic transmissions. It plays a role in torque transmission and regulation between the engine and the transmission. The working principle of the torque converter 10 is based on fluid dynamics, and energy transfer and gain are achieved through the flow of liquid between the pump wheel 100, the turbine 102 and the guide wheel 101.

[0074] refer to Figure 1As shown, the torque converter 10 is usually composed of at least a pump wheel 100, a turbine 102 and a guide wheel 101. The pump wheel 100 is directly connected to the engine. When the engine rotates, the pump wheel 100 drives the internal liquid to rotate. The rotation of the pump wheel 100 generates centrifugal force in the liquid, and the liquid is thrown to the outer edge of the pump wheel 100; the turbine 102 is connected to the input shaft of the transmission. When the liquid flows from the pump wheel 100 into the turbine 102, it will impact the blades of the turbine 102, driving the turbine 102 to rotate, thereby converting the kinetic energy of the liquid into mechanical energy and outputting it to the transmission; the guide wheel 101 is located between the pump wheel 100 and the turbine 102. Its function is to redirect the liquid to the pump wheel 100, thereby improving the efficiency of the torque converter 10, especially in the case of low speed and high torque, and the guide wheel 101 usually rotates only when the liquid flow direction meets certain conditions, otherwise it remains fixed.

[0075] Therefore, reference Figure 2 As shown, in some embodiments, the method for optimizing the fluid of the torque converter 10 includes the following steps:

[0076] Step S1: constructing a geometric model of the torque converter 10 according to the parameters of the torque converter 10, generating a model of the torque converter 10, and then meshing the model of the torque converter 10.

[0077] Among them, computational fluid dynamics (CFD) simulation is used to optimize the internal liquid flow path of the torque converter 10, thereby reducing energy loss and improving transmission efficiency and performance.

[0078] Specifically, in step S1, refer to Figure 3 As shown, the method further comprises the following steps:

[0079] Step S10: According to the parameters of the torque converter 10, the geometric models of the pump wheel 100, the turbine 102 and the stator 101 of the torque converter 10 are respectively established, and then the geometric models of the pump wheel 100, the turbine 102 and the stator 101 are assembled to generate the torque converter 10 model.

[0080] In the actual implementation process, according to the design specifications and drawings of the torque converter 10, the size and shape parameters of the pump wheel 100, the turbine 102 and the guide wheel 101 are obtained, and then the geometric models of the pump wheel 100, the turbine 102 and the guide wheel 101 of the torque converter 10 are constructed by using 3D modeling software (such as SolidWorks, CATIA, etc.), and the parameters such as unit and precision are set for the geometric model; then, the constructed geometric models of the pump wheel 100, the turbine 102 and the guide wheel 101 are accurately positioned by using assembly constraints (such as alignment, coaxiality, etc.) to ensure the correctness of the assembly, so as to generate the torque converter 10 model; during the assembly process, the interference between the components is checked to ensure that there is no overlap or collision, and the detailed features that do not affect the flow field calculation (such as small chamfers, small holes, etc.) are removed to simplify the model to reduce the amount of calculation.

[0081] Step S11: Generate a global grid according to the torque converter 10 model and preset grid division parameters and perform local grid refinement in a preset area to generate a boundary layer grid.

[0082] In the actual implementation process, after the torque converter 10 model is completed, the mesh type (such as structured mesh, unstructured mesh, hybrid mesh, etc.) is selected according to the calculation requirements, and the global mesh size and the mesh size of the local refined area are set to ensure the mesh accuracy of key areas (such as blade surface, gap area, etc.). At the same time, a boundary layer mesh is generated on the solid surface (such as blades, shells, etc.) to capture the flow characteristics near the wall. In this way, the meshing software (such as ANSYS Meshing, ICEM CFD, etc.) is used to generate a global mesh for the torque converter 10 model, and local mesh refinement is performed in key areas (such as blades, narrow flow channel areas) to ensure the mesh quality and quantity in these areas; after the mesh is generated, the quality indicators of the mesh (such as unit distortion, aspect ratio, etc.) are checked to ensure that the mesh quality meets the calculation requirements. At the same time, the operator manually optimizes and adjusts the areas where the quality does not meet the requirements, and re-divides the mesh when necessary.

