Transmission bearing installation pre-tightening amount calculation method and system

Abstract

The invention relates to the technical field of bearing life calculation, in particular to a transmission bearing installation pre-tightening amount calculation method and system, and the method comprises the steps: S1, building a finite element mesh model of a transmission housing and a shaft through finite element simulation software based on predefined material attributes; the material attributes comprise elastic modulus, Poisson's ratio and thermal expansion coefficient of the transmission shell and the shaft; s2, based on the actual working condition of transmission assembly life simulation analysis, importing the finite element mesh model of the transmission shell and the shaft into a pre-constructed multi-body dynamics simulation model of the transmission shell, and establishing node connection between the finite element mesh model of the transmission shell and the shaft and a transmission part in the multi-body dynamics simulation model; s3, setting a detection object and a design variable, and adopting a preset strategy to obtain a target mapping curve of the detection object and the design variable; compared with the prior art, the optimal relation between the pre-tightening amount and the service life of the bearing can be quickly determined, so that the service life of the bearing is maximized.

Description

Technical Field

[0001] This application relates to the field of bearing life calculation technology, and in particular to a method and system for calculating the installation preload of a transmission bearing. Background Technology

[0002] The primary function of transmission bearings is to support the shaft and gears, ensuring the rotational accuracy of the shaft and gears, smooth gear meshing, and reducing system friction and wear. The presence of clearance in bearings ensures flexible and unobstructed operation, but also requires maintaining smooth operation, minimizing shaft settlement, and maximizing the number of load-bearing rolling elements. Therefore, bearing clearance significantly impacts the bearing's dynamic performance (noise, vibration, and friction), rotational accuracy, service life (wear and fatigue), and load-bearing capacity.

[0003] Excessive clearance reduces the number of rolling elements bearing the load simultaneously, increasing the load on each individual element and thus decreasing the bearing's rotational accuracy and lifespan. Conversely, insufficient clearance increases friction, generates more heat, and accelerates wear, similarly reducing bearing lifespan. Therefore, strict control and adjustment of bearing clearance are crucial. Bearing clearance adjustment capabilities are categorized into non-adjustable and adjustable bearings. The optimal operating clearance is determined by operating conditions and expected lifespan. However, there is a lack of verification methods for bearing clearance in the initial design phase, relying solely on later testing for validation. Furthermore, bench testing cannot fully replicate the vehicle's condition, failing to meet rapid development requirements.

[0004] During the assembly of the transmission assembly, the interference fit causes stress deformation in the inner and outer rings of the bearing, resulting in changes in radial dimensions. In actual operation, because the thermal expansion coefficient of the aluminum housing is higher than that of the bearing, the radial deformation of the bearing housing will be greater than that of the bearing. The radial clearance of the bearing does not meet the radial deformation caused by the above two situations, resulting in sliding friction in the bearing. The bearing and bearing housing and other parts are squeezed against each other, which can cause structural noise or even bearing failure.

[0005] Based on the above, this application provides a method and system for calculating the installation preload of transmission bearings to maximize bearing life. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for calculating the preload of transmission bearings. This method offers high simulation efficiency and can quickly determine the optimal relationship between the preload and bearing life, thereby maximizing bearing life. The specific solution is as follows:

[0007] A method for calculating the installation preload of a transmission bearing, the method comprising the following steps:

[0008] S1: Based on predefined material properties, a finite element mesh model of the transmission housing and shaft is constructed using finite element simulation software; the material properties include the elastic modulus, Poisson's ratio, and coefficient of thermal expansion of the transmission housing and shaft;

[0009] S2: Based on the actual working conditions of the transmission assembly life simulation analysis, the finite element mesh model of the transmission housing and shaft is imported into the pre-built multibody dynamics simulation model of the transmission housing, and node connections are established between it and the transmission components in the multibody dynamics simulation model.

[0010] S3: Set the detection object and design variables, adopt the preset strategy, and obtain the target mapping curve of the detection object and design variables.

[0011] Optionally, step S2 includes:

[0012] Based on the actual operating conditions of the transmission assembly life simulation analysis, temperature parameters are pre-configured.

[0013] The temperature parameters include at least: the initial ambient temperature of the transmission assembly, and the temperatures of the housing, shaft, inner and outer rings of the bearings, rolling elements, and lubricating oil under actual operating conditions; wherein, based on actual operating conditions, the temperature parameter configuration during transmission assembly operation must meet the following design requirements:

[0014] Bearing roller temperature > inner ring temperature > shaft temperature > bearing outer ring temperature > housing temperature = oil temperature.

[0015] Optionally, step S3, which involves setting the detection object and design variables, and using a preset strategy to obtain the target mapping curve of the detection object and design variables, specifically includes:

[0016] The tolerance and fit parameters for bearing installation in the simulation model are pre-configured; bearing service life is used as the test object, and preload is used as the design variable.

[0017] Among them, the preload generated by the maximum interference when the installation tolerance is matched will be determined as a design variable.

