Design method of speed reducer lubricating system

Abstract

The invention discloses a design method of a speed reducer lubrication system, and belongs to the technical field of passive speed reducer lubrication. According to design parameters and a geometric model of a target speed reducer, a lubrication response surface model and an initial flow field model are constructed, and based on the lubrication response surface model and the initial flow field model, the speed reducer lubrication system is designed. The optimal lubricating system design scheme enabling the lubricating ratio of the target speed reducer to be maximum and the oil stirring loss to be minimum under the multiple working rotating speeds is determined, the lubricating flow field structure of the target speed reducer can be reasonably adjusted, the lubricating ratio is improved, the oil stirring loss is reduced, and the problems that an existing speed reducer shell lubricating system is unreasonable in design and poor in reliability are solved. And the lubrication of the gear train structure is insufficient.

Description

Technical Field

[0001] The invention relates to a design method of a reducer lubrication system and belongs to the technical field of passive reducer lubrication. Background Art

[0002] During the operation of the reducer, the meshing friction of the gears and the rolling friction of the bearings generate a large amount of heat, causing the temperature to rise rapidly. Excessive temperature can cause damage to the gears and bearings. Therefore, oil lubrication is required to reduce friction and heat generation. At the same time, the lubricating oil can also remove some of the heat and play a cooling role. Common lubrication methods are active lubrication and passive lubrication. Active lubrication requires the participation of components such as oil pumps, oil coolers, and oil filters. It has higher cooling efficiency, but also higher costs. Passive lubrication mainly uses the oil stirred up by the rotation of the gears and splashed onto the inner wall of the housing. Reasonable design of the oil storage and oil guide structure allows the oil to flow into the parts that need lubrication. It has a simple structure and low cost.

[0003] A large number of reducer experts at home and abroad have studied the causes of reducer failure. There are many reasons for reducer failure, such as analyzing the failure from the perspective of reducer fatigue from the perspective of gear material, gear micro-modification, bearing strength, gear shaft arrangement, synchronizer structural material, etc. Few people have conducted research on the reducer lubrication system. In fact, some common failures in reducers are often not caused by insufficient materials, strength or rigidity of the parts themselves, but by poor lubrication. The main potential failure mode of the reducer lubrication system is that some areas of the reducer are not lubricated properly, resulting in too high oil temperature, and bonding and fracture of gears, bearings, synchronizers and other components; the main cause of failure is unreasonable design of the housing lubrication system and unreasonable selection of lubrication system parameters. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a design method for a reducer lubrication system, which can reasonably adjust the lubrication flow field structure of the target reducer, improve the lubrication ratio and reduce the oil stirring loss, and solve the problems of unreasonable design of the current reducer housing lubrication system and insufficient lubrication of the gear train structure.

[0005] In order to solve the above technical problems, the present invention is implemented by adopting the following technical solutions: The present invention provides a design method for a reducer lubrication system, comprising: Obtain the design parameters and geometric model of the target reducer, and construct the lubrication response surface model and initial flow field model; Based on the lubrication response surface model and the initial flow field model, the optimal lubrication system design scheme is determined to maximize the lubrication ratio and minimize the oil churning loss of the target reducer at multiple operating speeds. According to the optimal lubrication system design scheme, the lubrication system of the target reducer is obtained.

[0006] Furthermore, the design parameters include: reducer speed, lubricating oil quantity and lubricating oil viscosity.

[0007] Furthermore, the lubrication response surface model is expressed as: ; in: represents the lubrication response surface model; Indicates the reducer i design parameters, Indicates the reducer j design parameters, i < j , n Indicates the number of design parameters; represents the constant term, express The corresponding linear term model coefficients, express The corresponding quadratic model coefficients, express The corresponding interaction model coefficients.

[0008] Furthermore, the method for constructing the initial flow field model includes: discretizing a geometric model of the target reducer to construct the initial flow field model.

