A plastic gear steady-state meshing temperature field calculation method based on an intelligent iterative algorithm

Abstract

This invention discloses a method for calculating the steady-state meshing temperature field of plastic gears based on an intelligent iterative algorithm, comprising the following steps: 1) determining the operating conditions of the plastic gear meshing, including speed, torque, ambient temperature, and initial gear temperature, and converting these operating conditions into boundary conditions required for finite element analysis; 2) calculating the steady-state meshing heat flux of the gear under the operating conditions determined in step 1) based on the intelligent iterative algorithm; 3) using the steady-state meshing heat flux obtained in step 2) as a heat load, and simulating the steady-state meshing temperature field of the plastic gear using a finite element steady-state thermal analysis algorithm. This invention can intuitively obtain the steady-state meshing temperature field distribution of plastic gears during actual stable meshing, while avoiding the high equipment and time costs associated with actual product testing, thus shortening the development cycle of plastic gear products.

Description

Technical Field

[0001] This invention relates to the field of computer simulation technology, and specifically to a method for calculating the steady-state meshing temperature field of plastic gears based on an intelligent iterative algorithm. Background Technology

[0002] Plastic gears have been increasingly widely used in production in recent years due to their advantages such as low noise, lightweight, easy maintenance and self-lubrication.

[0003] However, during actual meshing, plastic gears generate not only frictional heat due to tooth surface contact and relative sliding, but also viscoelastic hysteresis loss heat due to the viscoelastic hysteresis loss characteristics of the plastic itself. Because plastic has poor thermal conductivity, during stable meshing (i.e., when the temperature field of the plastic gear reaches a steady state), the plastic teeth will exhibit localized high temperatures. Since the mechanical properties of plastic are significantly temperature-sensitive, this will lead to localized softening of the teeth under stable meshing conditions, significantly reducing their load-bearing capacity. Furthermore, since the localized temperature rise zone usually occurs in the tooth surface contact area, rapid wear of the plastic gear tooth surface will also occur under stable meshing conditions.

[0004] To evaluate the performance of plastic gears during stable meshing, it is first necessary to calculate the temperature field of the plastic gears under stable meshing conditions, i.e., the steady-state meshing temperature field of the plastic gears.

[0005] Therefore, there is an urgent need to develop a calculation method that can accurately and efficiently predict the steady-state meshing temperature field of plastic gears. Summary of the Invention

[0006] The purpose of this invention is to provide a method for calculating the steady-state meshing temperature field of plastic gears based on an intelligent iterative algorithm, so as to solve the problems existing in the prior art.

[0007] The technical solution adopted to achieve the purpose of this invention is as follows: a method for calculating the steady-state meshing temperature field of plastic gears based on an intelligent iterative algorithm, comprising the following steps:

[0008] 1) Determine the operating conditions for the meshing of plastic gears. The operating conditions include speed, torque, ambient temperature and initial gear temperature. The operating conditions are converted into boundary conditions for finite element analysis.

[0009] 2) Based on the intelligent iterative algorithm, calculate the steady-state meshing heat flow of the gear under the working conditions determined in step 1).

[0010] 3) Using the steady-state meshing heat flow obtained in step 2) as the heat load, the steady-state meshing temperature field of the plastic gear is simulated and calculated using the finite element steady-state thermal analysis algorithm.

[0011] Furthermore, step 2) includes the following sub-steps:

[0012] 2.1) Based on specific iterative criteria, calculate the meshing heat flux distribution for different meshing cycles until the meshing heat flux distribution is determined to be stable. Specifically:

[0013] Define the current meshing cycle number as j, the reference meshing cycle number as k, and the iteration interval as N, all initially set to 1. Based on the differences between the current cycle and the reference cycle, subsequent steps are divided into two cases: step A) and step B).

[0014] A) The current period is the reference period, i.e., j = k:

[0015] A1) Based on the boundary conditions of the finite element analysis calculated from the working conditions of the plastic gear meshing, the finite element structural analysis of the plastic gear meshing process in the reference meshing period k is performed. The history of the change of normal contact force and relative slip velocity at each node on the meshing contact surface of the plastic gear in the current meshing period, as well as the history of the change of principal strain at each element integration point in the reference period k are output.

