Calculation method and device for viscous loss of oil-filled motor

Abstract

The present application relates to a method and device for calculating the viscous loss of an oil-filled motor. The method and device simulate the fluid field by meshing the three-dimensional model of the motor imported into the CFD software to obtain the mesh model, obtain the friction coefficient simulation data and axial Reynolds number simulation data of the fluid in the Taylor vortex state and the turbulent state, and construct the relationship between the friction coefficient and the axial Reynolds number, the rotor surface roughness height and the temperature of the fluid in the Taylor vortex state and the turbulent state based on the simulation data, and determine the viscous loss of the fluid in the Taylor vortex state and the turbulent state. The present application effectively improves the calculation accuracy of the viscous loss of the oil-filled motor.

Description

Technical Field

[0001] The present application relates to the technical field of oil-filled motors, and in particular to a method and device for calculating viscous loss of oil-filled motors. Background Art

[0002] Oil motors are usually filled with insulating oil. Due to its good cooling and insulation properties, they can operate stably in high temperature and high pressure environments. Therefore, they are widely used in deep sea areas, oil well mining, and aerospace fields. According to statistics, about 41% of common motor failures are caused by bearing failures. Since the viscosity of oil is much greater than that of air, the viscous loss generated by the motor accounts for a large proportion of the total loss. Under high speed conditions, the viscous loss often accounts for more than 50% of the total motor loss. Therefore, accurately and quickly calculating the viscous loss under different motor structures and different working conditions can provide a reasonable basis for the structural optimization design of the motor.

[0003] In the related technical solutions, the calculation of viscous loss mainly adopts the empirical formula method, but its calculation error is large. When the speed increases and Taylor vortex appears in the fluid morphology, the roughness of the rotor surface will have a greater impact on the viscous loss, and when the speed continues to increase, the Reynolds number will increase, and the fluid motion state will become turbulent, which will cause the actual viscous loss to reach nearly 10 times the result of the viscous loss calculated by the analytical formula. Therefore, accurately calculating the friction coefficient is the key to calculating the viscous loss analytical formula. In the related technical solutions, the effects of the Reynolds number and the roughness of the rotor surface on the friction coefficient are not comprehensively considered, and the effect of temperature on the viscous loss is not considered, resulting in inaccurate calculation of the viscous loss. Summary of the invention

[0004] Based on this, the present application proposes a method for calculating the viscous loss of an oil-filled motor, which improves the calculation accuracy of the viscous loss of the oil-filled motor.

[0005] In a first aspect, the present application provides a method for calculating viscous loss of an oil-filled motor, the method comprising:

[0006] The three-dimensional model of the motor is imported into the CFD software, a boundary layer is set in the air gap part of the motor, and the three-dimensional model is meshed to obtain a mesh model of the motor;

[0007] A turbulence model of the fluid field in the air gap part is selected, and the boundary conditions of the turbulence model are set. Based on setting different parameters, the fluid field is simulated and calculated by CFD software to obtain friction coefficient simulation data and axial Reynolds number simulation data of the fluid in Taylor vortex state and turbulent state, wherein the parameters include motor parameters and fluid parameters, the motor parameters are at least one of the following: rotor outer diameter, stator inner diameter, rotor angular velocity, air gap width, rotor surface roughness height, and the fluid parameters are at least one of the following: viscosity and density;

[0008] Based on the friction coefficient simulation data and the axial Reynolds number simulation data, the first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state is obtained by fitting;

[0009] Based on the roughness height of the rotor surface and the first functional relationship, a second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the roughness height of the rotor surface is constructed;

[0010] Based on the relationship between fluid viscosity and temperature change, the third functional relationship between the axial Reynolds number and temperature of the fluid in Taylor vortex state and turbulent state is constructed;

[0011] Based on the first function relationship, the second function relationship and the third function relationship, the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the roughness height of the rotor surface and the temperature is determined, and then a corrected friction coefficient relationship is obtained;

[0012] Based on the modified friction coefficient relationship, the viscous loss of the fluid in the Taylor vortex state and turbulent state is determined.

[0013] In one embodiment, a three-dimensional model of a motor is imported into CFD software, a boundary layer is set in an air gap portion of the motor, and the three-dimensional model is meshed to obtain a mesh model of the motor, including:

[0014] Construct a three-dimensional model of the motor's stator, rotor and winding, import the three-dimensional model into the CFD simulation software, and mesh the three-dimensional model;

[0015] A boundary layer is set in the air gap of the motor, the air gap is divided into a turbulent region, a boundary layer and a laminar region, and the turbulent region and the laminar region are meshed;

[0016] The boundary layer is meshed based on the dimensionless distance and divided into three flow regions: viscous bottom layer, buffer layer and logarithmic layer based on the dimensionless distance, where the dimensionless distance is the distance from a point in the air gap to the boundary condition.

[0017] In one embodiment, based on the friction coefficient simulation data and the axial Reynolds number simulation data, a first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state is fitted, including:

[0018] The roughness height of the rotor surface is set to 0, the rotor outer diameter, air gap width and rotor angular velocity are changed, and the fluid field is simulated and calculated by simulation CFD software to obtain the first simulation data of the change of the friction coefficient of the fluid with the axial Reynolds number under different rotor outer diameters and air gap widths;

[0019] Based on the first simulation data, the first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state is obtained by curve fitting:

[0020] ;

[0021] Among them, C f1 represents the friction coefficient, R in is the rotor outer diameter, δ represents the air gap width of the motor, R eσ represents the axial Reynolds number, z, α, and γ are the first unknown coefficients, and the first unknown coefficients are determined by fitting based on the first simulation data.

[0022] In one embodiment, based on the roughness height of the rotor surface and the first functional relationship, a second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the roughness height of the rotor surface is constructed, including:

[0023] The rotor outer diameter and air gap width are set unchanged, the rotor surface roughness height and the rotor angular velocity are changed, and the fluid field is simulated and calculated by simulation CFD software to obtain the second simulation data of the change of the fluid friction coefficient with the rotor surface roughness height under different angular velocity conditions;

[0024] The second simulation data is curve fitted, and based on the rotor surface roughness height and the first functional relationship, a second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the rotor surface roughness height is constructed. The second functional relationship is:

[0025] ;

[0026] Wherein, Ks represents the roughness height of the rotor surface, b is the second undetermined coefficient, and the second undetermined coefficient is determined by fitting based on the second simulation data.