[0009] Furthermore, the optimal lubrication system design scheme for maximizing the lubrication ratio and minimizing the oil churning loss of the target reducer at multiple operating speeds is determined based on the lubrication response surface model and the initial flow field model, including: The smooth particle hydrodynamics algorithm is used to map the design parameters to the initial flow field model to generate the corresponding particle flow field model; Construct the objective function; Based on the objective function and particle flow field model, the target design parameters of the target reducer are determined to maximize the lubrication ratio and minimize the oil churning loss at multiple operating speeds. Based on the target design parameters, the optimal model coefficients and flow field optimization model are determined to make the lubrication response surface model meet the lubrication and churning loss indicators; According to the optimal model coefficient and flow field optimization model, the optimal lubrication system design scheme is obtained.

[0010] Furthermore, constructing the objective function includes: The objective function is expressed as: ; in: represents the objective function of maximizing the lubrication ratio, Indicates the reducer i design parameters,n Indicates the number of reducer design parameters; The lubrication ratio is expressed as: ; Indicates the lubrication ratio, represents the wetted wall area, Represents the surface area of the parts to be lubricated in the reducer. The lubrication ratio is proportional to the wetted wall area. The maximum lubrication ratio is equivalent to the maximum wetted wall area. represents the function for finding the wetted wall area, Indicates the maximum value of the wetted wall area; represents the objective function of minimizing churning loss; represents the function for finding the churning loss, Indicates the minimum value of churning loss.

[0011] Furthermore, the target design parameters for maximizing the lubrication ratio and minimizing the oil churning loss of the target reducer at multiple operating speeds are determined based on the objective function and the particle flow field model, including: The wetted wall area equivalent to the lubrication ratio is calculated using the following formula: ; in: represents the wetted wall area; represents a smooth function, ; represents the smooth length, ; Represents the empirical coefficient, and its value range is ; represents the interparticle distance, Indicates the i The position of the particle, Indicates the geometric position of the wall; Expressed as a natural constant e is the exponential function of the base; represents the spatial dimension of the objective function; Indicates the i The contribution of each particle to the wetted wall area is ; Indicates the i The mass of the particle, Indicates the i The density of particles; The smooth particle that maximizes the wetted wall area is taken as the optimal particle, and multiple design parameters corresponding to the optimal particle are output; The multiple design parameters corresponding to the optimal particles are used as target design parameters.

[0012] Furthermore, the determination of the optimal model coefficients and flow field optimization model that enable the lubrication response surface model to satisfy the lubrication and churning loss indicators based on the target design parameters includes: According to the target design parameters, the lubrication response surface model graphical curve is fitted; In the process of fitting the graph curve of the lubrication response surface model, the points in the initial flow field model that are not fully lubricated are determined; Based on the insufficiently lubricated points, the lubrication conditions of the points are optimized to obtain the initial flow field approximate model; Based on the initial flow field approximation model, a lubrication response surface model graph curve is fitted and the lubrication conditions of the points are continuously optimized according to the number of insufficiently lubricated points until the lubrication response surface model graph curve is fully fitted; The model coefficients of the lubrication response surface model that completely fits the graphical curve are taken as the optimal model coefficients; The initial flow field approximate model without insufficient lubrication points is used as the flow field optimization model.

[0013] Furthermore, the step of optimizing the lubrication conditions of the points based on the insufficiently lubricated points to obtain an initial flow field approximation model includes: If there are points that are not fully lubricated, oil grooves, oil holes or oil guide ribs are opened on the lubricating oil path to fully lubricate the points; where full lubrication of the points means that the lubrication ratio of the points meets the preset value.

[0014] Furthermore, the reduction ratio of the oil churning loss of the flow field optimization model is not less than 10% of the initial flow field model.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention constructs a lubrication response surface model and an initial flow field model based on multiple design parameters and geometric models of the target reducer, and based on the lubrication response surface model and the initial flow field model, determines the optimal lubrication system design scheme that maximizes the lubrication ratio and minimizes the oil churning loss of the target reducer at multiple operating speeds. It can reasonably adjust the lubrication flow field structure of the target reducer, improve the lubrication ratio and reduce the oil churning loss, and solve the problems of unreasonable design of the current reducer housing lubrication system and insufficient lubrication of the gear train structure.