[0016] A2) Scripts written in Python are used to calculate the heat generation power at the contact tooth surface nodes. The heat generation power at the contact tooth surface nodes is calculated using equation (1).

[0017]

[0018] In the formula, q f,nl Q represents the heat generation power at the contact tooth surface node. f,nl F represents the accumulated frictional heat at the contact tooth node during one meshing cycle. t is the duration of contact engagement at the node in each meshing cycle. β is the proportionality coefficient of frictional heat distribution between the contact surfaces, calculated by equation (2). μ is the coefficient of friction. contact v represents the instantaneous normal contact force at the node. slip The instantaneous relative slip velocity at the node.

[0019]

[0020] Where: subscripts 1 and 2 represent the tooth surfaces of the driving gear and the driven gear, respectively. β1 + β2 = 1. λ is the thermal conductivity. c is the specific heat capacity. ρ is the density. v r Let be the linear velocity at the base circle.

[0021] A3) Using a script written in Python, and combining the unit principal strain history output in step A1), calculate the heat generation power density within each grid cell. The heat generation power density at the integration point of each grid cell is calculated using equation (3).

[0022] qh,ip =ξ h,ip / t (3)

[0023] In the formula, q h,ip The heat generation power density at each grid cell integration point during one meshing cycle. ξ h,ip The viscoelastic hysteresis loss heat density accumulated at each meshing point in each meshing cycle.

[0024] A4) Calculate the meshing heat flow distribution state parameters for the reference period k.

[0025] A5) Calculate the three-dimensional temperature field at the end of the current period j based on the meshing heat flow of the reference period k.

[0026] A6) Calculate the rate of change Δ of the meshing heat flux distribution state parameters of the reference period k compared to the previous reference period kN.

[0027] A7) If Δ ≥ 5%, the iteration interval N = 1. If Δ < 5%, the iteration interval increases, N = N + 1.

[0028] A8) If the updated iteration interval N = 10, it is determined that the distribution of meshing heat flux has stabilized, and the process proceeds to step 2.2). If the updated iteration interval N < 10, it is determined that the distribution of meshing heat flux has not stabilized, and the process continues to step A9).

[0029] A9) Update the current meshing cycle j = j + 1. If j = k + N at this point, the reference meshing cycle k = k + N also needs to be updated. Based on the differences between the updated current meshing cycle and the reference meshing cycle, reselect either step A) or step B).

[0030] B) The current engagement cycle is not the reference cycle, i.e., j ≠ k:

[0031] B1) Calculate the three-dimensional temperature field at the end of the current period j based on the meshing heat flow of the reference period k.

[0032] B2) If the updated iteration interval N = 10, it is determined that the distribution of meshing heat flux has stabilized, and the process proceeds to step 2.2). If the updated iteration interval N < 10, it is determined that the distribution of meshing heat flux has not stabilized, and the process continues to step B3).

[0033] B3) Update the current meshing cycle j = j + 1. If j = k + N at this point, the reference meshing cycle k = k + N also needs to be updated. Based on the differences between the updated current meshing cycle and the reference meshing cycle, reselect either step A) or step B).

[0034] 2.2) Treat the meshing heat flow of the current reference meshing period k as the steady-state meshing heat flow and output the steady-state meshing heat flow.

[0035] Further, in step A3), the principal strain history at each grid element integration point during one meshing cycle is extracted from the analysis results. A Fourier transform is performed to obtain a series of sinusoidal strain curves. The amplitude of each sinusoidal strain component at each grid element integration point is substituted into equation (4) to calculate ξ. h,ip .

[0036]

[0037] In the formula, δ represents the total modulus of the plastic under specific temperature and strain rate conditions. i It is the viscoelastic loss angle of plastic under specific temperature and strain rate conditions. ω i Let ε be the angular frequency of the i-th sinusoidal strain component. i Let be the amplitude of the i-th sinusoidal strain component.

