Disclosure of Invention
In order to solve the technical problems in the background, the application provides a friction pair surface micro-texture for reducing high-speed friction belt row torque. To solve the following problems: (1) The linear speed (2) for delaying the occurrence of the high-frequency collision of the wet clutch reduces the torque value of the belt bar of the high-speed stage of the idle wet clutch. Aiming at the problem of the belt-driven torque of the no-load wet clutch in the high-speed stage, the method adopts a method combining theoretical analysis, numerical simulation and experimental study based on a single friction plate fluid-solid coupling dynamics model, obtains the influencing factors of the belt-driven torque of the wet clutch in the high-speed range, determines the optimized variables, establishes an optimized design model, and finally solves the optimized model to obtain the optimal friction plate surface micro-texture of the high-speed low belt-driven torque, thereby greatly reducing the belt-driven torque of the no-load wet clutch in the high-speed stage.
In order to achieve the above purpose, the application provides a method for designing a micro-texture on the surface of a friction plate of a wet clutch, comprising the following steps:
constructing a friction plate surface micro-texture line parameter model of the wet clutch;
acquiring a design variable based on the friction plate surface micro-texture line parameter model;
and optimizing the design variable to obtain the surface micro-texture of the friction plate of the wet clutch.
Preferably, the method for constructing the friction plate surface micro-texture line parameter model comprises the following steps:
any micro-texture line parameterization representation method based on a curve interpolation method is adopted to obtain a shape line expression;
fitting the shape line expression by adopting a cubic spline interpolation method to obtain a micro-texture shape line expression;
and optimizing the micro-texture line expression to obtain the friction plate surface micro-texture line parameter model.
Preferably, the design variables include: friction plate micro-texture parameters and micro-texture line parameters;
the friction plate micro-texture parameters include: the number of micro-textures, the depth of the micro-textures, the circumferential groove table ratio and the radial groove dam ratio; wherein the circumferential groove table ratio is a ratio representing the micro-texture to the circumferential direction of the periodic unit; the radial groove dam ratio is the ratio of representing the micro texture to the radial direction between the inner diameter and the outer diameter;
the micro-texture line parameters include: offset angles of four discrete points on the shape line in the circumferential direction.
Preferably, the constraint condition of the design variable includes:
g i (X)≤0,i=1~24
wherein the constraint function g i The definition of (X) includes:
wherein N is g Representing the number of microtextures; n (N) gmax Representing a maximum number of microtextures; n (N) gmin Representing a minimum microtexture number; h is a g Representing the microtexture depth; h is a gmax Representing a maximum microtexture depth; h is a gmin Representing a minimum microtexture depth; r is (r) c Representing the circumferential land ratio; r is (r) cmax Representing the maximum circumferential land ratio; r is (r) cmin Representing a minimum circumferential land ratio; r is (r) ra Representing the radial slot dam ratio; r is (r) ramax Representing a maximum radial slot dam ratio; r is (r) ramin Representing a minimum radial slot dam ratio;represents the circumferential angular offset; />Representing the maximum circumferential angular offset;representing a minimum circumferential angular offset; psi phi type s Indicating effectiveCoefficient of friction area; psi phi type smax Representing the maximum effective friction area coefficient; psi phi type smin Representing the minimum effective friction area coefficient.
Preferably, the method for performing the optimization comprises:
optimizing the micro-texture parameters of the friction plate to obtain optimized parameters;
based on the optimization parameters, performing optimization on the micro-texture line parameters to obtain an optimization initial value;
and verifying the optimized initial value to obtain the optimal parameter.
Preferably, the method for performing the verification comprises: and substituting the optimized initial value into a single friction plate fluid-solid coupling dynamic model and a high-speed friction belt row torque model to obtain an objective function value, comparing the objective function value obtained by substituting the optimized initial value with a random solution, verifying whether the optimized initial value is a true optimal solution, and outputting an optimal parameter for optimizing the microstructure of the surface of the friction plate.