[0016] 2. The present invention uses a smooth particle fluid dynamics algorithm to map the design parameters to the initial flow field model, establishes a corresponding particle flow field model, takes the smooth particle that maximizes the wetted wall area as the optimal particle, and outputs multiple design parameters corresponding to the optimal particle; the multiple design parameters corresponding to the optimal particle are used as target design parameters, and the optimal solution for the wetted wall area and oil stirring loss under various operating speed conditions is effectively found. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of a design method for a reducer lubrication system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Example

[0019] like Figure 1 As shown, a design method for a reducer lubrication system includes: Obtaining the design parameters and geometric model of the target reducer, and constructing a lubrication response surface model and an initial flow field model. In this embodiment, the design parameters of the target reducer include the reducer speed, lubricating oil quantity, and lubricating oil viscosity; Based on the lubrication response surface model and the initial flow field model, the optimal lubrication system design scheme that maximizes the lubrication ratio and minimizes the oil churning loss of the target reducer at multiple operating speeds is determined. Specifically: Discretize the geometric model of the target reducer and construct the initial flow field model; The smooth particle hydrodynamics algorithm is used to map the design parameters to the initial flow field model to generate the corresponding particle flow field model; Construct the objective function, which is expressed as: ; in: represents the objective function of maximizing the lubrication ratio, Indicates the reducer i design parameters, n Indicates the number of reducer design parameters; The lubrication ratio is expressed as: ; Indicates the lubrication ratio, represents the wetted wall area, Represents the surface area of the parts to be lubricated in the reducer. The lubrication ratio is proportional to the wetted wall area. The maximum lubrication ratio is equivalent to the maximum wetted wall area. represents the function for finding the wetted wall area, Indicates the maximum value of the wetted wall area; represents the objective function of minimizing churning loss; represents the function for finding the churning loss, Indicates the minimum value of churning loss.

[0020] Based on the objective function and particle flow field model, the target design parameters that maximize the lubrication ratio and minimize the oil churning loss of the target reducer at multiple operating speeds are determined, including: The wetted wall area equivalent to the lubrication ratio is calculated using the following formula: ; in: represents the wetted wall area;

[0021] The smooth particle that maximizes the wetted wall area is selected as the optimal particle, and multiple design parameters corresponding to the optimal particle are output. By using the design parameters corresponding to the optimal particle as the target design parameters, the optimal solution of the wetted wall area and oil churning loss under various operating speed conditions is found. This can reasonably adjust the lubrication flow field structure of the target reducer, improve the lubrication ratio and reduce the oil churning loss.

[0022] Based on the target design parameters, the optimal model coefficients and flow field optimization model are determined to ensure that the lubrication response surface model meets the lubrication and churning loss indicators, including: According to the target design parameters, the lubrication response surface model graphical curve is fitted; In the process of fitting the graph curve of the lubrication response surface model, the points in the initial flow field model that are not fully lubricated are determined; Based on the insufficiently lubricated points, the lubrication conditions of the points are optimized to obtain the initial flow field approximate model; Based on the initial flow field approximation model, the lubrication response surface model graph curve is fitted and the lubrication conditions of the points are continuously optimized according to the number of insufficiently lubricated points until the lubrication response surface model graph curve is fully fitted. The lubrication response surface model is expressed as: ; in: represents the lubrication response surface model; Indicates the i The design parameters of each reducer, Indicates the j The reducer design parameters, i < j , n Indicates the number of design parameters; represents the constant term, express The corresponding linear term model coefficients, express The corresponding quadratic model coefficients, express The corresponding interaction model coefficients; The model coefficients of the lubrication response surface model that completely fits the graphical curve are taken as the optimal model coefficients, and the initial flow field approximate model without insufficiently lubricated points is taken as the flow field optimization model.