[0018] Optionally, step S3, which involves setting the detection object and design variables, and using a preset strategy to obtain the target mapping curve of the detection object and design variables, further includes:

[0019] Using design variables as variables, a first set of DOE simulation models is constructed based on pre-configured first configuration parameters, and the initial mapping curve between the detection object and the design variables is output through the first set of DOE simulation models; wherein, the first configuration parameters include the first preset range and the first simulation step size of the design variables;

[0020] Based on the initial mapping curve of the detection object and design variables, the curve interval corresponding to the maximum value of the detection object is taken as the key interval;

[0021] Using the critical interval as the simulation range, the second set of DOE simulation models with design variables as variables is obtained by adjusting the first configuration parameters, and the target mapping curve of the detection object and design variables is output through the second set of DOE simulation models.

[0022] Optionally, step S3, which involves setting the detection object and design variables, and using a preset strategy to obtain the target mapping curve of the detection object and design variables, further includes:

[0023] Using design variables as variables and based on pre-configured multiphysics coupling first configuration parameters, a first set of coupled DOE simulation models is constructed, with design variables as the baseline and key variables as interaction variables. The initial mapping curve between the detection object and the design variables is output through the first set of coupled DOE simulation models, and the thermodynamic mapping curves of the design variables, key variables, and detection object are generated simultaneously. Among them, the key variables are the load, shell temperature, and the thermal deformation of the shell and shaft corresponding to different loads.

[0024] Based on the initial mapping curve and the thermal mapping curve, the dynamic key interval corresponding to the maximum value of the detected object is determined. The dynamic key interval is used as the simulation domain, and the first configuration parameter is adjusted by an adaptive step-size iterative algorithm.

[0025] Through the structural and thermal coupling correction module, the contact stress change corresponding to the design variables is input into the temperature field simulation to correct the material properties in the critical range, and a second set of DOE simulation models is constructed accordingly.

[0026] The second set of DOE models outputs the target mapping curves for the detection object and design variables, as well as the table showing the relationship between the optimal preload and key variable constraints.

[0027] Optionally, the adaptive step-size iterative algorithm adjusts the first configuration parameter, specifically including:

[0028] The second simulation step size is generated based on the rate of change of curvature of the initial curve.

[0029] A system for calculating the installation preload of a transmission bearing, the system comprising:

[0030] The first simulation module is configured to construct a finite element mesh model of the transmission housing and shaft using finite element simulation software based on predefined material properties; the material properties include the elastic modulus, Poisson's ratio, and coefficient of thermal expansion of the transmission housing and shaft.

[0031] The second simulation module is configured to simulate the actual working conditions based on the life simulation analysis of the transmission assembly. It imports the finite element mesh model of the transmission housing and shaft into the pre-built multibody dynamics simulation model of the transmission housing and establishes node connections between it and the transmission components in the multibody dynamics simulation model.

[0032] The strategy module is configured to set the detection objects and design variables, adopt a preset strategy, and obtain the target mapping curves of the detection objects and design variables.

[0033] An electronic device includes: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; the memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the method.

[0034] A computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method described herein.

[0035] A simulation platform, comprising:

[0036] An electronic device for implementing the steps of the method;

[0037] A processor that runs a program, and when the program runs, it executes the steps of the method from data output by the electronic device.

[0038] A storage medium for storing a program that, when run, executes the steps of the method on data output from an electronic device.

[0039] The above solution achieves the following beneficial technical effects:

[0040] This application provides a method and system for calculating the preload of a transmission bearing. Based on predefined material properties, a finite element mesh model of the transmission housing and shaft is constructed using finite element simulation software, avoiding the problem of performance discrepancy between virtual and real parts. Furthermore, the housing / shaft model is connected to the transmission components at nodes and combined with actual working conditions to closely match the real interaction state of the parts during the overall operation of the transmission, overcoming the distortion problem caused by calculating isolated parts. By setting the detection object and design variables and adopting a preset strategy, the optimal relationship between the preload and bearing life can be quickly determined. Compared with the traditional method of repeatedly conducting physical tests, this saves a lot of R&D and time costs, and the output target mapping curve can directly obtain the impact of the preload on the life, ultimately maximizing the bearing life. Attached Figure Description

[0041] Figure 1A flowchart illustrating a method for calculating the installation preload of a transmission bearing;

[0042] Figure 2 A flowchart illustrating a method for calculating the preload of a transmission bearing in one embodiment;

[0043] Figure 3 This is a multibody dynamics simulation model of a transmission assembly according to an embodiment of the present invention;

[0044] Figure 4 A finite element model of a transmission housing according to an embodiment of the invention;

[0045] Figure 5 A finite element model of a transmission shaft according to one embodiment of the invention;

[0046] Figure 6 This is a flowchart of a DOE simulation model according to an embodiment of the present invention;

[0047] Figure 7 This is a DOE simulation result diagram of an embodiment of the present invention;

[0048] Figure 8 This is a preload-life curve diagram of one embodiment of the present invention. Detailed Implementation

[0049] To make the purpose, technical solution, and advantages of this application clearer, the following will be described in conjunction with the appendix. Figures 1-8 This application will be described in further detail. It is obvious that the described embodiments are merely some, not all, of the embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments described herein without inventive effort are within the scope of protection of this application.