The application also provides a friction plate surface micro-texture design system of the wet clutch, which comprises: the system comprises a construction module, a design module and an optimization module;
the construction module is used for constructing a friction plate surface microstructure line parameter model of the wet clutch;
the design module is used for obtaining design variables based on the friction plate surface microstructure line parameter model;
and the optimization module optimizes the design variable to obtain the surface micro-texture of the friction plate of the wet clutch.
Preferably, the process of constructing the module includes:
any micro-texture line parameterization representation method based on a curve interpolation method is adopted to obtain a shape line expression;
fitting the shape line expression by adopting a cubic spline interpolation method to obtain a micro-texture shape line expression;
and optimizing the micro-texture line expression to obtain the friction plate surface micro-texture line parameter model.
Preferably, the workflow of the optimization module includes:
optimizing the micro-texture parameters of the friction plate to obtain optimized parameters;
based on the optimization parameters, performing optimization on the micro-texture line parameters to obtain an optimization initial value;
and verifying the optimized initial value to obtain the optimal parameter.
Preferably, the process of performing the verification includes: and substituting the optimized initial value into a single friction plate fluid-solid coupling dynamic model and a high-speed friction belt row torque model to obtain an objective function value, comparing the objective function value obtained by substituting the optimized initial value with a random solution, verifying whether the optimized initial value is a true optimal solution, and outputting an optimal parameter for optimizing the microstructure of the surface of the friction plate.
Compared with the prior art, the application has the following beneficial effects:
1. the absolute value of the rigidity coefficient of the gap flow field of the friction plate of the wet clutch is larger than that of the rigidity coefficient of the optimized front gap flow field, and the fluid elastic force is increased when the friction plate is close to the separation plate, so that the fluid supporting effect is enhanced, and collision contact is not easy to occur;
2. the wet clutch friction plate not only delays the linear speed of high-frequency collision, but also obviously reduces the collision frequency and the collision strength after collision, and then reduces the total band-gap torque value at high speed.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In order that the above-recited objects, features and advantages of the present application will become more readily apparent, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description.
Example 1
As shown in fig. 1, a flow chart of a method of the present embodiment includes the steps of:
s1, constructing a friction plate surface micro-texture line parameter model of the wet clutch.
As shown in FIG. 2, a parameterized representation of arbitrary microstructure lines based on curve interpolation is used, r in FIG. 2 (a) g An outer radius of the friction plate surface micro-texture, theta p (θ p =2π/N g ) A circumferential angle theta corresponding to a periodic structure of the friction plate g Is the corresponding circumference angle of the micro-texture, r in And r out Represents the radial inner diameter and the radial outer diameter of the friction plate, and the ith discrete point p on the micro-texture line i The coordinates in the cylindrical coordinate system of the friction plate surface are (r) i ,θ i ) For the convenience of modeling, each discrete on the shape line is distributed at equal intervals along the radial direction, the radial distance is delta r, and the shape line expression can be given by an interpolation method after the discrete point coordinates are obtained. In this example, a cubic spline interpolation was used to fit the microtextured texture lines. Adopting a three-bending moment construction method to obtain a cubic splineThe interpolation polynomial is as follows:
wherein r is the radial coordinate of the fitted groove-shaped line; r is (r) i And r i+1 The radial coordinates of the ith and the (i+1) th discrete points respectively, and the variation range of r is r i To r i+1 The method comprises the steps of carrying out a first treatment on the surface of the θ is the circumferential coordinate of the fitted groove-shaped line; θ i And theta i+1 Circumferential coordinates of the ith and (i+1) th discrete points respectively, and a variation range of θ is θ i To theta i+1 The method comprises the steps of carrying out a first treatment on the surface of the i is the serial number of the discrete point, and the value of i is preset; m is M i Representing the curve at P i The second derivative value at the point, the bending moment value.