[0023] Example 2 like Figure 1 As shown, a design method for a reducer lubrication system includes: Obtaining the design parameters and geometric model of the target reducer, and constructing a lubrication response surface model and an initial flow field model. In this embodiment, the design parameters of the target reducer include the reducer speed, lubricating oil quantity, and lubricating oil viscosity; Based on the lubrication response surface model and the initial flow field model, the optimal lubrication system design scheme that maximizes the lubrication ratio and minimizes the oil churning loss of the target reducer at multiple operating speeds is determined. Specifically: Discretize the geometric model of the target reducer and construct the initial flow field model; The smooth particle hydrodynamics algorithm is used to map the design parameters to the initial flow field model to generate the corresponding particle flow field model; Construct the objective function, which is expressed as: ; in: represents the objective function of maximizing the lubrication ratio, Indicates the reducer i design parameters, n Indicates the number of reducer design parameters; The lubrication ratio is expressed as: ; Indicates the lubrication ratio, represents the wetted wall area, Represents the surface area of the parts to be lubricated in the reducer. The lubrication ratio is proportional to the wetted wall area. The maximum lubrication ratio is equivalent to the maximum wetted wall area. represents the function for finding the wetted wall area, Indicates the maximum value of the wetted wall area; represents the objective function of minimizing churning loss; represents the function for finding the churning loss, Indicates the minimum value of churning loss.

[0024] Based on the objective function and particle flow field model, the target design parameters that maximize the lubrication ratio and minimize the oil churning loss of the target reducer at multiple operating speeds are determined, including: The wetted wall area equivalent to the lubrication ratio is calculated using the following formula: ; in: represents the wetted wall area; represents a smooth function, ; represents the smooth length, ; Represents the empirical coefficient, and its value range is ; represents the interparticle distance; Indicates the i The position of the particle, Indicates the geometric position of the wall; Expressed as a natural constant e is the exponential function of the base; represents the spatial dimension of the objective function; Indicates the i The contribution of each particle to the wetted wall area is ; Indicates the i The mass of the particle, Indicates the i The density of particles; The smooth particle that maximizes the wetted wall area is selected as the optimal particle, and multiple design parameters corresponding to the optimal particle are output. By using the design parameters corresponding to the optimal particle as the target design parameters, the optimal solutions for the wetted wall area and oil stirring loss under various operating speed conditions are effectively found.

[0025] Based on the target design parameters, the optimal model coefficients and flow field optimization model are determined to ensure that the lubrication response surface model meets the lubrication and churning loss indicators, including: According to the target design parameters, the lubrication response surface model graphical curve is fitted; In the process of fitting the graph curve of the lubrication response surface model, the points in the initial flow field model that are not fully lubricated are determined; Based on insufficiently lubricated points, the lubrication conditions of the points are optimized to obtain an initial flow field approximation model. It should be noted that if there are insufficiently lubricated points, oil grooves, oil holes, or oil guide ribs are opened in the lubricating oil path to ensure that the points are fully lubricated. Full lubrication of the points is indicated by the lubrication ratio of the points meeting the preset value. Based on the initial flow field approximation model, a lubrication response surface model graph curve is fitted and the lubrication conditions of the points are continuously optimized according to the number of insufficiently lubricated points until the lubrication response surface model graph curve is fully fitted; The model coefficients of the lubrication response surface model that completely fits the graphical curve are taken as the optimal model coefficients, and the initial flow field approximate model without insufficiently lubricated points is taken as the flow field optimization model; In this embodiment, the reduction ratio of the oil churning loss in the flow field optimization model is not less than 10% of that in the initial flow field model. The oil churning loss is the power loss caused by the reducer gears overcoming the fluid resistance of the lubricating oil, which is mainly represented by the transmission efficiency: ; Indicates transmission efficiency, P indicates oil stirring power loss, It represents the input power of the transmission system. The oil churning power loss is inversely proportional to the transmission efficiency. The smaller the oil churning loss, the higher the transmission efficiency. Therefore, the reduction ratio of oil churning loss is equivalently reflected by the transmission efficiency. The lubrication response surface model is expressed as: ; in: represents the lubrication response surface model; Indicates the i The design parameters of each reducer, Indicates the j The reducer design parameters, i < j , n Indicates the number of design parameters;