[0027] In one embodiment, based on the relationship between the viscosity and temperature change of the fluid, a third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state is constructed, including:

[0028] According to the data of the dynamic viscosity of the fluid changing with temperature, the relationship between the dynamic viscosity and temperature of the oil-filled motor fluid is constructed as follows:

[0029] ;

[0030] Where, f(T) represents the viscosity ratio, μ 0represents the dynamic viscosity of the oil-filled motor fluid at room temperature, μ represents the dynamic viscosity of the oil-filled motor fluid at temperature T, and T represents the temperature;

[0031] The relationship between the axial Reynolds number of the fluid and the dynamic viscosity of the fluid is:

[0032] ;

[0033] Among them, ρ represents the fluid density, w represents the rotor angular velocity, and δ represents the air gap width of the motor;

[0034] According to the relationship between the axial Reynolds number of the fluid and the dynamic viscosity of the fluid, and the relationship between the dynamic viscosity of the oil-filled motor fluid and the temperature, the third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state is constructed as follows:

[0035] .

[0036] In one embodiment, based on the first functional relationship, the second functional relationship and the third functional relationship, the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the rotor surface roughness height and the temperature is determined, and then a corrected friction coefficient relationship is obtained, including:

[0037] Based on the first, second and third functional relationships, the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the roughness height of the rotor surface and the temperature is determined, and the corrected friction coefficient C is obtained. f2 The relationship is:

[0038] .

[0039] In one embodiment, based on the modified friction coefficient relationship, determining the viscous loss of the fluid in the Taylor vortex state and the turbulent state includes:

[0040] Viscous loss of fluid P oilgap1 The expression is:

[0041] ;

[0042] Among them, L ef Indicates the effective length of the motor;

[0043] According to the corrected friction coefficient relationship, the viscous loss P of the fluid in the Taylor vortex state and turbulent state is determined. oilgap2 The expression is:

[0044] .

[0045] In a second aspect, the present application provides a device for calculating viscous loss of an oil-filled motor. The device comprises:

[0046] A meshing module is used to import the three-dimensional model of the motor into the CFD software, set a boundary layer in the air gap part of the motor, and mesh the three-dimensional model to obtain a mesh model of the motor;

[0047] A simulation module is used to select a turbulence model of the fluid field in the air gap part, set the boundary conditions of the turbulence model, and simulate and calculate the fluid field through CFD software based on setting different parameters to obtain friction coefficient simulation data and axial Reynolds number simulation data of the fluid in Taylor vortex state and turbulent state, wherein the parameters include motor parameters and fluid parameters, the motor parameters are at least one of the following: rotor outer diameter, stator inner diameter, rotor angular velocity, air gap width, rotor surface roughness height, and the fluid parameters are at least one of the following: viscosity and density;

[0048] A first calculation module is used to fit a first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in a Taylor vortex state and a turbulent state based on the friction coefficient simulation data and the axial Reynolds number simulation data;

[0049] A second calculation module is used to construct a second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the rotor surface roughness height based on the rotor surface roughness height and the first functional relationship;

[0050] A third calculation module is used to construct a third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state based on the relationship between the dynamic viscosity of the fluid and the temperature change;

[0051] A fourth calculation module is used to determine the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the roughness height of the rotor surface and the temperature based on the first functional relationship, the second functional relationship and the third functional relationship, and then obtain a corrected friction coefficient relationship;

[0052] The fifth calculation module is used to determine the viscous loss of the fluid in the Taylor vortex state and the turbulent state based on the modified friction coefficient relationship.

[0053] In a third aspect, the present application provides a computer device including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method for calculating the viscous loss of an oil-filled motor of the first aspect is implemented.

[0054] In a fourth aspect, the present application provides a computer storage medium having a computer program stored thereon, and when the computer program is run on a computer, the computer executes the method for calculating the viscous loss of an oil-filled motor according to the first aspect.

[0055] This application will import the three-dimensional model of the motor into the CFD software, set the boundary layer in the air gap part of the motor, and mesh the three-dimensional model to obtain the network model of the motor. Select the turbulence model of the fluid field in the air gap part, set the boundary conditions, and simulate the fluid field based on different parameter settings to obtain the friction coefficient simulation data and axial Reynolds number simulation data of the fluid in the Taylor vortex state and turbulent state. The first functional relationship is constructed by the friction coefficient simulation data and the axial Reynolds number simulation data, the second functional relationship is constructed by the rotor surface roughness height and the first functional relationship, and the third functional relationship is constructed by the relationship between the viscosity of the fluid and the temperature change. Based on the three functional formulas, the relationship between the friction coefficient and the axial Reynolds number, the rotor surface roughness height and the temperature of the fluid in the Taylor vortex state and the turbulent state is determined, and then the corrected friction coefficient relationship is obtained to determine the viscous loss of the fluid in the Taylor vortex state and the turbulent state. The present application combines the relationship between the friction coefficient and the Reynolds number, the coupling relationship between the friction coefficient and the surface roughness, and the influence of temperature, and corrects the analytical formula for viscous loss after the appearance of Taylor vortex and turbulent state. This can greatly improve the calculation accuracy of the viscous loss of the oil-filled motor, and significantly improve the coupling calculation speed of the viscous loss calculation and the temperature field distribution, thereby greatly improving the calculation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A schematic diagram of a first process flow of a method for calculating viscous loss of an oil-filled motor in one embodiment;

[0057] Figure 2 A second flow chart of a method for calculating viscous loss of an oil-filled motor in one embodiment;

[0058] Figure 3 A schematic diagram of a three-dimensional model of a motor in an embodiment;

[0059] Figure 4 A schematic diagram of meshing a three-dimensional model of a motor in one embodiment;

[0060] Figure 5 A schematic diagram of air gap grid division in one embodiment;

[0061] Figure 6 A third flow chart of a method for calculating viscous loss of an oil-filled motor in one embodiment;

[0062] Figure 7 is a data schematic diagram of the friction coefficient changing with the axial Reynolds number and the ratio of the air gap width to the rotor outer diameter in one embodiment;

[0063] Figure 8 is a relationship diagram between the friction coefficient and the Reynolds number obtained by simulation in one embodiment;

[0064] Fig. 9 A fourth flow chart of a method for calculating viscous loss of an oil-filled motor in one embodiment;

[0065] Fig.10 is a relationship diagram between the friction coefficient and the roughness height of the rotor surface obtained by simulation in one embodiment;

[0066] Fig.11 A system block diagram of a device for calculating viscous loss of an oil-filled motor in one embodiment;

[0067] Fig.12 A system block diagram of a computer device for calculating viscous losses of an oil-filled motor in one embodiment. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution of the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0069] As mentioned above, the viscous loss of the oil-filled motor is closely related to the fluid morphology. The viscous loss of the oil-filled motor fluid is affected by a combination of factors such as the rotor surface roughness and the Reynolds number of the insulating oil. When calculating the viscous loss of the oil-filled motor fluid, the relationship between the flow morphology of the fluid at the air gap and the rotor surface roughness and temperature is not considered. The obtained result is quite different from the actual result, resulting in inaccurate calculation accuracy. Therefore, the embodiment of the present application provides a method for calculating the viscous loss of the oil-filled motor, such as Figure 1 The method comprises the following steps:

[0070] Step 101: Import the constructed three-dimensional model of the motor into the CFD software, set a boundary layer in the air gap part of the motor, and mesh the three-dimensional model to obtain a mesh model of the motor.