Assuming that the cubic spline curve has a natural boundary condition, namely the second derivative value at the head end and the tail end of the curve is zero, and calculating an M matrix of interpolation points according to a three-bending moment equation:
wherein,,
substituting the discrete point coordinates on the shape line into the formula (3) to obtain a d matrix, substituting the d matrix into the formula (2) to obtain a bending moment value matrix M, and substituting M into the formula (1) to obtain the microstructure shape line function expression of cubic spline interpolation fitting. As shown in FIG. 2 (b), 5 equally spaced discrete points p are employed in the radial direction i (r i ,θ i ) Constructing a micro-textured yarn, wherein i=1 to 4, p 0 And p 4 Respectively seated on the friction plate inner and outer diameters. P in the figure inew Representing the position of the ith discrete point obtained by optimizing, wherein the ith discrete point maintains radial coordinate r in the optimizing process i Unchanged, only make it change a certain angle in the circumferential directionThereby making itObtain the position coordinates (r) inew ,θ inew ). After all the discrete point coordinates are obtained, the expression of the micro-texture line can be obtained through a cubic spline interpolation fitting formula (1). The relation between the optimized discrete point coordinates of the shape line and the original position points is as follows:
due to periodic boundary conditions, discrete points p on the inner diameter 0 The position is set to be unchanged during the optimizing process. Through the optimizing method, the optimizing problem of the micro-texture line is that the micro-texture line is converted into a circumferential offset angle vector of discrete points of the shape lineNumerical optimization problems of (2).
S2, obtaining design variables based on the friction plate surface micro-texture line parameter model.
The optimization design parameters are mainly divided into the following two types:
(1) Friction plate microtexture parameters including: number of microtextures Ng, microtexture depth h g Circumferential groove table ratio r representing circumferential proportion of micro-texture occupied period unit c And a radial groove-to-dam ratio r characterizing the radial ratio of the microtexture to the inner and outer diameters ra ;
(2) Micro-texture line parameters, i.e. the offset angle of four discrete points on a line in the circumferential directionSuch a total of 8 independent parameters are used as optimization design variables, and are expressed as follows:
the constraint conditions of the design parameters are as follows:
g i (X)≤0,i=1~24 (6)
wherein the constraint function g i The definition of (X) includes:
wherein N is g Representing the number of microtextures; n (N) gmax Representing a maximum number of microtextures; n (N) gmin Representing a minimum microtexture number; h is a g Representing the microtexture depth; h is a gmax Representing a maximum microtexture depth; h is a gmin Representing a minimum microtexture depth; r is (r) c Representing the circumferential land ratio; r is (r) cmax Representing the maximum circumferential land ratio; r is (r) cmin Representing a minimum circumferential land ratio; r is (r) ra Representing the radial slot dam ratio; r is (r) ramax Representing a maximum radial slot dam ratio; r is (r) ramin Representing a minimum radial slot dam ratio;represents the circumferential angular offset; />Representing the maximum circumferential angular offset;representing a minimum circumferential angular offset; psi phi type s Representing the effective friction area coefficient; psi phi type smax Representing the maximum effective friction area coefficient; psi phi type smin Representing the minimum effective friction area coefficient.
And S3, optimizing the design variable to obtain the surface micro-texture of the friction plate of the wet clutch.
The optimization parameters shown in the formula (5) are divided into two groups, and the two groups are respectively placed in two stages for optimization. The first stage is the optimization of the friction plate micro-texture parameters to (N) g ,h g ,r c ,r ra ) As a design variable, the micro-texture profile parameters (i.e) All set to 0; the second stage is the optimization of the micro-texture line parameters, by the above-mentioned micro-texture line parameters +.>To design forThe variable, the optimization parameter obtained in the first stage is used as the initial value of the optimization in the stage; and finally, substituting the optimized initial value into a single friction plate fluid-solid coupling dynamic model and a high-speed friction belt row torque model to obtain an objective function value, comparing the objective function value obtained by substituting the initial value with a random solution, verifying whether the optimal solution obtained in the first two stages is a true optimal solution, and outputting the optimal parameter for obtaining the optimization of the microstructure of the friction plate surface.
The specific optimization flow is shown in fig. 3.