[0083] Among them, mesh quality indicators usually include:

[0084] Unit shape: Make sure the unit shape is close to a square or regular hexahedron to reduce distortion;

[0085] Aspect ratio: Control the aspect ratio of the unit to ensure it is within a reasonable range (usually no more than 10:1);

[0086] Boundary layer: Generate a multi-layer boundary layer grid. The number of layers and thickness are set according to the flow characteristics. Generally, there are 10 to 20 layers, and the thickness increases layer by layer.

[0087] Step S2: according to the torque converter 10 model, a preset fluid model is set and the fluid properties of the preset fluid model are set, and then according to the preset fluid model, preset boundary conditions and initial flow field conditions are set.

[0088] Among them, in CFD simulation, selecting a suitable fluid model and defining the physical properties of the fluid are key steps to ensure calculation accuracy and reliability of results; the selection of the fluid model is based on the characteristics of the fluid flow inside the torque converter 10, and common fluid models include incompressible fluid, compressible fluid, viscous fluid, etc.

[0089] Specifically, in step S2, refer to Figure 4 As shown, the method further comprises the following steps:

[0090] Step S20: setting an incompressible fluid model in the torque converter 10 model, and then setting matching fluid properties according to the incompressible fluid model, wherein the fluid properties include density, viscosity, specific heat capacity and thermal conductivity.

[0091] In the actual implementation process, the incompressible fluid model is suitable for the torque converter 10 working at normal temperature and pressure, and the fluid density changes little. Usually, the incompressible fluid model is selected in the CFD simulation software (such as ANSYS Fluent, CFX, OpenFOAM, etc.), and the density is set to a constant; according to the selected incompressible fluid model, the physical properties of the corresponding fluid are defined, including:

[0092] Density: The mass density of the fluid. Enter the density value of the fluid in the simulation software. For incompressible fluids, the density is a constant.

[0093] Viscosity: The viscosity coefficient of the fluid. Enter the dynamic viscosity value of the fluid in the simulation software;

[0094] Specific heat capacity: the amount of heat required to raise the unit temperature of a unit mass of fluid. Enter the specific heat capacity value of the fluid in the simulation software;

[0095] Thermal conductivity: The thermal conductivity of the fluid. Enter the thermal conductivity value of the fluid in the simulation software. For temperature-dependent fluids, the thermal conductivity may change with temperature, and the corresponding temperature relationship needs to be defined.

[0096] Step S21: According to the torque converter 10 model and the incompressible fluid model, the boundary conditions of the inlet velocity, outlet pressure and wall are set.

[0097] In actual implementation, the inlet velocity boundary condition: defines the magnitude and direction of the inlet velocity, which is usually a constant or a known velocity distribution. In the CFD software, select the inlet boundary and set the velocity value and direction;

[0098] Outlet pressure boundary condition: define the outlet pressure value, usually atmospheric pressure or known pressure distribution. In the CFD software, select the outlet boundary and set the pressure value;

[0099] Wall boundary conditions: Select the slip wall condition. In the CFD software, select the wall boundary and set the slip condition.

[0100] Step S22: using the full-field initialization method or the partition initialization method to set the initial velocity field, initial pressure field and initial turbulence parameters.

[0101] In the actual implementation process, the initial conditions define the state of the flow field at the beginning of the simulation. Good initial conditions help to accelerate the convergence of the calculation and improve the stability of the calculation. Initial velocity field: defines the initial velocity distribution, which can be a constant velocity field or a velocity distribution based on prior knowledge;

[0102] Initial pressure field: defines the initial pressure distribution, which can be a constant pressure field or a pressure distribution based on prior knowledge;

[0103] Initial turbulence parameters: define the initial turbulent kinetic energy and turbulent dissipation rate to ensure the stability of the turbulence model.

[0104] Step S3: According to the torque converter 10 model, a preset solution method is used to calculate the internal flow field of the torque converter 10, and then according to the internal flow field of the torque converter 10, the flow field results are analyzed and abnormal areas where energy loss exceeds a preset range are identified.