[0038] Furthermore, in step A4), the calculation method for the distribution state parameters of the meshing heat flux is as follows:

[0039] Given the frictional heat generation power q at the node calculated in steps A2) and A3). f,nl and the viscoelastic hysteresis loss power density q at the integration point of the grid cell h,ip A Python script was written to read the coordinates of each node and integration point from the finite element simulation results, and then performed coordinate transformations as required. Let the node coordinates be (x... nl ,y nl ,z nl The coordinates of the integration point are (x...). ip ,y ip ,z ip ).

[0040] The distribution parameters of frictional heat flux include the weighted average value of the frictional heat flux. and weighted variance v f The calculation methods are Equations (5) and (6):

[0041]

[0042]

[0043] in,

[0044] The distribution parameters of viscoelastic hysteresis heat flux include the weighted average value of the viscoelastic hysteresis heat flux. and weighted variance v h The calculation methods are Equations (7) and (8):

[0045]

[0046]

[0047] in,

[0048] The present invention also discloses a computer-readable storage medium storing a computer program for implementing the above-described method for calculating the steady-state meshing temperature field of plastic gears based on an intelligent iterative algorithm.

[0049] This invention also discloses a plastic gear meshing temperature field prediction system, comprising a processor, an input unit, an output unit, and a storage unit. The input unit can receive information from an external material database. The output unit can reflect information about external performance. The storage unit is used to store simulation software, instruction sequences executed by the processor to generate operational data for implementing the above method, and data generated during the operation of the plastic gear steady-state meshing temperature field prediction system.

[0050] The beneficial effects of this invention are as follows:

[0051] A. The steady-state meshing heat flux of plastic gears in a stable meshing state is calculated by using an intelligent iterative algorithm to ensure that the steady-state meshing temperature field of plastic gears in a stable meshing state is obtained more accurately and efficiently.

[0052] B. It can intuitively obtain the steady-state meshing temperature field distribution of plastic gears during the actual stable meshing process, while avoiding the high equipment and time costs caused by actual product experiments, thus shortening the development cycle of plastic gear products. Attached Figure Description

[0053] Figure 1 A flowchart for calculating the steady-state meshing temperature field of plastic gears;

[0054] Figure 2 The flowchart shows the calculation process for steady-state meshing heat flux based on an intelligent iterative algorithm.

[0055] Figure 3 A schematic diagram of the coordinate transformation of the model when calculating the meshing heat flux distribution state parameters;

[0056] Figure 4 Example of calculating the steady-state meshing temperature field of a plastic gear. Detailed Implementation

[0057] The present invention will be further described below with reference to embodiments, but it should not be construed that the scope of the present invention is limited to the following embodiments. Various substitutions and modifications made based on ordinary technical knowledge and common practices in the art without departing from the above-described technical concept of the present invention should be included within the scope of protection of the present invention.

[0058] Example 1:

[0059] See Figure 1 This embodiment discloses a method for calculating the steady-state meshing temperature field of plastic gears based on an intelligent iterative algorithm. The plastic gear used is a helical gear obtained by injection molding from pure POM material, and the meshing object of the plastic gear is a copper metal worm. The method includes the following steps:

[0060] 1) Determine the operating conditions of the plastic gear meshing, including speed, torque, ambient temperature and initial gear temperature, and convert these operating conditions into the boundary conditions required for finite element analysis.

[0061] 2) Based on the intelligent iterative algorithm, calculate the steady-state meshing heat flux of the gears under the operating conditions determined in step 1). See [link / reference]. Figure 2 This process includes the following sub-steps:

[0062] 2.1) Based on specific iterative criteria, calculate the meshing heat flux distribution for different meshing cycles until the meshing heat flux distribution is determined to be stable. Specifically:

[0063] Define the current meshing cycle number as j, the reference meshing cycle number as k, and the iteration interval as N, all initially set to 1. Based on the differences between the current cycle and the reference cycle, subsequent steps are divided into two cases: step A) and step B).