The 8 optimization parameters are realized through a parameter optimization design subprogram, the subprogram adopts an optimization design method based on an approximate model, and the specific running process is as follows:
as before, the 8 optimization design variables are divided into two groups, and are respectively placed in two stages to be independently optimized, and each stage can obtain the optimal solution of the selected design variable. The optimization method of each stage is as follows:
1) Firstly, sampling and selecting points by an optimal pull Ding Chao cube method, generating a test design space of 100 groups of sample points, and substituting the test design space into a single friction plate fluid-solid coupling dynamics and a high-speed friction belt-row torque model respectively to obtain a belt-row torque response result under the condition of each parameter group. After the calculated values of the band elimination torque corresponding to all the parameter groups are obtained, the sensitivity analysis is carried out on the variables in the parameter groups, and then the influence of each variable on the band elimination torque can be determined.
2) And then simulating the relation between the input optimization parameters and the output band-gap torque by adopting an elliptic base neural network model, constructing a mathematical model with a calculation result similar to that of the high-speed friction band-gap torque model, but with a greatly reduced calculation amount, and then carrying out search optimization based on the approximate model.
3) And finally searching an optimal solution by adopting a multi-island genetic algorithm, coding individuals optimizing a problem solution space, performing genetic operations such as selection, crossing, mutation and the like on the coded individual population, and iterating out a combination containing the optimal solution from the new population. The parameters of the multi-island genetic algorithm herein are set as follows: the subgroup rule modulus is 10, the island number algebra is 10, the total evolution algebra is 30, the crossover probability is 0.8, the mutation probability is 0.01, the inter-island mobility is 0.2, and the migration interval algebra is 5.
The geometric dimensions of the friction plate, the working condition parameters and the constraint conditions of the design parameters adopted by the optimal design of the embodiment are shown in table 2. The optimal solutions for optimizing the four microtexture parameters and the four shape line parameters of the obtained friction plate are shown in table 1.
TABLE 1
TABLE 2
The results of the comparison of the optimal solution and the random solution verification are shown in table 3. The errors of the elliptic base neural network model used for simulating the relation between the input optimization parameters and the output band-gap torque are shown in the table 4 and the table 5, the errors of the simulated input micro-texture parameters, the input shape line parameters and the elliptic base neural network model responding to the band-gap torque are far smaller than allowable critical values, the correlation coefficient is approximately 1, the allowable value requirement is met, the established approximation model and the sample point data have high fitting degree and fitting precision, and the relation between the test factors and the responses can be reflected well.
TABLE 3 Table 3
TABLE 4 Table 4
TABLE 5
When the surface micro-texture of the friction plate has any irregular boundary, the boundary is difficult to coincide with the grid boundary, and the method for dispersing the flow field by adopting the regular sector grid is difficult to be applied.
As shown in fig. 4, for any surface microtextured line in the cylindrical coordinate system (r, θ), the (r, θ) cylindrical coordinate system shown in fig. 4 (a) is transformed to the (ζ, η) rectangular coordinate system shown in fig. 4 (b) by means of the patch coordinate transformation, and the (ζ, η) coordinate system grids are square grids with intervals of 1. Thus, the irregular calculation area is changed into a regular square grid calculation area, and the discrete calculation by the finite volume method is convenient.
The transformation matrix (jacobian matrix) J transformed from the (r, θ) coordinate system to the (ζ, η) coordinate system is:
the coordinate transformation formula taking pressure as a variable is obtained by a chain law of partial derivatives and is as follows:
wherein the subscript represents the partial derivative with respect to the variable, and thus, the jacobian matrix determinant may be represented as:
|J|=r ξ (rθ η )-r η (rθ ξ ) (10)
the mass flow components in the ζ and η directions are as follows:
wherein,,
from the flow formulaObtaining the flow rate per unit length along the direction of xi and eta:
and writing a lubrication control equation into a vector form, and substituting a coordinate conversion formula taking pressure as a variable and flow expressions in r and theta directions into the equations respectively to obtain the flow in unit length along the directions of xi and eta.