[0105] The internal flow field of the torque converter 10 is calculated by CFD simulation software (such as ANSYS Fluent, CFX, OpenFOAM, etc.), and appropriate simulation software and solution algorithm are selected to ensure the accuracy and efficiency of the calculation, providing a reliable basis for the optimized design.

[0106] Specifically, in step S3, refer to Figure 5 As shown, the method further comprises the following steps:

[0107] Step S30: Calculate the internal flow field of the torque converter 10 using the pressure implicit operator separation solution method.

[0108] Among them, the Pressure Implicit with Splitting of Operators (PISO algorithm) is a pressure-velocity coupling algorithm for solving incompressible flows. It is based on the pressure correction method and solves the velocity and pressure distribution in the flow field step by step. The PISO algorithm is an improved version of the SIMPLER algorithm (SIMPLE-Revised) and is suitable for transient flow calculations. In the PISO algorithm, the pressure correction formula is as follows:

[0109] p n+1 =p * +β p (p′-p * )

[0110] Among them, p n+1 is the pressure field at the next time step, that is, the updated pressure field; p * is the predicted pressure field, usually the pressure value calculated at the initial condition or in the previous step; β p is the pressure relaxation factor, which usually takes a value between 0 and 1 and is used to control the amplitude of pressure correction and help convergence; p′ is the pressure correction term, which is obtained by solving the pressure correction equation.

[0111] The steps of the PISO algorithm are:

[0112] Calculation of initial velocity field and pressure field: Based on the velocity field and pressure field of the previous time step, the explicit time advancement method is used to calculate the preliminary estimated velocity field and pressure field;

[0113] Pressure correction: Use the predicted velocity field to calculate the preliminary pressure field p * , solve the pressure correction term p′ according to the continuity equation (mass conservation) of the velocity field, and use the pressure correction formula of the PISO algorithm to perform pressure correction to obtain a more accurate pressure field p n+1 ;

[0114] Velocity correction: Using the updated pressure field p n+1 , correct the initially estimated velocity field to obtain a more accurate velocity field;

[0115] Repeated pressure correction and velocity correction: Multiple pressure correction and velocity correction are performed within one time step to ensure that the coupling of the pressure field and the velocity field can more accurately meet the incompressible condition.

[0116] Step S31: Setting the residual limit of the continuity, momentum or energy equation.

[0117] The residual limit is usually 10 -6 to 10 -3 ; The calculation formula of the continuity equation is:

[0118]

[0119] in, is the partial derivative of density with respect to time, which indicates the rate of change of fluid density with time; is the divergence of density and velocity field, which means the divergence of the product of density and velocity, reflecting the change of mass flux; u is the velocity of the fluid.

[0120] The momentum equation is calculated as:

[0121]

[0122] Where ρ is the fluid density, is the partial derivative of the velocity vector with respect to time, which indicates the rate of change of fluid velocity with time; is the convection term of the velocity field, which represents the self-convection effect of the velocity field and is the change term of the fluid momentum in space; is the pressure gradient term, which represents the force generated by the pressure difference inside the fluid. is the gradient of pressure p; μ is the dynamic viscosity coefficient, which represents the internal friction between fluid molecules; F is the external force acting on the fluid; is the Laplace operator of the velocity vector, which represents the diffusion effect of the velocity field and reflects the influence of viscous diffusion on the velocity field.

[0123] The energy equation is calculated as:

[0124]

[0125] Among them, c p The specific heat capacity at constant pressure is the heat required to raise the temperature of a unit mass of fluid by one Kelvin under constant pressure. is the partial derivative of temperature with respect to time, indicating the rate of change of temperature with time; is the convection term of the temperature field, which represents the influence of fluid motion on the temperature distribution; is the divergence of thermal conductivity, is the temperature gradient, k is the thermal conductivity; Q is the heat source term, which represents the heat generated or consumed in a unit volume of fluid, which can be an internal heat source or external input heat.

[0126] Step S32: Set a preset number of iteration steps and set monitoring points to monitor changes in pressure and speed variables.

[0127] Among them, the preset number of iteration steps is set by the operator according to actual needs; monitoring points are set at key positions of the flow field (such as near the blades and narrow places of the flow channel), and the changes in variables (such as speed, pressure, temperature, etc.) at these positions are recorded to observe their convergence.