[0064] A) The current period is the reference period, i.e., j = k:

[0065] A1) Based on the boundary conditions of the finite element analysis calculated from the working conditions of the plastic gear meshing, the finite element structural analysis of the plastic gear meshing process in the reference meshing period k is performed. The history of the change of normal contact force and relative slip velocity at each node on the meshing contact surface of the plastic gear in the current meshing period, as well as the history of the change of principal strain at each element integration point in the reference period k are output.

[0066] A2) Scripts written in Python are used to calculate the heat generation power at the contact tooth surface nodes. The heat generation power at the contact tooth surface nodes is calculated using equation (1).

[0067]

[0068] In the formula, q f,nl Q represents the heat generation power at the contact tooth surface node. f,nl F represents the accumulated frictional heat at the contact tooth node during one meshing cycle. t is the duration of contact engagement at the node in each meshing cycle. β is the proportionality coefficient of frictional heat distribution between the contact surfaces, calculated by equation (2). μ is the coefficient of friction. contact v represents the instantaneous normal contact force at the node.slip The instantaneous relative slip velocity at the node.

[0069]

[0070] Where: subscripts 1 and 2 represent the tooth surfaces of the driving gear and the driven gear, respectively. β1 + β2 = 1. λ is the thermal conductivity. c is the specific heat capacity. ρ is the density. v r Let be the linear velocity at the base circle.

[0071] A3) Using a script written in Python, and combining the unit principal strain history output in step A1), calculate the heat generation power density within each grid cell. The heat generation power density at the integration point of each grid cell is calculated using equation (3).

[0072] q h,ip =ξ h,ip / t (3)

[0073] In the formula, q h,ip The heat generation power density at each grid cell integration point during one meshing cycle. ξ h,ip The viscoelastic hysteresis loss heat density accumulated at each meshing point in each meshing cycle.

[0074] Furthermore, the principal strain history at each grid element integration point during one meshing cycle is extracted from the analysis results. A Fourier transform is performed to obtain a series of sinusoidal strain curves. The amplitude of each sinusoidal strain component at each grid element integration point is substituted into equation (4) to calculate ξ. h,ip .

[0075]

[0076] In the formula, δ represents the total modulus of the plastic under specific temperature and strain rate conditions. i It is the viscoelastic loss angle of plastic under specific temperature and strain rate conditions. ω i Let ε be the angular frequency of the i-th sinusoidal strain component. i Let be the amplitude of the i-th sinusoidal strain component.

[0077] A4) Calculate the meshing heat flux distribution state parameters for the reference period k. Specifically, the calculation method for the meshing heat flux distribution state parameters is as follows:

[0078] Given the frictional heat generation power q at the node calculated in steps A2) and A3). f,nl and the viscoelastic hysteresis loss power density q at the integration point of the grid cell h,ipBy writing Python scripts, the coordinates of each node and integration point in the finite element simulation results are read, and the coordinates are transformed as required. Figure 3 The location is shown. Let the node coordinates be (x...). nl ,y nl ,z nl The coordinates of the integration point are (x...). ip ,y ip ,z ip ).

[0079] The distribution parameters of frictional heat flux include the weighted average value of the frictional heat flux. and weighted variance v f The calculation methods are Equations (5) and (6):

[0080]

[0081]

[0082] in,

[0083] The distribution parameters of viscoelastic hysteresis heat flux include the weighted average value of the viscoelastic hysteresis heat flux. and weighted variance v h The calculation methods are Equations (7) and (8):

[0084]

[0085]

[0086] in,

[0087] A5) Calculate the three-dimensional temperature field at the end of the current period j based on the meshing heat flow of the reference period k.

[0088] A6) Calculate the rate of change Δ of the meshing heat flux distribution state parameters of the reference period k compared to the previous reference period kN.

[0089] A7) If Δ ≥ 5%, it indicates that the distribution of meshing heat flux has changed significantly, and the iteration interval N = 1. If Δ < 5%, it indicates that the distribution of meshing heat flux has not changed significantly, and the iteration interval is increased to N = N + 1.