Example two
In this example, the gap flow field characteristics with the optimized friction plate surface microtexture (i.e., optimized grooves) were analyzed by numerical simulation and compared with the friction plate prior to optimization (i.e., radial grooves). FIG. 5 shows graphs of torque simulation and test values of the optimized slot friction plate band across the friction plate line speed under different conditions, and graphs of torque simulation and test values of the radial slot friction plate band across the same conditions are also plotted in the graph for comparison in order to verify the effect of the optimized slot on reducing high speed band across the friction plate line speed.
The four conditions are shown in fig. 5 (a) (b) (c) (d), and the comparison results are shown as follows: the torque values of the optimized groove and the radial groove band row are not greatly different in the low-speed section; however, in the high speed section, the optimized slot friction plate band torque values, while still exhibiting a tendency to increase as the friction plate linear velocity increases, have been significantly reduced compared to the radial slot band torque values. The total band elimination torque value at the highest linear velocity of 108.4m/s is reduced by 63.5% under the working condition of fig. 5 (a), 60.4% under the working condition of fig. 5 (b), 56.0% under the working condition of fig. 5 (c), and 54.3% under the working condition of fig. 5 (d).
In addition, the corresponding linear velocity values of the high-speed rubbing phenomenon before and after optimization under four working conditions are compared with those shown in table 6, the optimized groove can generate stronger dynamic pressure effect due to the flow field, the rigidity coefficient of the flow field is obviously improved compared with that before optimization, the supporting effect on unstable motion of the friction plate is enhanced, the linear velocity of the friction plate corresponding to the high-speed rubbing belt row torque is respectively improved by 53.7% and 49.8%, and the high-speed rubbing phenomenon is obviously retarded.
TABLE 6
Example III
As shown in fig. 6, a system structure diagram of the present embodiment includes: the system comprises a construction module, a design module and an optimization module. The construction module is used for constructing a friction plate surface micro-texture line parameter model of the wet clutch; the design module is used for obtaining design variables based on the friction plate surface micro-texture line parameter model; and the optimization module optimizes the design variable to obtain the surface micro-texture of the friction plate of the wet clutch.
In the following, the present embodiment will be described in detail to solve the technical problems in actual life.
First, a friction plate surface micro-texture line parameter model of the wet clutch is constructed by a construction module.
As shown in fig. 2, a parameterized representation of any micro-texture line based on curve interpolation is used, r in fig. 2 (a) g An outer radius of the friction plate surface micro-texture, theta p (θ p =2π/N g ) A circumferential angle theta corresponding to a periodic structure of the friction plate g Is the corresponding circumference angle of the micro-texture, r in And r out Represents the radial inner diameter and the radial outer diameter of the friction plate, and the ith discrete point p on the micro-texture line i The coordinates in the cylindrical coordinate system of the friction plate surface are (r) i ,θ i ) For the convenience of modeling, each discrete on the shape line is distributed at equal intervals along the radial direction, the radial distance is delta r, and the shape line expression can be given by an interpolation method after the discrete point coordinates are obtained. In this example, a cubic spline interpolation was used to fit the microtextured texture lines. The cubic spline interpolation polynomial is obtained by adopting a three-bending moment construction method as follows:
wherein r is the radial coordinate of the fitted groove-shaped line; r is (r) i And r i+1 The radial coordinates of the ith and the (i+1) th discrete points respectively, and the variation range of r is r i To r i+1 The method comprises the steps of carrying out a first treatment on the surface of the θ is the circumferential coordinate of the fitted groove-shaped line; θ i And theta i+1 Circumferential coordinates of the ith and (i+1) th discrete points respectively, and a variation range of θ is θ i To theta i+1 The method comprises the steps of carrying out a first treatment on the surface of the i is the serial number of the discrete point, and the value of i is preset; m is M i Representing the curve at P i The second derivative value at the point, the bending moment value.