[0026] The optimal lubrication system design scheme is determined based on the optimal model coefficient and the flow field optimization model. The lubrication system of the target reducer is obtained from the optimal lubrication system design scheme. Under the premise of comprehensive consideration of lubrication and oil churning losses, the principle of minimizing the oil resistance along the tangential direction of the gear is followed. Oil grooves, oil holes or oil guide ribs are opened at the points on the lubricating oil path that are not fully lubricated to ensure that these points are fully lubricated, and the design of the lubricating oil path is reasonably optimized. In order to illustrate the effectiveness of the results of the method proposed in this embodiment, the design parameters include: reducer speed A, lubricating oil amount B and lubricating oil viscosity C; The speed of the reducer A is 1500rpm, 6750rpm and 12000rpm; The values of lubricating oil quantity B are 1.4L, 1.7L and 2L; The viscosity C of lubricating oil is 、 and ; The following indicators are used for verification: F value( F-statistic ), used to test the significance of the regression model, ; p value( p-value ), usually calculated automatically by statistical software such as (Minitab, Design-Expert, SPSS, etc.); in, represents the regression mean square, represents the residual mean square; ; represents the regression sum of squares, ; M represents the number of trials, Indicates the m The output of the lubrication response surface model for the experiment is, express M Average wetted wall area or churning oil loss in each test; represents the total number of model coefficients and constant terms in the lubrication response surface model; ; represents the residual sum of squares, ; No. m The wetted wall area of the first test or the m Churning loss in the test;

[0027] Table 1 Test data

[0028] Based on the data shown in Table 1, the lubrication response surface model can be calculated. F The value is 35.05, p The value is less than 0.0001, and the sliding response surface model of the proposed method in this example is established; The method proposed in this embodiment is at a rotation speed of 1500 rpm, the amount of lubricating oil is selected to be 2L, and the viscosity of the lubricating oil is selected to be , the oil stirring power loss is the smallest, the wet wall area is the largest, the oil stirring power loss is 98.5w, and the wet wall area accounts for 78.7%; At a speed of 6750rpm, the lubricating oil volume is selected as 1.85L, and the lubricating oil viscosity is selected as , the oil stirring power loss is the smallest, the wet wall area is the largest, the oil stirring power loss is 484.8w, and the wet wall area accounts for 81.1%; At a speed of 12000rpm, the lubricating oil volume is selected as 1.61L, and the lubricating oil viscosity is selected as , the oil stirring power loss is the smallest, the wet wall area is the largest, the oil stirring power loss is 867.6w, and the wet wall area accounts for 69.6%.

[0029] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The present application is described with reference to the flowcharts of the methods according to the embodiments of the present application. It should be understood that each process in the flowchart can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate the instructions for implementing the process in the flowchart. Figure 1 a process or multiple processes or boxes Figure 1 a device that performs the functions specified in a block or multiple blocks; These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A function specified in a process or multiple processes.

[0030] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 The steps of a specified function in a process or multiple processes.

[0031] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which are all protected by the present invention.

Claims

1. A design method for a reducer lubrication system, characterized in that: include: Obtain the design parameters and geometric model of the target reducer, and construct the lubrication response surface model and initial flow field model; Based on the lubrication response surface model and the initial flow field model, the optimal lubrication system design scheme is determined to maximize the lubrication ratio and minimize the oil churning loss of the target reducer at multiple operating speeds. According to the optimal lubrication system design scheme, the lubrication system of the target reducer is obtained.

2. The design method of the reducer lubrication system according to claim 1, characterized in that: Design parameters include: reducer speed, lubricating oil quantity and lubricating oil viscosity.

3. The design method of the reducer lubrication system according to claim 2, characterized in that: The lubrication response surface model is expressed as: ； in: represents the lubrication response surface model; Indicates the i The design parameters of each reducer, Indicates the reducer j design parameters, i < j , n Indicates the number of design parameters; represents the constant term, express The corresponding linear term model coefficients, express The corresponding quadratic model coefficients, express The corresponding interaction model coefficients.

4. The design method of the reducer lubrication system according to claim 2, characterized in that: The method for constructing the initial flow field model includes: discretizing a geometric model of a target reducer and constructing the initial flow field model.