[0071] Specifically, CFD (Computational Fluid Dynamics) modeling is to input a three-dimensional mechanical model into the CFD software, and then select a model for the fluid in it to calculate. The calculation usually requires obtaining the motor size parameters, the relevant parameters of the motor oil, etc. The stator and rotor are the two main components of the motor. The air gap is the gap between the rotor and the stator of the motor, which is used to physically separate the two motor components. The air gap is not necessarily air, but can be any non-magnetic material placed in the magnetic circuit to increase the magnetic resistance of the magnetic circuit. In simple terms, the air gap is a piece of non-magnetic material that creates a space between the magnet and the magnetic material. The air gap can be made of materials such as wood, plastic, aluminum and other non-magnetic metals. If the magnet has a coating, such as non-magnetic nickel or rubber epoxy resin coating, the coating will cause an air gap. The larger the air gap, the more common the strength loss. Meshing is to divide the model into many small units. The degree of matching between the meshing and the calculation target and the quality of the mesh determine the quality of the subsequent calculation.

[0072] Step 102: Select a turbulence model of the fluid field in the air gap part, set the boundary conditions of the turbulence model, and simulate and calculate the fluid field through CFD software based on setting different parameters to obtain friction coefficient simulation data and axial Reynolds number simulation data of the fluid in Taylor vortex state and turbulent state, wherein the parameters include motor parameters and fluid parameters, the motor parameters are at least one of the following: rotor outer diameter, stator inner diameter, rotor angular velocity, air gap width, rotor surface roughness height, and the fluid parameters are at least one of the following: viscosity and density.

[0073] Specifically, a turbulence model of the fluid field of a suitable air gap part is selected, and the boundary conditions of the turbulence model are set. The boundary conditions may be velocity boundaries, setting appropriate velocity conditions on the rotor and stator surfaces of the motor; pressure boundaries, setting pressure conditions at the inlet and outlet of the fluid; wall conditions, setting no-slip conditions and appropriate wall roughness on the solid surface of the motor. The motor parameters include at least one of the following: rotor outer diameter, stator inner diameter, rotor angular velocity, air gap width, rotor surface roughness height, and the fluid parameters are at least one of the following: viscosity, density. Use CFD software (such as ANSYS Fluent, CFX, etc.) to simulate and calculate the set model. Extract the following data from the simulation results: friction coefficient simulation data, describing the friction characteristics between the fluid and the motor surface; axial Reynolds number simulation data, describing the laminar or turbulent state of fluid flow.

[0074] Step 103: Based on the friction coefficient simulation data and the axial Reynolds number simulation data, a first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state is obtained by fitting.

[0075] Specifically, the data of friction coefficient and axial Reynolds number are obtained from CFD simulation. These data should include the friction coefficient and the corresponding axial Reynolds number under different working conditions. Select a suitable fitting model according to the data characteristics. For the relationship between the friction coefficient and the axial Reynolds number, polynomial fitting or empirical formula fitting can be considered, such as power function or exponential function form. According to the fitting results, the first functional relationship between the friction coefficient and the axial Reynolds number under the Taylor vortex state is obtained.

[0076] Step 104: Based on the rotor surface roughness height and the first functional relationship, a second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the rotor surface roughness height is constructed.

[0077] Specifically, the friction coefficient data under different rotor surface roughness heights are obtained from CFD simulation. These data will be used to establish the functional relationship between the friction coefficient and the surface roughness. A suitable fitting model is selected according to the data characteristics. For the relationship between the friction coefficient and the surface roughness, polynomial fitting or empirical formula fitting can be considered. Based on the fitting results and the first functional formula, the second functional relationship between the friction coefficient and the axial Reynolds number and the rotor surface roughness height is obtained.

[0078] Step 105: Based on the relationship between the viscosity of the fluid and the temperature change, a third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state is constructed.

[0079] Specifically, the viscosity of the fluid changes with temperature. Generally, the viscosity of the fluid decreases with increasing temperature. Obtain the viscosity data of the fluid at different temperatures from the CFD simulation. These data will be used to establish the functional relationship between viscosity and temperature. Use statistical software or programming tools (such as MATLAB, Python, etc.) to fit the data. Based on the fitting results, the third functional relationship between the axial Reynolds number and temperature is obtained.

[0080] Step 106: Based on the first functional relationship, the second functional relationship and the third functional relationship, determine the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the rotor surface roughness height and the temperature, and then obtain a corrected friction coefficient relationship.

[0081] Specifically, according to step 103, a first functional relationship between the friction coefficient and the axial Reynolds number is obtained. According to step 104, a second functional relationship between the friction coefficient and the axial Reynolds number and the roughness height of the rotor surface is obtained. According to step 105, a third functional relationship between the axial Reynolds number and the temperature is obtained. The three relationships are integrated, that is, the axial Reynolds coefficient expression in the third functional relationship is substituted into the second functional relationship, and the relationship between the friction coefficient and the temperature and the roughness height of the rotor surface is obtained. The relationship between the friction coefficient and the axial Reynolds number, the roughness height of the rotor surface and the temperature is determined to obtain a corrected friction coefficient relationship.

[0082] Step 107: Based on the corrected friction coefficient relationship, determine the viscous loss of the fluid in the Taylor vortex state and the turbulent state.

[0083] Specifically, according to step 106, we obtain a modified friction coefficient relationship that comprehensively considers the influence of the axial Reynolds number, the rotor surface roughness height and the temperature. Based on the modified friction coefficient relationship, the viscous loss under the Taylor vortex state is determined.

[0084] In the above embodiment, the grid model obtained by meshing the three-dimensional model of the motor imported into the CFD software is simulated, and the motor structural parameters, temperature, and rotor surface roughness are changed to obtain a series of simulation data. The first functional relationship is constructed by the friction coefficient simulation data and the axial Reynolds number simulation data respectively; the second functional relationship is constructed by the rotor surface roughness height and the first functional relationship; the third functional relationship is constructed by the relationship between the viscosity of the fluid and the temperature change. Based on the three functional relationships, the relationship between the friction coefficient and the axial Reynolds number, the rotor surface roughness height and the temperature is determined, and then the corrected friction coefficient relationship is obtained. The present application combines the relationship between the friction coefficient and the Reynolds number, the coupling relationship between the friction coefficient and the surface roughness, and the influence of temperature to correct the viscous loss analytical formula after the Taylor vortex appears, which can greatly improve the calculation accuracy of the viscous loss of the oil-filled motor, and significantly improve the coupling calculation speed of the viscous loss calculation and the temperature field distribution, greatly improving the calculation efficiency.