[0090] A8) If the updated iteration interval N = 10, it can be determined that the distribution of meshing heat flux has stabilized, and proceed to step 2.2). If the updated iteration interval N < 10, it can be determined that the distribution of meshing heat flux has not stabilized, and continue to step A9).

[0091] A9) Update the current meshing cycle j = j + 1. If j = k + N at this point, the reference meshing cycle k = k + N also needs to be updated. Based on the differences between the updated current meshing cycle and the reference meshing cycle, reselect either step A) or step B).

[0092] B) The current engagement cycle is not the reference cycle, i.e., j ≠ k:

[0093] B1) Calculate the three-dimensional temperature field at the end of the current period j based on the meshing heat flow of the reference period k.

[0094] B2) If the updated iteration interval N = 10, it is determined that the distribution of meshing heat flux has stabilized, and the process proceeds to step 2.2). If the updated iteration interval N < 10, it is determined that the distribution of meshing heat flux has not stabilized, and the process continues to step B3).

[0095] B3) Update the current meshing cycle j = j + 1. If j = k + N at this point, the reference meshing cycle k = k + N also needs to be updated. Based on the differences between the updated current meshing cycle and the reference meshing cycle, reselect either step A) or step B).

[0096] 2.2) Treat the meshing heat flow of the current reference meshing period k as the steady-state meshing heat flow and output the steady-state meshing heat flow.

[0097] 3) Using the steady-state meshing heat flux obtained in step 2) as the heat load, the steady-state meshing temperature field of the plastic gear is simulated and calculated using the finite element steady-state thermal analysis algorithm. The analysis results of the steady-state meshing temperature field of the plastic gear are as follows: Figure 4 As shown.

[0098] It is worth noting that, in this embodiment, the algorithm involved in step 2) can also calculate the transient temperature field of the plastic gear within a certain meshing cycle, and is more efficient than the traditional method.

[0099] Analyzing the steady-state meshing temperature field of plastic gears allows for the prediction of their meshing performance under continuous and stable operating conditions, including predictions of contact fatigue life, wear conditions, and thermal load capacity. Based on these predictions, the product design can be adjusted and optimized in a timely manner during the design phase, thereby improving product performance.

[0100] Example 2:

[0101] This embodiment discloses a method for calculating the steady-state meshing temperature field of plastic gears based on an intelligent iterative algorithm, including the following steps:

[0102] 1) Determine the operating conditions of the plastic gear meshing, including speed, torque, ambient temperature and initial gear temperature, and convert these operating conditions into the boundary conditions required for finite element analysis.

[0103] 2) Based on the intelligent iterative algorithm, calculate the steady-state meshing heat flow of the gear under the working conditions determined in step 1).

[0104] 3) Using the steady-state meshing heat flow obtained in step 2) as the heat load, the steady-state meshing temperature field of the plastic gear is simulated and calculated using the finite element steady-state thermal analysis algorithm.

[0105] Example 3:

[0106] The main steps of this embodiment are the same as those of embodiment 2. Furthermore, step 2) includes the following sub-steps:

[0107] 2.1) Based on specific iterative criteria, calculate the meshing heat flux distribution for different meshing cycles until the meshing heat flux distribution is determined to be stable. Specifically:

[0108] Define the current meshing cycle number as j, the reference meshing cycle number as k, and the iteration interval as N, all initially set to 1. Based on the differences between the current cycle and the reference cycle, subsequent steps are divided into two cases: step A) and step B).

[0109] A) The current period is the reference period, i.e., j = k:

[0110] A1) Based on the boundary conditions of the finite element analysis calculated from the working conditions of the plastic gear meshing, the finite element structural analysis of the plastic gear meshing process in the reference meshing period k is performed. The history of the change of normal contact force and relative slip velocity at each node on the meshing contact surface of the plastic gear in the current meshing period, as well as the history of the change of principal strain at each element integration point in the reference period k are output.