[0128] Step S33: perform iterative calculations, monitor the residual, iteration steps and monitoring point variable changes in real time, and then generate flow field results.

[0129] Among them, when performing iterative calculations, for each equation (continuity equation, momentum equation or energy equation), calculate the residual of the current iteration step; after each iteration step, record and monitor the change of the residual; if the residuals of all equations are lower than the set limit, or the residual changes less than the set value in several consecutive iterations (i.e., tends to be stable), the calculation is considered to be converged, and then the converged flow field results are generated; if the residual does not reach the limit or the residual changes are greater than the set value, continue to iterate. The iterative process is: solve equations → update pressure field → correct velocity field → solve equations (if any) → calculate residuals.

[0130] Step S34: Calculate the velocity distribution, pressure distribution, turbulent kinetic energy and turbulent dissipation rate distribution in the preset area of ​​the torque converter 10 model according to the flow field results.

[0131] Among them, according to the flow field results, the velocity distribution at the key position is extracted, the pressure distribution inside the torque converter 10 is extracted, and the turbulent kinetic energy and turbulent dissipation rate distribution inside the torque converter 10 are extracted.

[0132] Step S35: Calculate the velocity gradient according to the velocity distribution, and identify high velocity gradient and eddy current areas.

[0133] Step S36: Calculate the pressure loss based on the pressure distribution and identify the high pressure loss area.

[0134] Step S37: Analyze the turbulence intensity and turbulence generation area according to the turbulence kinetic energy and turbulence dissipation rate distribution.

[0135] Step S4: According to the flow field results and the abnormal area, the preset structure of the torque converter 10 is optimized to generate an optimized model of the torque converter 10, and then a fluid dynamics simulation is performed based on the optimized model of the torque converter 10 to verify the optimization result.

[0136] Among them, by analyzing the simulation results, the deficiencies in the torque converter 10 model are identified, and then optimization measures are proposed to improve the performance and efficiency of the torque converter 10.

[0137] Specifically, in step S4, reference Figure 6 As shown, the method further comprises the following steps:

[0138] Step S40: Optimizing the inlet velocity distribution and outlet pressure conditions of the torque converter 10 model.

[0139] Among them, the boundary conditions of the inlet velocity distribution and the outlet pressure conditions are adjusted to simulate a flow environment closer to the actual working conditions.

[0140] Step S41: Optimizing the blade angle of the torque converter 10 model.

[0141] Among them, the inlet and outlet angles of the blades are modified exemplarily, and the inlet and outlet angles of the blades are adjusted to reduce flow separation and vortex areas to improve efficiency.

[0142] Step S42: Optimizing the blade shape of the torque converter 10 model.

[0143] Among them, the curvature and thickness distribution of the blades are exemplarily adjusted to optimize the flow path and reduce energy loss by adjusting the curvature and thickness distribution of the blades.

[0144] Step S43: Optimizing the number of flow channel structures of the torque converter 10 model.

[0145] Step S44: Optimizing the flow channel structure position and size of the torque converter 10 model.

[0146] Among them, guide plates or guide vanes are added in narrow flow passages or areas with large pressure losses, and eddy currents and flow separation are reduced by adding or removing guide structures at key positions.

[0147] During the optimization, multiple optimization schemes are generated, such as different blade angles, shapes and flow guide structures.

[0148] Specifically, after step S44, refer to Figure 6 As shown, the method further comprises the following steps:

[0149] Step S45: According to the optimization results, the geometric models of the pump wheel 100, the turbine 102 and the stator 101 of the torque converter 10 are respectively established, and then the optimized geometric models of the pump wheel 100, the turbine 102 and the stator 101 are assembled to generate the optimized model of the torque converter 10.

[0150] Step S46: Re-gridding according to the optimized model of the torque converter 10.

[0151] Step S47: Perform fluid dynamics simulation according to the optimized model of the torque converter 10, and then extract the velocity distribution, pressure distribution, turbulent kinetic energy and turbulent dissipation rate distribution of the preset area of ​​the optimized model of the torque converter 10.

[0152] Step S48: Calculate velocity gradient, pressure loss, turbulence intensity and turbulence generation area based on the extracted data.