[0085] In one embodiment, Figure 2 As shown, the three-dimensional model of the motor is imported into the CFD software, a boundary layer is set in the air gap part of the motor, and the three-dimensional model is meshed to obtain the mesh model of the motor, including:

[0086] Step 201: construct a three-dimensional model of the stator, rotor and winding of the motor, import the three-dimensional model into CFD simulation software, and mesh the three-dimensional model;

[0087] Specifically, CFD modeling (fluid dynamics modeling) is first performed, and the RNG k-ε model is selected. In this step, the three-dimensional mechanical model needs to be simplified, and some mechanical features that have little effect on the fluid field distribution, such as permanent magnets, bearings, brushes, commutators, etc., are ignored. The rotor is approximated by a cylinder, and the sharp parts of the model are processed. The motor model is as follows Figure 3 As shown. The constructed three-dimensional motor model is imported into the CFD simulation software, and the motor model is meshed. Meshing plays an extremely important role in computational fluid dynamics. Optimized meshing can reduce the amount of calculation while ensuring accuracy, thereby improving calculation efficiency and reducing calculation costs. The meshing inside the motor is shown in Figure 4 shown.

[0088] It should be noted that the RNG k-ε model is selected here for simulation calculation. A correction coefficient is used in the turbulent dissipation rate equation to consider the interaction between turbulent dissipation and average shear. The equation is as follows:

[0089]

[0090] Where t is time, ρ is the fluid density, k is the fluid turbulence kinetic energy, ε is the turbulent dissipation rate per unit mass of fluid, and u i is the time-averaged velocity of the fluid, x i With x j is the fluid transport component, i and j represent radial and tangential directions, and is the Prandtl number, which is 0.7194. is the generation term of turbulent kinetic energy, μ is the dynamic viscosity coefficient of the fluid, and μ t is the eddy current corrected fluid viscosity, is an empirical constant with a value of 1.42. is an empirical constant.

[0091] Compared with the standard k-ε model, the RNG k-ε model introduces a correction term related to the flow turbulence intensity. The calculation formula is as follows:

[0092] ;

[0093] .

[0094] in, is an empirical constant, and its value is 1.68; is the turbulent Prandtl number, which is 0.0845; is an empirical constant, its value is 4.38; is a dimensionless variable; is the modulus of the strain rate tensor; is a dimensionless variable. The RNG k-ε model shows better stability and reliability when dealing with complex flow problems (such as separated flow, backflow, etc.), and more accurately predicts the turbulent characteristics in the flow.

[0095] Step 202: setting a boundary layer in the air gap of the motor, dividing the air gap into a turbulent region, a boundary layer and a laminar region, and performing grid division on the turbulent region and the laminar region;

[0096] Specifically, in the CFD simulation software, a boundary layer is set for the air gap of the motor. The boundary layer is the area where the flow velocity, pressure, temperature and other fluid properties change sharply in the contact area between the fluid and the solid surface. The air gap is divided into three main flow regions: turbulent region, boundary layer and laminar region. The grid division is based on the characteristics of the flow and the velocity gradient, where the turbulent region is usually located in the center of the air gap, the laminar region is close to the wall, and the boundary layer is the transition zone from the wall to the turbulent region. The grid division of the turbulent region and the laminar region is as follows Figure 5 shown.

[0097] Step 203: Meshing the boundary layer based on the dimensionless distance, and dividing the boundary layer into three flow regions, namely, a viscous bottom layer, a buffer zone, and a logarithmic layer, based on the dimensionless distance, wherein the dimensionless distance is the distance from a point in the air gap to the boundary condition.

[0098] Specifically, the dimensionless distance y+ is an important parameter used to describe the flow near the wall in fluid mechanics, especially in the study of turbulent boundary layers. It defines the distance from the wall to a certain point, expressed in a dimensionless form, to evaluate the characteristics of the flow in different regions. Its definition is as follows:

[0099] .

[0100] in, y is the vertical distance from the wall to a point. r is the friction velocity, defined as:

[0101] ;

[0102] where τw is the wall shear stress and v is the kinematic viscosity of the fluid.

[0103] According to the value of the dimensionless distance y+, the near-wall region is divided into three flow regions: the viscous sublayer, the buffer layer, and the log-law region. Viscous sublayer: y+ < 5. In this region, the flow is almost laminar, with a large velocity gradient, and fluid molecules interact directly with the wall. Buffer layer: 5 < y+ < 30. In this region, the flow characteristics transition, with both viscous and turbulent effects. Log-law region: y+ > 30. In this region, the turbulent effect dominates, and the velocity distribution generally follows a logarithmic law. In CFD simulations, reasonable mesh generation is crucial for simulating turbulent boundary layers. For wall-adjacent meshes, it is usually required that the position of the first mesh point satisfies y+ < 1 or y+ < 5 to accurately capture the flow characteristics of the viscous sublayer.

[0104] In this embodiment, the method first involves constructing a three-dimensional model of the stator, rotor, and windings of the motor and importing the model into CFD simulation software for mesh generation to obtain the mesh model of the motor. Further, a boundary layer is set in the air gap of the motor and divided into a turbulent region, a boundary layer, and a laminar region, and these regions are finely meshed. The boundary layer is meshed based on the dimensionless distance (i.e., the distance from a point in the air gap to the boundary condition) and divided into three flow regions: the viscous sublayer, the buffer layer, and the log-law region. This method improves the accuracy and efficiency of calculating the viscous losses of the oil-filled motor, corrects the friction coefficient through CFD simulation data, and takes into account the influence of temperature on viscosity, realizing the coupling of viscous losses and the temperature field, thereby providing a more accurate basis for the structural optimization design of the motor and improving the performance and reliability of the motor under different working conditions.

[0105] It should be noted that the traditional viscous empirical formula is divided into two parts: before the appearance of laminar flow and Taylor vortices, as shown in the following formula:

[0106] ;

[0107] In the formula, μ is the fluid viscosity, R 2 is the inner diameter of the stator, R 1 is the outer diameter of the rotor, w is the angular velocity of the rotor. L ef is the effective length of the motor. C f is the friction coefficient, and Re is the Reynolds number. Among them, the friction coefficient is related to the Reynolds number and can be expressed as:

[0108] ;

[0109] where, Re δ is the axial Reynolds number, Re a is the tangential Reynolds number, and its expression is:

[0110] .

[0111] The flow state of oil is determined by the Reynolds number, which is:

[0112] when Re <300, the oil flow is pure laminar flow, called circular Couette flow.

[0113] When 300< Re <2000, an axisymmetric annular vortex appears in the oil flow, which is called Taylor vortex.

[0114] when Re >2000, the oil flow becomes turbulent.

[0115] It can be seen from the above relationship that the friction coefficient of the analytical formula after the appearance of Taylor vortex is related to many factors, so the correction of the friction coefficient is very necessary for the accurate calculation of viscous loss.