[0111] A2) Scripts written in Python are used to calculate the heat generation power at the contact tooth surface nodes. The heat generation power at the contact tooth surface nodes is calculated using equation (1).

[0112]

[0113] In the formula, q f,nl Q represents the heat generation power at the contact tooth surface node. f,nl F represents the accumulated frictional heat at the contact tooth node during one meshing cycle. t is the duration of contact engagement at the node in each meshing cycle. β is the proportionality coefficient of frictional heat distribution between the contact surfaces, calculated by equation (2). μ is the coefficient of friction. contact v represents the instantaneous normal contact force at the node. slip The instantaneous relative slip velocity at the node.

[0114]

[0115] Where: subscripts 1 and 2 represent the tooth surfaces of the driving gear and the driven gear, respectively. β1 + β2 = 1. λ is the thermal conductivity. c is the specific heat capacity. ρ is the density. v r Let be the linear velocity at the base circle.

[0116] A3) Using a script written in Python, and combining the unit principal strain history output in step A1), calculate the heat generation power density within each grid cell. The heat generation power density at the integration point of each grid cell is calculated using equation (3).

[0117] q h,ip =ξ h,ip / t (3)

[0118] In the formula, q h,ip The heat generation power density at each grid cell integration point during one meshing cycle. ξ h,ip The viscoelastic hysteresis loss heat density accumulated at each meshing point in each meshing cycle.

[0119] A4) Calculate the meshing heat flow distribution state parameters for the reference period k.

[0120] A5) Calculate the three-dimensional temperature field at the end of the current period j based on the meshing heat flow of the reference period k.

[0121] A6) Calculate the rate of change Δ of the meshing heat flux distribution state parameters of the reference period k compared to the previous reference period kN.

[0122] A7) If Δ ≥ 5%, the iteration interval N = 1. If Δ < 5%, the iteration interval increases, N = N + 1.

[0123] A8) If the updated iteration interval N = 10, it is determined that the distribution of meshing heat flux has stabilized, and the process proceeds to step 2.2). If the updated iteration interval N < 10, it is determined that the distribution of meshing heat flux has not stabilized, and the process continues to step A9).

[0124] A9) Update the current meshing cycle j = j + 1. If j = k + N at this point, the reference meshing cycle k = k + N also needs to be updated. Based on the differences between the updated current meshing cycle and the reference meshing cycle, reselect either step A) or step B).

[0125] B) The current engagement cycle is not the reference cycle, i.e., j ≠ k:

[0126] B1) Calculate the three-dimensional temperature field at the end of the current period j based on the meshing heat flow of the reference period k.

[0127] B2) If the updated iteration interval N = 10, it is determined that the distribution of meshing heat flux has stabilized, and the process proceeds to step 2.2). If the updated iteration interval N < 10, it is determined that the distribution of meshing heat flux has not stabilized, and the process continues to step B3).

[0128] B3) Update the current meshing cycle j = j + 1. If j = k + N at this point, the reference meshing cycle k = k + N also needs to be updated. Based on the differences between the updated current meshing cycle and the reference meshing cycle, reselect either step A) or step B).

[0129] 2.2) Treat the meshing heat flow of the current reference meshing period k as the steady-state meshing heat flow and output the steady-state meshing heat flow.

[0130] Example 4:

[0131] The main steps of this embodiment are the same as those of embodiment 3. Further, in step A3), the principal strain history at each grid cell integration point during one meshing cycle is extracted from the analysis results. A Fourier transform is performed to obtain a series of sinusoidal strain curves. The amplitude of each sinusoidal strain component at each grid cell integration point is substituted into equation (4) to calculate ξ. h,ip .

[0132]

[0133] In the formula, δ represents the total modulus of the plastic under specific temperature and strain rate conditions. i It is the viscoelastic loss angle of plastic under specific temperature and strain rate conditions. ω i Let ε be the angular frequency of the i-th sinusoidal strain component. i Let be the amplitude of the i-th sinusoidal strain component.