5. The design method of the reducer lubrication system according to claim 4, characterized in that: The optimal lubrication system design scheme for maximizing the lubrication ratio and minimizing the oil churning loss of the target reducer at multiple operating speeds based on the lubrication response surface model and the initial flow field model includes: The smooth particle hydrodynamics algorithm is used to map multiple design parameters to the initial flow field model to generate the corresponding particle flow field model; Construct the objective function; Based on the objective function and particle flow field model, the target design parameters of the target reducer are determined to maximize the lubrication ratio and minimize the oil churning loss at multiple operating speeds. Based on the target design parameters, the optimal model coefficients and flow field optimization model are determined to make the lubrication response surface model meet the lubrication and churning loss indicators; According to the optimal model coefficient and flow field optimization model, the optimal lubrication system design scheme is obtained.

6. The design method of the reducer lubrication system according to claim 5, characterized in that: The constructing of the objective function comprises: The objective function is expressed as: ； in: represents the objective function of maximizing the lubrication ratio, Indicates the reducer i design parameters, n Indicates the number of reducer design parameters; The lubrication ratio is expressed as: ; Indicates the lubrication ratio, represents the wetted wall area, Represents the surface area of the parts to be lubricated in the reducer. The lubrication ratio is proportional to the wetted wall area. The maximum lubrication ratio is equivalent to the maximum wetted wall area. represents the function for finding the wetted wall area, Indicates the maximum value of the wetted wall area; represents the objective function of minimizing churning loss; represents the function for finding the churning loss, Indicates the minimum value of churning loss.

7. The design method of the reducer lubrication system according to claim 5, characterized in that: The target design parameters for maximizing the lubrication ratio and minimizing the oil churning loss of the target reducer at multiple operating speeds are determined based on the objective function and the particle flow field model, including: The wetted wall area equivalent to the lubrication ratio is calculated using the following formula: ； in: represents the wetted wall area; represents a smooth function, ; represents the smooth length, ; Represents the empirical coefficient, and its value range is ; represents the interparticle distance, Indicates the i The position of the particle, Indicates the geometric position of the wall; Expressed as a natural constant e is the exponential function of the base; represents the spatial dimension of the objective function; Indicates the i The contribution of each particle to the wetted wall area is ; Indicates the i The mass of the particle, Indicates the i The density of particles; The smooth particle that maximizes the wetted wall area is taken as the optimal particle, and multiple design parameters corresponding to the optimal particle are output; The multiple design parameters corresponding to the optimal particles are used as target design parameters.

8. The design method of the reducer lubrication system according to claim 5, characterized in that: The method of determining the optimal model coefficients and flow field optimization model that enable the lubrication response surface model to meet lubrication and oil churning loss indicators based on the target design parameters includes: According to the target design parameters, the lubrication response surface model graphical curve is fitted; In the process of fitting the graph curve of the lubrication response surface model, the points in the initial flow field model that are not fully lubricated are determined; Based on the insufficiently lubricated points, the lubrication conditions of the points are optimized to obtain the initial flow field approximate model; Based on the initial flow field approximation model, a lubrication response surface model graph curve is fitted and the lubrication conditions of the points are continuously optimized according to the number of insufficiently lubricated points until the lubrication response surface model graph curve is fully fitted; The model coefficients of the lubrication response surface model that completely fits the graphical curve are taken as the optimal model coefficients; The initial flow field approximate model without insufficient lubrication points is used as the flow field optimization model.

9. The design method of the reducer lubrication system according to claim 8, characterized in that: The method of optimizing the lubrication conditions of the points based on insufficient lubrication to obtain an initial flow field approximate model includes: If there are points that are not fully lubricated, oil grooves, oil holes or oil guide ribs are opened on the lubricating oil path to fully lubricate the points; where full lubrication of the points means that the lubrication ratio of the points meets the preset value.

10. The design method of the reducer lubrication system according to claim 5, characterized in that: The reduction ratio of the oil churning loss of the flow field optimization model is not less than 10% of the initial flow field model.

Images