[0116] In one embodiment, Figure 6 As shown, based on the friction coefficient simulation data and the axial Reynolds number simulation data, the first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state is fitted, including:

[0117] Step 601: setting the rotor surface roughness height to 0, changing the rotor outer diameter, air gap width and rotor angular velocity, and performing simulation calculation on the fluid field through simulation CFD software to obtain first simulation data of the change of the friction coefficient of the fluid with the axial Reynolds number under different rotor outer diameters and air gap widths;

[0118] Specifically, the roughness height of the rotor surface is set to 0 to eliminate the effect of surface roughness on the fluid flow characteristics, so as to focus on studying the effects of rotor outer diameter, air gap width and rotor angular velocity on the friction coefficient. A series of different combinations of rotor outer diameter and air gap width are selected, and these parameters are used in CFD simulation to simulate fluid flow under different operating conditions. The angular velocity of the rotor is changed to cover different operating conditions. This will affect the flow characteristics of the fluid, especially the axial Reynolds number. The fluid field is simulated and calculated using CFD software to obtain the first simulation data of the variation of the friction coefficient of the fluid with the axial Reynolds number under different rotor outer diameters and air gap widths. Based on the first simulation data, a data graph of the variation of the friction coefficient with the axial Reynolds number and the ratio of the air gap width to the rotor outer diameter is obtained, as shown in the figure. Figure 7 shown.

[0119] Step 602: Perform curve fitting based on the first simulation data to obtain a first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state, which is expressed as:

[0120] ;

[0121] Among them, C f1 represents the friction coefficient, R in is the rotor outer diameter, δ represents the air gap width of the motor, R eσ represents the axial Reynolds number, z, α, and γ are the first unknown coefficients, and the first unknown coefficients are determined by fitting based on the first simulation data.

[0122] Specifically, the relationship between the friction coefficient and the axial Reynolds number is first considered. Based on the first simulation data, a curve fitting is performed to obtain a relationship diagram between the friction coefficient and the Reynolds number, such as Figure 8 As shown, the horizontal axis is the axial Reynolds number and the vertical axis is the friction coefficient. Using the relationship diagram between the friction coefficient and the axial Reynolds number obtained by simulation, the relationship between the friction coefficient and the axial Reynolds number can be expressed by the following formula:

[0123] .

[0124] The coefficient z is established by fitting. z is used to represent the air gap thickness including the air gap area. δ and rotor radius R in Due to the narrowness of the air gap of the oil-filled permanent magnet synchronous motor (0.5–1.5 mm), the air gap thickness is used δ / R in To express this feature, we can use the coefficient z Expressed as δ / R in The function of z ( δ / R in ). Taking the logarithm of both sides gives the formula:

[0125] .

[0126] Based on the curve fitting of the first simulation data, the first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state is expressed as:

[0127] ;

[0128] Among them, C f1 represents the friction coefficient, R in is the rotor outer diameter, δ represents the air gap width of the motor, R eσrepresents the axial Reynolds number, z, α, and γ are first undetermined coefficients, and the first undetermined coefficients are determined by fitting based on the first simulation data. This embodiment can accurately describe the relationship between the friction coefficient and the axial Reynolds number, thereby improving the accuracy of the viscous loss calculation of the oil-filled motor.

[0129] In one embodiment, Fig. 9 As shown, the coupling relationship between the friction coefficient and the rotor surface roughness height of the rotor surface is determined, and according to the coupling relationship and the first functional relationship, the second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the rotor surface roughness height is constructed, including:

[0130] Step 901: setting the rotor outer diameter and the air gap width unchanged, changing the rotor surface roughness height and the rotor angular velocity, and performing simulation calculation on the fluid field through simulation CFD software to obtain second simulation data of the change of the fluid friction coefficient with the rotor surface roughness height under different angular velocity conditions;

[0131] Specifically, the coupling relationship between the friction coefficient and the surface roughness is considered. Keeping the rotor outer diameter and the air gap width unchanged, a series of different combinations of rotor surface roughness heights and rotor angular velocities are selected. Use CFD software to simulate the fluid field under different conditions. In the simulation, the rotor surface roughness and angular velocity are used as variables to simulate the fluid flow and the change of friction coefficient under different working conditions. The friction coefficient data under different rotor surface roughness and angular velocity conditions are collected, and these friction coefficient data are used as the second simulation data of the change of the friction coefficient of the fluid with the rotor surface roughness height under different angular velocity conditions. The relationship diagram between the friction coefficient and the rotor surface roughness height obtained based on the second simulation data is as shown in Fig.10 As shown, the horizontal axis is the roughness height of the rotor surface and the vertical axis is the friction coefficient.

[0132] Step 902: curve fitting is performed on the second simulation data, and based on the rotor surface roughness height and the first functional relationship, a second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the rotor surface roughness height is constructed, and the second functional relationship is:

[0133] ;

[0134] Wherein, b is the second undetermined coefficient, and the second undetermined coefficient is determined by fitting based on the second simulation data.

[0135] Specifically, based on step 901, the friction coefficient data under different rotor surface roughness heights and angular velocity conditions have been obtained. Based on the simulation results and experimental results, when Taylor vortices appear in the fluid morphology, the influence of the rotor surface roughness on the viscous loss is greater, so the concept of roughness ratio is proposed:

[0136] ;

[0137] in, R in is the rotor outer diameter, K s is the surface roughness height (unit: mm). Substituting the surface roughness height into the calculation of the friction coefficient, the expression of the friction coefficient can be obtained as follows:

[0138] ;

[0139] Among them, b is the second undetermined coefficient, and the second undetermined coefficient b is determined by fitting based on the second simulation data through CFD simulation. The friction coefficient expression is the second functional relationship between the friction coefficient and the axial Reynolds number and the roughness height of the rotor surface.

[0140] In this embodiment, the method can accurately describe the relationship between the friction coefficient and the rotor surface roughness and the axial Reynolds number, and can more accurately predict the viscous loss of the oil-filled motor under different operating conditions, thereby providing an important theoretical basis for the design and performance optimization of the motor.

[0141] In one embodiment, based on the relationship between the viscosity and temperature change of the fluid, a third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state is constructed, including:

[0142] Considering that temperature will affect the viscosity of oil, and when the fluid is turbulent, the viscosity mainly affects the size of the Reynolds number. In order to more conveniently take temperature into account in the calculation of viscous loss, the viscosity ratio is introduced, that is:

[0143] ;

[0144] According to the data of the dynamic viscosity of the selected oil changing with temperature, its f(T) expression.

[0145] Therefore, according to the data of the dynamic viscosity of the fluid changing with temperature, the relationship between the dynamic viscosity and temperature of the oil-filled motor fluid is constructed as follows:

[0146] ;

[0147] Where, f(T) represents the viscosity ratio, μ 0 It represents the dynamic viscosity of the oil-filled motor fluid at room temperature, and μ represents the dynamic viscosity of the oil-filled motor fluid at temperature T.