[0134] Example 5:

[0135] The main steps in this embodiment are the same as in embodiment 3. Further, in step A4), the calculation method for the distribution state parameters of the meshing heat flux is as follows:

[0136] Given the frictional heat generation power q at the node calculated in steps A2) and A3). f,nl and the viscoelastic hysteresis loss power density q at the integration point of the grid cell h,ip A Python script was written to read the coordinates of each node and integration point from the finite element simulation results, and then performed coordinate transformations as required. Let the node coordinates be (x... nl ,y nl ,z nl The coordinates of the integration point are (x...). ip ,y ip ,z ip ).

[0137] The distribution parameters of frictional heat flux include the weighted average value of the frictional heat flux. and weighted variance v f The calculation methods are Equations (5) and (6):

[0138]

[0139]

[0140] in,

[0141] The distribution parameters of viscoelastic hysteresis heat flux include the weighted average value of the viscoelastic hysteresis heat flux. and weighted variance v h The calculation methods are Equations (7) and (8):

[0142]

[0143]

[0144] in,

[0145] Example 6:

[0146] This embodiment discloses a computer-readable storage medium storing a computer program for implementing any one of the methods for calculating the steady-state meshing temperature field of plastic gears based on an intelligent iterative algorithm in embodiments 2 to 5.

[0147] Example 7:

[0148] This embodiment discloses a plastic gear meshing temperature field prediction system, including a processor, an input unit, an output unit, and a storage unit. The input unit can receive information from an external material database. The output unit can reflect information about external performance. The storage unit is used to store simulation software, instruction sequences executed by the processor for generating operational data to implement any one of the methods in embodiments 2-5, and data during the operation of the plastic gear steady-state meshing temperature field prediction system.

Claims

1. A method for calculating the steady-state engagement temperature field of a plastic gear based on an intelligent iterative algorithm, characterized in that, Comprising the following steps: 1) determining the working conditions of the plastic gear meshing, the working conditions including the rotating speed, the torque, the ambient temperature and the initial temperature of the gear, and converting the working conditions into the boundary conditions required for finite element analysis; 2) based on the intelligent iteration algorithm, calculating the steady-state meshing heat flow under the working conditions determined in step 1); the specific steps are as follows: 2.1) based on a specific iteration criterion, calculating the meshing heat flow distribution of different meshing periods until the meshing heat flow distribution is determined to be stable: Define the current meshing period number as j, the reference meshing period number as k, and the iteration interval as N, and the initial values of the three are all 1; according to the difference between the current period j and the reference period k, the subsequent steps are divided into two cases A) and B): A) the current period is the reference period, i.e. j=k: A1) based on the finite element analysis boundary conditions converted from the working conditions of the plastic gear meshing, performing finite element structural analysis on the meshing process of the plastic gear in the reference meshing period k, and outputting the change history of the normal contact force and the relative slip speed at each node on the meshing contact surface of the plastic gear in the current meshing period, as well as the change history of the principal strain at each element integration point in the reference period k; A2) based on Python language script, calculating the heat generation power at the contact tooth surface nodes; The heat generation power at the contact tooth surface nodes is calculated by formula (1); (1) wherein is the heat generation power at the contact tooth surface node; is the accumulated friction heat at the contact tooth surface node in one meshing cycle; t is the time length of the node participating in contact meshing in each meshing cycle; is the distribution proportion coefficient of the friction heat between the contact surfaces, calculated by formula (2); is the friction coefficient; is the instantaneous normal contact force at the node; is the instantaneous relative slip speed at the node; (2) wherein: the lower indices 1 and 2 represent the tooth surfaces of the driving gearwheel and the driven gearwheel, respectively; ; is the thermal conductivity; is the specific heat capacity; is the density; is the linear speed at the base circle; A3) based on Python language script, combining the element principal strain history output in step A1), and calculating the heat generation power density in each grid element; the heat generation power density at each grid element integration point is calculated by formula (3); (3) wherein is the heat power density generated by each grid cell for the integration point in one engagement cycle; is the viscoelastic hysteresis heat density accumulated by each grid cell for the integration point in each engagement cycle; A4) calculating the meshing heat flow distribution state parameters of the reference period k; A5) based on the meshing heat flow of the reference period k, calculating the three-dimensional temperature field at the end stage of the current period j; A6) calculating the change rate Δ of the meshing heat flow distribution state parameters of the reference period k compared with the previous reference period k-N; A7) if Δ≥5%, the iteration interval N=1; if Δ<5%, the iteration interval is increased, N=N+1; A8) if the updated iteration interval N=10, it is determined that the distribution of the meshing heat flow has tended to be stable, and step 2.2) is skipped; if the updated iteration interval N<10, it is determined that the distribution of the meshing heat flow has not tended to be stable, and step A9) is continued; A9) updating the current meshing period j=j+1; wherein, if j=k+N at this time, the reference meshing period k=k+N also needs to be updated; according to the difference between the updated current meshing period and the reference meshing period, reselecting to enter A) or B); B) the current meshing period is not the reference period, i.e. j≠k: B1) based on the meshing heat flow of the reference period k, calculating the three-dimensional temperature field at the end stage of the current period j; B2) if the updated iteration interval N=10, it is determined that the distribution of the meshing heat flow has tended to be stable, and step 2.2) is skipped; if the updated iteration interval N<10, it is determined that the distribution of the meshing heat flow has not tended to be stable, and step B3) is continued; B3) updating the current meshing period j = j + 1; wherein, if j = k + N at this time, the reference meshing period k = k + N also needs to be updated; according to the difference between the updated current meshing period and the reference meshing period, reselecting to enter A) or B); 2.2) taking the meshing heat flow of the current reference meshing period k as the steady-state meshing heat flow, and outputting the steady-state meshing heat flow; 3) taking the steady-state meshing heat flow obtained in step 2) as a thermal load, simulating and calculating the steady-state meshing temperature field of the plastic gear through a finite element steady-state thermal analysis algorithm.