Assuming that the cubic spline curve has a natural boundary condition, namely the second derivative value at the head end and the tail end of the curve is zero, and calculating an M matrix of interpolation points according to a three-bending moment equation:
wherein,,
substituting the discrete point coordinates on the shape line into formula (16) to obtain a d matrix, substituting the d matrix into formula (15) to obtain a bending moment value matrix M, and substituting M into formula (14) to obtain the microstructure shape line function expression of cubic spline interpolation fitting. As shown in FIG. 2 (b), 5 equally spaced discrete points p are employed in the radial direction i (r i ,θ i ) Constructing a micro-textured yarn, wherein i=1 to 4, p 0 And p 4 Respectively seated on the friction plate inner and outer diameters. P in the figure inew Representing the position of the ith discrete point obtained by optimizing, wherein the ith discrete point maintains radial coordinate r in the optimizing process i Unchanged, only make it change a certain angle in the circumferential directionThereby obtaining the position coordinates after optimizing(r inew ,θ inew ). After all the discrete point coordinates are obtained, the expression of the micro-texture line can be obtained through a cubic spline interpolation fitting formula (1). The relation between the optimized discrete point coordinates of the shape line and the original position points is as follows:
due to periodic boundary conditions, discrete points p on the inner diameter 0 The position is set to be unchanged during the optimizing process. Through the optimizing method, the optimizing problem of the micro-texture line is that the micro-texture line is converted into a circumferential offset angle vector of discrete points of the shape lineNumerical optimization problems of (2).
And then, the design module obtains design variables based on the friction plate surface micro-texture line parameter model.
The optimization design parameters are mainly divided into the following two types:
(1) Friction plate microtexture parameters including: number of microtextures Ng, microtexture depth h g Circumferential groove table ratio r representing circumferential proportion of micro-texture occupied period unit c And a radial groove-to-dam ratio r characterizing the radial ratio of the microtexture to the inner and outer diameters ra ;
(2) Micro-texture line parameters, i.e. the offset angle of four discrete points on a line in the circumferential directionSuch a total of 8 independent parameters are used as optimization design variables, and are expressed as follows:
the constraint conditions of the design parameters are as follows:
g i (X)≤0,i=1~24 (19)
wherein the constraint function g i The definition of (X) includes:
wherein N is g Representing the number of microtextures; n (N) gmax Representing a maximum number of microtextures; n (N) gmin Representing a minimum microtexture number; h is a g Representing the microtexture depth; h is a gmax Representing a maximum microtexture depth; h is a gmin Representing a minimum microtexture depth; r is (r) c Representing the circumferential land ratio; r is (r) cmax Representing the maximum circumferential land ratio; r is (r) cmin Representing a minimum circumferential land ratio; r is (r) ra Representing the radial slot dam ratio; r is (r) ramax Representing a maximum radial slot dam ratio; r is (r) ramin Representing a minimum radial slot dam ratio;represents the circumferential angular offset; />Representing the maximum circumferential angular offset;representing a minimum circumferential angular offset; psi phi type s Representing the effective friction area coefficient; psi phi type smax Representing the maximum effective friction area coefficient; psi phi type smin Representing the minimum effective friction area coefficient.
And finally, optimizing the design variable by an optimizing module to obtain the surface micro-texture of the friction plate of the wet clutch.
The optimization parameters shown in the formula (18) are divided into two groups, and the two groups are respectively placed in two stages for optimization. The first stage is the optimization of the friction plate micro-texture parameters to (N) g ,h g ,r c ,r ra ) As a design variable, the micro-texture profile parameters (i.e) All set to 0; the second stage is the optimization of the micro-texture line parameters, by the above-mentioned micro-texture line parameters +.>As a design variable, the optimization parameter obtained in the first stage is used as an initial optimization value in the stage; and finally, substituting the optimized initial value into a single friction plate fluid-solid coupling dynamic model and a high-speed friction belt row torque model to obtain an objective function value, comparing the objective function value obtained by substituting the initial value with a random solution, verifying whether the optimal solution obtained in the first two stages is a true optimal solution, and outputting the optimal parameter for obtaining the optimization of the microstructure of the friction plate surface.
The specific optimization flow is shown in fig. 3.