[0148] Calculate μ = μ 0* f(T). So μ= μ 0* Substituting f(T) into the relationship between the axial Reynolds number and the dynamic viscosity of the fluid, the relationship between the axial Reynolds number and the dynamic viscosity of the fluid is:

[0149] ;

[0150] Among them, ρ represents the fluid density, w represents the rotor angular velocity, and δ represents the air gap width of the motor;

[0151] According to the relationship between the axial Reynolds number of the fluid and the dynamic viscosity of the fluid, and the relationship between the dynamic viscosity of the oil-filled motor fluid and the temperature, the third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state is constructed as follows:

[0152] .

[0153] In this embodiment, the method determines the relationship between the dynamic viscosity and temperature of the oil-filled motor fluid, and uses the relationship between the axial Reynolds number and the dynamic viscosity of the fluid to construct a third functional relationship between the axial Reynolds number and the temperature, which can accurately describe the relationship between the axial Reynolds number and the temperature, so that the influence of temperature is considered when calculating the viscous loss of the oil-filled motor. Through the third functional relationship, the characteristics of the fluid flow inside the motor under different temperature conditions can be more accurately predicted, thereby improving the accuracy of the viscous loss calculation, which is crucial for the performance analysis and optimization of the motor under different ambient temperatures.

[0154] In one embodiment, based on the first functional relationship, the second functional relationship and the third functional relationship, the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the rotor surface roughness height and the temperature is determined, and then a corrected friction coefficient relationship is obtained, including:

[0155] Based on the first, second and third functional relationships, the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the roughness height of the rotor surface and the temperature is determined, and the corrected friction coefficient C is obtained. f2 The relationship is:

[0156] .

[0157] Specifically, the third functional relationship between the axial Reynolds number and the temperature is substituted into the second functional relationship between the friction coefficient and the axial Reynolds number and the rotor surface roughness height, the relationship between the friction coefficient and the axial Reynolds number, the rotor surface roughness height and the temperature is determined, and a corrected friction coefficient relationship is obtained.

[0158] In this embodiment, the method establishes a complex relationship between the friction coefficient and the axial Reynolds number, the rotor surface roughness height and the temperature by combining the first functional relationship, the second functional relationship and the third functional relationship, and obtains a revised friction coefficient relationship. This revised friction coefficient relationship makes the prediction of the viscous loss of the oil-filled motor under different working conditions more accurate, which helps to optimize the motor performance, reduce energy consumption, extend the service life, and reduce the dependence on experiments in actual engineering applications, thereby improving the efficiency of design and analysis.

[0159] In one embodiment, based on the modified friction coefficient relationship, determining the viscous loss of the fluid in the Taylor vortex state and the turbulent state includes:

[0160] From the above, we can see that the viscous loss P of the fluid oilgap1 The expression is:

[0161] ;

[0162] According to the corrected friction coefficient relationship, the viscous loss P of the fluid in the Taylor vortex state and turbulent state is determined. oilgap2 The expression is:

[0163] .

[0164] Specifically, the flow state of oil is determined by the Reynolds number. Re <2000, the oil flow becomes Taylor vortex. Substituting the fluid viscous loss expression in the Taylor vortex state into the corrected friction coefficient relationship, the expression of viscous loss in the Taylor vortex state is obtained.

[0165] In this embodiment, the corrected friction coefficient relationship is used to calculate the viscous loss in the Taylor eddy state and the turbulent state, thereby improving the accuracy of the calculation of the viscous loss of the oil-filled motor.

[0166] Based on the same inventive concept, the present application also provides a device for calculating the viscous loss of an oil-filled motor as mentioned above. The implementation solution for solving the problem provided by the device is similar to the implementation solution recorded in the above method. Therefore, the specific limitations in one or more embodiments of the viscous loss calculation device for an oil-filled motor provided below can be found in the above limitations on the method for calculating the viscous loss of an oil-filled motor, and will not be repeated here.

[0167] In one embodiment, Fig.11As shown, a device for calculating viscous loss of an oil-filled motor is provided. The device comprises: a grid division module 1101, a simulation module 1102, a first calculation module 1103, a second calculation module 1104, a third calculation module 1105, a fourth calculation module 1106 and a fifth calculation module 1107, wherein:

[0168] A meshing module 1101 is used to import the three-dimensional model of the motor into the CFD software, set a boundary layer in the air gap part of the motor, and mesh the three-dimensional model to obtain a mesh model of the motor;

[0169] The simulation module 1102 is used to select a turbulence model of the fluid field in the air gap part, set the boundary conditions of the turbulence model, and simulate and calculate the fluid field through CFD software based on setting different parameters to obtain friction coefficient simulation data and axial Reynolds number simulation data of the fluid in Taylor vortex state and turbulent state, wherein the parameters include motor parameters and fluid parameters, the motor parameters are at least one of the following: rotor outer diameter, stator inner diameter, rotor angular velocity, air gap width, rotor surface roughness height, and the fluid parameters are at least one of the following: viscosity and density;

[0170] A first calculation module 1103 is used to fit a first functional relationship between the friction coefficient and the axial Reynolds number in a Taylor vortex state and a turbulent state based on the friction coefficient simulation data and the axial Reynolds number simulation data;

[0171] A second calculation module 1104 is used to construct a second functional relationship between the friction coefficient and the axial Reynolds number and the rotor surface roughness height in the Taylor vortex state and the turbulent state based on the rotor surface roughness height and the first functional relationship;

[0172] The third calculation module 1105 is used to construct a third functional relationship between the axial Reynolds number and the temperature in the Taylor vortex state and the turbulent state based on the relationship between the dynamic viscosity of the fluid and the temperature change;

[0173] A fourth calculation module 1106 is used to determine the relationship between the friction coefficient and the axial Reynolds number, the rotor surface roughness height and the temperature in the Taylor vortex state and the turbulent state based on the first functional relationship, the second functional relationship and the third functional relationship, and then obtain a corrected friction coefficient relationship;

[0174] The fifth calculation module 1107 is used to determine the viscous loss in the Taylor vortex state and the turbulent state based on the corrected friction coefficient relationship.

[0175] In one embodiment, the first calculation module 1103 sets the rotor surface roughness height to 0, changes the rotor outer diameter, the air gap width and the rotor angular velocity, and performs simulation calculation on the fluid field through simulation CFD software to obtain first simulation data of the change of the friction coefficient of the fluid with the axial Reynolds number under different rotor outer diameters and air gap widths. Based on the first simulation data, curve fitting is performed to obtain a first functional relationship between the friction coefficient and the axial Reynolds number in the Taylor vortex state and the turbulent state, which is expressed as:

[0176] ;

[0177] Among them, C f1 represents the friction coefficient, R in is the rotor outer diameter, δ represents the air gap width of the motor, R eσ represents the axial Reynolds number, z, α, and γ are the first unknown coefficients, and the first unknown coefficients are determined by fitting based on the first simulation data.