2. The plastic gear steady-state engagement temperature field calculation method based on an intelligent iterative algorithm according to claim 1, characterized in that: In step A3), the principal strain history at each grid point in one engagement cycle is extracted from the analysis results; Fourier transform is performed to obtain a series of sinusoidal strain curves; the amplitude of each sinusoidal partial strain at each grid point is brought into formula (4) to calculate ; (4) In the formula, This refers to the total modulus of the plastic under specific temperature and strain rate conditions. It is the viscoelastic loss angle of plastic under specific temperature and strain rate conditions; For the first The angular frequency of a sinusoidal strain component; For the first The amplitude of each sinusoidal strain component.

3. The steady state engagement temperature field calculation method of plastic gear based on intelligent iterative algorithm according to claim 1, characterized in that, In step A4), the calculation method of the distribution state parameter of the meshing heat flow is as follows: Step A2) and step A3) calculate the friction heat power at the node and the viscoelastic hysteresis loss power density at the grid element integration point , the corresponding node and integration point coordinates are read from the finite element simulation results by writing a Python script, and coordinate transformation is performed according to the requirements; the node coordinates are recorded as , and the integration point coordinates are ; The distribution state parameters of the frictional heat flow include a weighted average value of the frictional heat flow and a weighted variance The calculation is performed according to formula (5) and formula (6): (5) (6) wherein ; ; ; The distribution state parameters of the viscoelastic hysteresis heat flow include a weighted average value of the viscoelastic hysteresis heat flow and a weighted variance The calculation is performed according to equations (7) and (8): (7) (8) wherein ; ; .

4. A computer-readable storage medium, characterized in that: The computer program for realizing the plastic gear steady-state meshing temperature field calculation method based on the intelligent iterative algorithm in any one of claims 1-3 is stored.

5. A plastic gear mesh temperature field prediction system characterized by: The system comprises a processor, an input unit, an output unit and a storage unit; the input unit can receive information from an external material database; the output unit can reflect information of external performance; the storage unit is used for storing simulation software, instruction sequences for generating operation data of any one of the methods in claims 1-3 executed by the processor and data during operation of the plastic gear steady-state meshing temperature field prediction system.

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