[0153] Among them, after the optimization scheme is generated, CFD simulation is performed on each optimization scheme to calculate the efficiency and pressure loss of each optimization scheme; according to the efficiency and pressure loss of each optimization scheme, the simulation results before and after optimization are compared to evaluate the effect of each optimization scheme; then the optimization scheme with the best effect is selected, that is, the optimization scheme with the greatest efficiency improvement and the smallest pressure loss is selected; then the best optimization scheme is subjected to multiple rounds of simulation verification to ensure its stable effect, and according to the simulation results, the optimization scheme is further fine-tuned to achieve the best effect.

[0154] Step S5: Repeat steps S3 to S4 until the optimization model of the torque converter 10 meets the preset optimization requirements.

[0155] Among them, CFD simulation is performed for each optimization scheme to evaluate its effect, and the best optimization scheme is selected through multiple rounds of simulation verification and adjustment.

[0156] Specifically, in step S4, reference Figure 7 As shown, the method further comprises the following steps:

[0157] Step S50: comparing the velocity fields, pressure fields and turbulence characteristics of the multiple optimization schemes, and then comparing the improvement effects of the multiple optimization schemes according to their efficiencies and pressure losses, to generate the best optimization scheme.

[0158] Among them, the velocity fields under different optimization schemes are compared, and the velocity distribution in key areas such as the pump wheel 100, the turbine 102 and the guide wheel 101 is paid attention to; the pressure distribution at different positions in the optimization scheme is analyzed, and the pressure gradient and pressure loss are paid attention to; the turbulence intensity of each scheme is compared through a turbulence model (such as k-∈ or k-ω model) to evaluate the impact of turbulence on efficiency and performance; the efficiency is calculated: Wherein, η is the efficiency of the torque converter 10, T out and T in is the output and input torque, ω out and ω in is the angular velocity of output and input; calculate the pressure loss: Δs = s in -s out , where Δs is the pressure loss, s in and out are the inlet and outlet pressures; based on this, the solution with the highest efficiency and the smallest pressure loss is selected as the best optimization solution according to the calculation results.

[0159] Step S51: performing a preset number of fluid dynamics simulations on the best optimization solution, while monitoring the convergence of each fluid dynamics simulation to generate simulation results.

[0160] The geometric model and boundary conditions of the best optimization solution are used to perform a preset number of CFD simulations (e.g., 20 rounds); a convergence criterion is set (e.g., the residual limit is 10 -5 ) to ensure the stability and accuracy of the calculation; monitor the residual of each iteration to ensure that the convergence standard is reached within the preset number of iterations, record the results of each simulation, such as velocity field, pressure field, turbulence characteristics, etc., and evaluate its convergence to generate simulation results.

[0161] Step S52: fine-tune the optimization model and boundary conditions of the torque converter 10 according to the simulation results. After a preset number of rounds of fine-tuning, determine the final optimization solution and record the key parameters and adjustment measures of the final optimization solution.

[0162] Among them, according to the simulation results, the local structure of the geometric model (such as the blade angle of the impeller 100, the number of blades of the turbine 102, etc.) and the boundary conditions (such as inlet velocity, outlet pressure, etc.) are adjusted to improve the fluid flow and heat transfer efficiency; CFD simulation is performed on the model after each fine-tuning to verify the adjustment effect. When the adjusted scheme shows a stable performance improvement in multiple rounds of simulation, it is determined to be the final optimization scheme, and then the key parameters of the final optimization scheme (such as blade shape, speed, pressure, etc.) are recorded, and the adjustment measures and their impact on the flow field characteristics are recorded to provide a reference for subsequent improvements.

[0163] Among them, the preset number of times and preset rounds are set by the operating personnel according to actual needs.

[0164] refer to Figure 8 and Fig. 9 As shown, in some embodiments, the present application also relates to a fluid optimization system for a torque converter 10 using the fluid optimization method for the torque converter 10, comprising:

[0165] The above-mentioned torque converter 10;

[0166] The cooling device comprises a cooling unit 110 and a circulation unit, wherein the cooling unit 110 wraps the torque converter 10 and is filled with cooling liquid; two ends of the circulation unit are respectively connected to the cooling unit 110 to provide water cooling circulation for the coolant in the cooling unit 110;

[0167] The control unit is connected with the torque converter 10, the cold shortage unit 110 and the circulation unit, and is used to provide fluid optimization and temperature reduction control.