[0178] In one embodiment, the second calculation module 1104 sets the rotor outer diameter and the air gap width unchanged, changes the rotor surface roughness height and the rotor angular velocity, and performs simulation calculation on the fluid field through simulation CFD software to obtain second simulation data of the change of the friction coefficient of the fluid with the rotor surface roughness height under different angular velocity conditions; curve fitting is performed on the second simulation data, and based on the rotor surface roughness height and the first functional relationship, a second functional relationship between the friction coefficient and the axial Reynolds number and the rotor surface roughness height under Taylor vortex state and turbulent state is constructed, and the second functional relationship is:

[0179] ;

[0180] Among them, K s represents the roughness height of the rotor surface, b is the second unknown coefficient, and the second unknown coefficient is determined by fitting based on the second simulation data.

[0181] In one embodiment, the third calculation module 1105 constructs a third functional relationship between the axial Reynolds number and the temperature in the Taylor vortex state and the turbulent state based on the relationship between the viscosity and the temperature change of the fluid, wherein:

[0182] According to the data of the dynamic viscosity of the fluid changing with temperature, the relationship between the dynamic viscosity and temperature of the oil-filled motor fluid is constructed as follows:

[0183] ;

[0184] Where, f(T) represents the viscosity ratio, μ 0 represents the dynamic viscosity of the oil-filled motor fluid at room temperature, μ represents the dynamic viscosity of the oil-filled motor fluid at temperature T, and T represents the temperature;

[0185] The relationship between the axial Reynolds number and dynamic viscosity of the fluid is:

[0186] ;

[0187] Among them, ρ represents the fluid density, w represents the rotor angular velocity, and δ represents the air gap width of the motor;

[0188] According to the relationship between the axial Reynolds number of the fluid and the dynamic viscosity of the fluid, and the relationship between the dynamic viscosity of the oil-filled motor fluid and the temperature, the third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state is constructed as follows:

[0189] .

[0190] In one embodiment, the fourth calculation module 1106 determines the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the rotor surface roughness height and the temperature based on the first functional relationship, the second functional relationship and the third functional relationship, and then obtains the corrected friction coefficient C f2 The relationship is:

[0191] .

[0192] In one embodiment, the fifth calculation module 1107 determines the viscous loss of the fluid in the Taylor vortex state and the turbulent state based on the modified friction coefficient relationship, including:

[0193] Viscous loss of fluid P oilgap1 The expression is:

[0194] ;

[0195] According to the corrected friction coefficient relationship, the expression for determining the viscous loss of the fluid in the Taylor vortex state and turbulent state is:

[0196] ;

[0197] Among them, P oilgap2 It represents the viscous loss of the fluid in Taylor vortex state and turbulent state.

[0198] Each module in the above-mentioned oil-filled motor viscous loss calculation device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0199] Based on the same concept, the present application also provides a computer device for calculating the viscous loss of an oil-filled motor, including a memory and a processor.

[0200] Specifically, Fig.12 It is a hardware structure diagram of a computer device provided by this application. Fig.12 The computer device shown includes: a processor 1201, a communication interface 1202, a memory 1203 and a communication bus 1204. The processor 1201, the communication interface 1202 and the memory 1203 communicate with each other via the communication bus 1204. Fig.12 The connection method between the processor 1201, the communication interface 1202, and the memory 1203 shown is merely exemplary. During implementation, the processor 1201, the communication interface 1202, and the memory 1203 may also be connected to each other in communication with each other using other connection methods besides the communication bus 1204.

[0201] The processor 1201 may be a general-purpose processor, which may be a processor that performs specific steps and / or operations by reading and executing a computer program (e.g., a computer program) stored in a memory (e.g., memory 1203). The general-purpose processor may use data stored in the memory (e.g., memory 1203) during the execution of the steps and / or operations. The general-purpose processor may be, for example, but not limited to, a central processing unit (CPU). In addition, the processor 1201 may also be a dedicated processor, which may be a processor specially designed to perform specific steps and / or operations. The dedicated processor may be, but not limited to, an ASIC and an FPGA, etc. In addition, the processor 1201 may also be a combination of multiple processors, such as a multi-core processor.

[0202] The communication interface 1202 may include an input / output (I / O) interface, a physical interface, and a logical interface for interconnecting devices within the network device, as well as an interface for interconnecting the network device with other devices (e.g., network devices). The communication network may be Ethernet, a radio access network (RAN), a wireless local area network (WLAN), etc. The communication interface 1202 may be a module, a circuit, a transceiver, or any device capable of implementing communication.

[0203] The memory 1203 can be used to store a computer program, which may include instructions and data to implement the steps of any of the above synchronous motor position sensorless control methods. In an embodiment of the present application, the memory 1203 may be various types of storage media, such as random access memory (RAM), read only memory (ROM), non-volatile RAM (NVRAM), programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), flash memory, optical storage, and registers. The memory 1203 may include a hard disk and / or a memory.

[0204] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in the processor for execution. The software module can be located in a mature storage medium in the field such as a random access memory flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 1203, and the processor 1201 reads the information in the memory 1203 and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0205] An embodiment of the present application also provides a computer storage medium, which, when one or more instructions of the computer program stored therein are executed by the method for calculating the viscous loss of an oil-filled motor, implements the various processes of the above-mentioned method embodiment and can achieve the same technical effect as the above-mentioned method. To avoid repetition, they will not be repeated here.

[0206] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0207] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for calculating viscous loss of an oil-filled motor, characterized in that: The method comprises: Importing the constructed three-dimensional model of the motor into CFD software, setting a boundary layer in the air gap portion of the motor, and meshing the three-dimensional model to obtain a mesh model of the motor; A turbulence model of the fluid field of the air gap portion is selected, boundary conditions of the turbulence model are set, and based on setting different parameters, the fluid field is simulated and calculated by the CFD software to obtain friction coefficient simulation data and axial Reynolds number simulation data of the fluid in Taylor vortex state and turbulent state, wherein the parameters include motor parameters and fluid parameters, the motor parameters are at least one of the following: rotor outer diameter, stator inner diameter, rotor angular velocity, air gap width, rotor surface roughness height, and the fluid parameters are at least one of the following: viscosity and density; Based on the friction coefficient simulation data and the axial Reynolds number simulation data, a first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state is obtained by fitting; Based on the roughness height of the rotor surface and the first functional relationship, a second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the roughness height of the rotor surface is constructed; Based on the relationship between fluid viscosity and temperature change, the third functional relationship between the axial Reynolds number and temperature of the fluid in Taylor vortex state and turbulent state is constructed; Based on the first function relationship, the second function relationship and the third function relationship, the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the roughness height of the rotor surface and the temperature is determined, and then a corrected friction coefficient relationship is obtained; Based on the corrected friction coefficient relationship, the viscous loss of the fluid in the Taylor vortex state and the turbulent state is determined.