The 8 optimization parameters are realized through a parameter optimization design subprogram, the subprogram adopts an optimization design method based on an approximate model, and the specific running process is as follows:
as before, the 8 optimization design variables are divided into two groups, and are respectively placed in two stages to be independently optimized, and each stage can obtain the optimal solution of the selected design variable. The optimization method of each stage is as follows:
1) Firstly, sampling and selecting points by an optimal pull Ding Chao cube method, generating a test design space of 100 groups of sample points, and substituting the test design space into a single friction plate fluid-solid coupling dynamics and a high-speed friction belt-row torque model respectively to obtain a belt-row torque response result under the condition of each parameter group. After the calculated values of the band elimination torque corresponding to all the parameter groups are obtained, the sensitivity analysis is carried out on the variables in the parameter groups, and then the influence of each variable on the band elimination torque can be determined.
2) And then simulating the relation between the input optimization parameters and the output band-gap torque by adopting an elliptic base neural network model, constructing a mathematical model with a calculation result similar to that of the high-speed friction band-gap torque model, but with a greatly reduced calculation amount, and then carrying out search optimization based on the approximate model.
3) And finally searching an optimal solution by adopting a multi-island genetic algorithm, coding individuals optimizing a problem solution space, performing genetic operations such as selection, crossing, mutation and the like on the coded individual population, and iterating out a combination containing the optimal solution from the new population. The parameters of the multi-island genetic algorithm herein are set as follows: the subgroup rule modulus is 10, the island number algebra is 10, the total evolution algebra is 30, the crossover probability is 0.8, the mutation probability is 0.01, the inter-island mobility is 0.2, and the migration interval algebra is 5.
The geometric dimensions of the friction plate, the working condition parameters and the constraint conditions of the design parameters adopted by the optimal design of the embodiment are shown in table 2. The optimal solutions for optimizing the four microtexture parameters and the four shape line parameters of the obtained friction plate are shown in table 1.
The results of the comparison of the optimal solution and the random solution verification are shown in table 3. The errors of the elliptic base neural network model used for simulating the relation between the input optimization parameters and the output band-gap torque are shown in the table 4 and the table 5, the errors of the simulated input micro-texture parameters, the input shape line parameters and the elliptic base neural network model responding to the band-gap torque are far smaller than allowable critical values, the correlation coefficient is approximately 1, the allowable value requirement is met, the established approximation model and the sample point data have high fitting degree and fitting precision, and the relation between the test factors and the responses can be reflected well.
When the surface micro-texture of the friction plate has any irregular boundary, the boundary is difficult to coincide with the grid boundary, and the method for dispersing the flow field by adopting the regular sector grid is difficult to be applied.
As shown in fig. 4, for any surface microtextured line in the cylindrical coordinate system (r, θ), the (r, θ) cylindrical coordinate system shown in fig. 4 (a) is transformed to the (ζ, η) rectangular coordinate system shown in fig. 4 (b) by means of the patch coordinate transformation, and the (ζ, η) coordinate system grids are square grids with intervals of 1. Thus, the irregular calculation area is changed into a regular square grid calculation area, and the discrete calculation by the finite volume method is convenient.
The transformation matrix (jacobian matrix) J transformed from the (r, θ) coordinate system to the (ζ, η) coordinate system is:
the coordinate transformation formula taking pressure as a variable is obtained by a chain law of partial derivatives and is as follows:
wherein the subscript represents the partial derivative with respect to the variable, and thus, the jacobian matrix determinant may be represented as:
|J|=r ξ (rθ η )-r η (rθ ξ ) (23)
the mass flow components in the ζ and η directions are as follows:
wherein,,
from the flow formulaObtaining the flow rate per unit length along the direction of xi and eta:
and writing a lubrication control equation into a vector form, and substituting a coordinate conversion formula taking pressure as a variable and flow expressions in r and theta directions into the equations respectively to obtain the flow in unit length along the directions of xi and eta.
The above embodiments are merely illustrative of the preferred embodiments of the present application, and the scope of the present application is not limited thereto, but various modifications and improvements made by those skilled in the art to which the present application pertains are made without departing from the spirit of the present application, and all modifications and improvements fall within the scope of the present application as defined in the appended claims.