[0168] Specifically, the cold-shortage unit 110 can adopt a wrapped shell design to wrap the torque converter 10, and fill the cold-shortage unit 110 with coolant or cold-shortage oil; the circulation unit can adopt a combination of a circulating pump 111 and a heat exchanger 112 for heat dissipation; wherein the heat exchanger 112 can adopt one or more plate heat exchangers and / or shell and tube heat exchangers.

[0169] In some embodiments, reference Fig.10 As shown, the control unit includes:

[0170] A model building module 120, for building a geometric model of the torque converter 10 according to the parameters of the torque converter 10, generating a model of the torque converter 10, and then meshing the model of the torque converter 10;

[0171] The condition establishment module 121 is used to set a preset fluid model and set the fluid properties of the preset fluid model, and then set the preset boundary conditions and initial flow field conditions according to the preset fluid model;

[0172] The abnormality analysis module 122 is used to calculate the internal flow field of the torque converter 10 using a preset solution method, and then analyze the flow field results and identify abnormal areas where the energy loss exceeds a preset range based on the internal flow field of the torque converter 10;

[0173] The model optimization module 123 is used to optimize the preset structure of the torque converter 10, generate an optimized model of the torque converter 10, and then perform fluid dynamics simulation according to the optimized model of the torque converter 10 to verify the optimization result;

[0174] The loop optimization module 124 is used to repeatedly execute the optimization process until the optimization model of the torque converter 10 meets the preset optimization requirements.

[0175] In some embodiments, the present application also relates to a computer medium having a computer program stored thereon, and the computer program is executed by a processor to implement the method for optimizing the fluid of a torque converter 10 .

[0176] In some embodiments, the present application also relates to a computer, comprising the computer medium described above.

[0177] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0178] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for optimizing fluid in a torque converter, characterized in that: The following steps are involved: Step S1: constructing a geometric model of the torque converter according to the torque converter parameters, generating a torque converter model, and then meshing the torque converter model; Step S2: according to the torque converter model, setting a preset fluid model and setting fluid properties of the preset fluid model, and then setting preset boundary conditions and initial flow field conditions according to the preset fluid model; Step S3: according to the torque converter model, a preset solution method is used to calculate the internal flow field of the torque converter, and then according to the internal flow field of the torque converter, the flow field results are analyzed and abnormal areas where energy loss exceeds a preset range are identified; Step S4: optimizing the preset structure of the torque converter according to the flow field results and the abnormal area, generating an optimization model of the torque converter, and then performing fluid dynamics simulation according to the optimization model of the torque converter to verify the optimization result; Step S5: Repeat steps S3 to S4 until the torque converter optimization model meets the preset optimization requirements.

2. The method for optimizing fluid in a torque converter according to claim 1, characterized in that: In step S1, the method comprises the following steps: Step S10: according to the torque converter parameters, geometric models of the pump wheel, turbine wheel and guide wheel of the torque converter are respectively established, and then the geometric models of the pump wheel, turbine wheel and guide wheel are assembled to generate a torque converter model; Step S11: Generate a global grid according to the torque converter model and preset grid division parameters and perform local grid refinement in a preset area to generate a boundary layer grid.

3. The method for optimizing fluid in a torque converter according to claim 2, characterized in that: In step S2, the method comprises the following steps: Step S20: setting an incompressible fluid model in the torque converter model, and then setting matching fluid properties according to the incompressible fluid model, wherein the fluid properties include density, viscosity, specific heat capacity and thermal conductivity; Step S21: setting the boundary conditions of the inlet velocity, outlet pressure and wall according to the torque converter model and the incompressible fluid model; Step S22: using the full-field initialization method or the partition initialization method to set the initial velocity field, initial pressure field and initial turbulence parameters.

4. The method for optimizing fluid in a torque converter according to claim 3, characterized in that: In step S3, the method comprises the following steps: Step S30: Calculating the internal flow field of the torque converter using a pressure implicit operator separation method; Step S31: setting residual limits of continuity, momentum or energy equations; Step S32: Set a preset number of iteration steps and set monitoring points to monitor changes in pressure and speed variables. Step S33: perform iterative calculations, monitor the residual, iteration steps and monitoring point variable changes in real time, and then generate flow field results.