2. The method for calculating viscous loss of an oil-filled motor according to claim 1, characterized in that: The three-dimensional model of the motor is imported into the CFD software, a boundary layer is set in the air gap part of the motor, and the three-dimensional model is meshed to obtain a mesh model of the motor, including: Constructing a three-dimensional model of the stator, rotor and winding of the motor, importing the three-dimensional model into CFD simulation software, and meshing the three-dimensional model; Setting a boundary layer in the air gap of the motor, dividing the air gap into a turbulent region, a boundary layer and a laminar region, and performing grid division on the turbulent region and the laminar region; The boundary layer is meshed based on a dimensionless distance, and the boundary layer is divided into three flow regions, namely, a viscous bottom layer, a buffer zone, and a logarithmic layer, based on the dimensionless distance, wherein the dimensionless distance is a distance from a point in the air gap to the boundary condition.

3. The method for calculating viscous loss of an oil-filled motor according to claim 1, characterized in that: The first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state is obtained by fitting based on the friction coefficient simulation data and the axial Reynolds number simulation data, including: Setting the roughness height of the rotor surface to 0, changing the rotor outer diameter, the air gap width and the angular velocity of the rotor, and performing simulation calculation on the fluid field by using the simulation CFD software to obtain first simulation data of the change of the friction coefficient of the fluid with the axial Reynolds number under the conditions of different rotor outer diameters and air gap widths; Based on the first simulation data, curve fitting is performed to obtain the first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in the Taylor vortex state and the turbulent state, which is expressed as: ； Among them, C f1 represents the friction coefficient, R in is the rotor outer diameter, δ represents the air gap width of the motor, R eσ represents the axial Reynolds number, z, α, and γ are first undetermined coefficients, and the first undetermined coefficients are determined by fitting based on the first simulation data.

4. The method for calculating viscous loss of an oil-filled motor according to claim 3, characterized in that: The second functional relationship between the friction coefficient, the axial Reynolds number, and the roughness height of the rotor surface is constructed based on the roughness height of the rotor surface and the first functional relationship, including: The outer diameter of the rotor and the air gap width are set to remain unchanged, the roughness height of the rotor surface and the angular velocity of the rotor are changed, and the fluid field is simulated and calculated by the simulation CFD software to obtain second simulation data of the change of the friction coefficient of the fluid with the roughness height of the rotor surface under different angular velocity conditions; The second simulation data is curve fitted, and based on the rotor surface roughness height and the first functional relationship, a second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the rotor surface roughness height is constructed, and the second functional relationship is: ； Wherein, Ks represents the roughness height of the rotor surface, b is a second undetermined coefficient, and the second undetermined coefficient is determined by fitting based on the second simulation data.

5. The method for calculating viscous loss of an oil-filled motor according to claim 4, characterized in that: The third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state is constructed based on the relationship between the viscosity and temperature of the fluid, including: According to the data of the dynamic viscosity of the fluid changing with temperature, the relationship between the dynamic viscosity and temperature of the oil-filled motor fluid is constructed as follows: ； Wherein, f(T) represents the viscosity ratio, μ0 represents the dynamic viscosity of the oil-filled motor fluid at room temperature, μ represents the dynamic viscosity of the oil-filled motor fluid at temperature T, and T represents temperature; The relationship between the axial Reynolds number and dynamic viscosity of the fluid is: ； Among them, ρ represents the fluid density, w represents the rotor angular velocity, and δ represents the air gap width of the motor; According to the relationship between the axial Reynolds number of the fluid and the dynamic viscosity of the fluid, and the relationship between the dynamic viscosity of the oil-filled motor fluid and the temperature, the third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state is constructed as follows: 。 6. The method for calculating viscous loss of an oil-filled motor according to claim 5, characterized in that: Based on the first functional relationship, the second functional relationship and the third functional relationship, the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the rotor surface roughness height and the temperature is determined, and then the corrected friction coefficient relationship is obtained, including: Based on the first, second and third functional relationships, the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the roughness height of the rotor surface and the temperature is determined, and the corrected friction coefficient C is obtained. f2 The relationship is: 。 7. The method for calculating viscous loss of an oil-filled motor according to claim 6, characterized in that: The method of determining the viscous loss of the fluid in the Taylor vortex state and the turbulent state based on the corrected friction coefficient relationship includes: Viscous loss of fluid P oilgap1 The expression is: ； Among them, L ef Indicates the effective length of the motor; According to the corrected friction coefficient relationship, the viscous loss P of the fluid in the Taylor vortex state and turbulent state is determined oilgap2 The expression is: 。 8. A device for calculating viscous loss of an oil-filled motor, characterized in that: The device comprises: A meshing module is used to import the three-dimensional model of the motor into the CFD software, set a boundary layer in the air gap part of the motor, and mesh the three-dimensional model to obtain a mesh model of the motor; A simulation module, for selecting a turbulence model of the fluid field of the air gap portion, setting boundary conditions of the turbulence model, and performing simulation calculations on the fluid field through the CFD software based on setting different parameters, to obtain friction coefficient simulation data and axial Reynolds number simulation data of the fluid in Taylor vortex state and turbulent state, wherein the parameters include motor parameters and fluid parameters, the motor parameters are at least one of the following: rotor outer diameter, stator inner diameter, rotor angular velocity, air gap width, rotor surface roughness height, and the fluid parameters are at least one of the following: viscosity and density; A first calculation module is used to fit a first functional relationship between the friction coefficient and the axial Reynolds number of the fluid in a Taylor vortex state and a turbulent state based on the friction coefficient simulation data and the axial Reynolds number simulation data; A second calculation module is used to construct a second functional relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number and the rotor surface roughness height based on the rotor surface roughness height and the first functional relationship; A third calculation module is used to construct a third functional relationship between the axial Reynolds number and the temperature of the fluid in the Taylor vortex state and the turbulent state based on the relationship between the dynamic viscosity of the fluid and the temperature change; a fourth calculation module, for determining the relationship between the friction coefficient of the fluid in the Taylor vortex state and the turbulent state and the axial Reynolds number, the roughness height of the rotor surface and the temperature based on the first functional relationship, the second functional relationship and the third functional relationship, and then obtaining a corrected friction coefficient relationship; The fifth calculation module is used to determine the viscous loss of the fluid in the Taylor vortex state and the turbulent state based on the corrected friction coefficient relationship.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method for calculating the viscous loss of an oil-filled motor according to any one of claims 1 to 7 is implemented.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed on a computer, the computer is enabled to execute the method for calculating the viscous loss of an oil-filled motor according to any one of claims 1 to 7.

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