5. The method for optimizing fluid in a torque converter according to claim 4, characterized in that: In step S3, the method further comprises the following steps: Step S34: Calculate the velocity distribution, pressure distribution, turbulent kinetic energy and turbulent dissipation rate distribution in the preset area of ​​the torque converter model according to the flow field results; Step S35: Calculate the velocity gradient according to the velocity distribution, and identify the high velocity gradient and eddy current area; Step S36: Calculate the pressure loss according to the pressure distribution and identify the high pressure loss area; Step S37: Analyze the turbulence intensity and turbulence generation area according to the turbulence kinetic energy and turbulence dissipation rate distribution.

6. The method for optimizing fluid in a torque converter according to claim 5, characterized in that: In step S4, the method comprises the following steps: Step S40: Optimizing the inlet velocity distribution and outlet pressure conditions of the torque converter model; Step S41: Optimizing the blade angle of the torque converter model; Step S42: Optimizing the blade shape of the torque converter model; Step S43: Optimizing the number of flow channel structures of the torque converter model; Step S44: Optimizing the flow channel structure position and size of the torque converter model.

7. The method for optimizing fluid in a torque converter according to claim 6, characterized in that: In step S4, the method further comprises the following steps: Step S45: according to the optimization result, geometric models of the pump wheel, turbine wheel and guide wheel of the torque converter are respectively established, and then the optimized geometric models of the pump wheel, turbine wheel and guide wheel are assembled to generate the optimized model of the torque converter; Step S46: re-gridding according to the torque converter optimization model; Step S47: performing fluid dynamics simulation according to the torque converter optimization model, and then extracting velocity distribution, pressure distribution, turbulent kinetic energy and turbulent dissipation rate distribution of a preset area of ​​the torque converter optimization model; Step S48: Calculate velocity gradient, pressure loss, turbulence intensity and turbulence generation area based on the extracted data.

8. The method for optimizing fluid in a torque converter according to claim 7, characterized in that: In step S5, the method further comprises the following steps: Step S50: comparing the velocity fields, pressure fields and turbulence characteristics of the multiple optimization schemes, and then comparing the improvement effects of the multiple optimization schemes according to their efficiencies and pressure losses, to generate the best optimization scheme; Step S51: performing a preset number of fluid dynamics simulations on the best optimization solution, monitoring the convergence of each fluid dynamics simulation, and generating simulation results; Step S52: fine-tune the torque converter optimization model and boundary conditions according to the simulation results. After a preset number of rounds of fine-tuning, determine the final optimization solution and record the key parameters and adjustment measures of the final optimization solution.

9. A torque converter fluid optimization system using the torque converter fluid optimization method according to any one of claims 1 to 8, characterized in that: include: Torque converter; The cooling device comprises a cooling unit and a circulation unit, wherein the cooling unit wraps the torque converter and is filled with cooling liquid; two ends of the circulation unit are respectively connected to the cooling unit to provide water cooling circulation for the coolant in the cooling unit; The control unit is connected with the torque converter, the cooling unit and the circulation unit to provide fluid optimization and temperature reduction control.

10. The torque converter fluid optimization system according to claim 9, characterized in that: The control unit comprises: A model building module, used to build a geometric model of the hydraulic torque converter according to the parameters of the hydraulic torque converter, generate a hydraulic torque converter model, and then perform meshing on the hydraulic torque converter model; A condition establishment module is used to set a preset fluid model and set the fluid properties of the preset fluid model, and then set preset boundary conditions and initial flow field conditions according to the preset fluid model; An abnormality analysis module, used to calculate the internal flow field of the torque converter using a preset solution method, and then analyze the flow field results and identify abnormal areas where energy loss exceeds a preset range based on the internal flow field of the torque converter; Model optimization module, used to optimize the preset structure of the torque converter, generate the torque converter optimization model, and then perform fluid dynamics simulation based on the torque converter optimization model to verify the optimization results; The loop optimization module is used to repeatedly execute the optimization process until the torque converter optimization model meets the preset optimization requirements.

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