[0050] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0051] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0052] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application for description, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0053] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0054] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0055] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0056] like Figure 1 The method shown is for calculating the installation preload of a transmission bearing, and the method includes the following steps:

[0057] S1: Based on predefined material properties, a finite element mesh model of the transmission housing and shaft is constructed using finite element simulation software; the material properties include the elastic modulus, Poisson's ratio, and coefficient of thermal expansion of the transmission housing and shaft;

[0058] S2: Based on the actual working conditions of the transmission assembly life simulation analysis, the finite element mesh model of the transmission housing and shaft is imported into the pre-built multibody dynamics simulation model of the transmission housing, and node connections are established between it and the transmission components in the multibody dynamics simulation model.

[0059] S3: Set the detection object and design variables, adopt the preset strategy, and obtain the target mapping curve of the detection object and design variables.

[0060] Specifically, see Figure 2As shown, this application constructs a finite element mesh model of the transmission housing and shaft using finite element simulation software based on predefined material properties, avoiding the problem of performance disconnect between virtual and real parts. Furthermore, by establishing node connections between the housing / shaft model and transmission components and combining them with actual working conditions, the model closely matches the actual interaction state of parts during the overall operation of the transmission, overcoming the problem of result distortion caused by isolated calculation of parts. By setting detection objects and design variables and adopting preset strategies, the optimal relationship between preload and bearing life can be quickly determined. Compared with the traditional method of repeatedly conducting physical tests, this saves a lot of R&D and time costs. Moreover, the output target mapping curve can directly obtain the impact of preload on life, ultimately maximizing bearing life to guide the preload in production assembly.

[0061] See Figure 3 , Figure 3 The multibody dynamics simulation model of the transmission housing includes: 1: Transmission housing; 2: Input shaft assembly; 3: Main gearbox upper right intermediate shaft assembly; 4: Lower left intermediate shaft assembly; 5: Two-shaft assembly; 6: Auxiliary gearbox input gear; 7: Auxiliary gearbox upper left intermediate shaft; 8: Auxiliary gearbox lower right intermediate shaft; 9: Output shaft; 10: Auxiliary gearbox upper left intermediate shaft front bearing; 11: Auxiliary gearbox upper left intermediate shaft rear bearing; 12: Auxiliary gearbox lower right intermediate shaft front bearing; 13: Auxiliary gearbox lower right intermediate shaft rear bearing. Power flow transmission path: Input shaft assembly 2 → Main gearbox upper right intermediate shaft assembly 3, lower left intermediate shaft assembly 4 → Two-shaft assembly 5 → Auxiliary gearbox input gear 6 → Auxiliary gearbox upper left intermediate shaft 7, lower right intermediate shaft 8 → Output shaft 9.

[0062] See Figure 4 As shown, the transmission housing 1 is divided into finite element elements using tetrahedral 10-node mesh elements, which are then imported into MASTA. Node connections are established with the front bearing 10 of the upper left intermediate shaft of the auxiliary gearbox, the rear bearing 11 of the upper left intermediate shaft of the auxiliary gearbox, the front bearing 12 of the lower right intermediate shaft of the auxiliary gearbox, and the rear bearing 13 of the lower right intermediate shaft of the auxiliary gearbox. The stop plane of the transmission housing is grounded.

[0063] See Figure 5 As shown, finite element analysis is performed on the upper left intermediate shaft 7 and the lower right intermediate shaft 8 of the auxiliary box, and node connections are established with the front bearing 10, rear bearing 11, front bearing 12, and rear bearing 13 of the upper left intermediate shaft of the auxiliary box, and then condensation is performed.

[0064] Furthermore, the material density, elastic modulus, Poisson's ratio, and coefficient of thermal expansion of the transmission housing and intermediate shaft are defined. Then, the housing mesh is condensed. During condensation, the thermal expansion option is calculated based on the material properties, as shown in the table below:

[0065] In one specific embodiment, step S2 includes:

[0066] Based on the actual operating conditions of the transmission assembly life simulation analysis, temperature parameters are pre-configured.

[0067] The temperature parameters include at least: the initial ambient temperature of the transmission assembly, and the temperatures of the housing, shaft, inner and outer rings of the bearings, rolling elements, and lubricating oil under actual operating conditions; wherein, based on actual operating conditions, the temperature parameter configuration during transmission assembly operation must meet the following design requirements:

[0068] Bearing roller temperature > inner ring temperature > shaft temperature > bearing outer ring temperature > housing temperature = oil temperature.

[0069] The bearing temperature is defined based on actual conditions. The bearing outer ring fit tolerance coefficient, bearing inner ring fit tolerance coefficient, and bearing initial radial preload coefficient are defined, while considering the influence of tolerance fit and temperature on the simulation results, as shown in the table below:

[0070] Furthermore, step S3, which involves setting the detection object and design variables, and using a preset strategy to obtain the target mapping curve for the detection object and design variables, specifically includes:

[0071] The tolerance and fit parameters for bearing installation in the simulation model are pre-configured; bearing service life is used as the test object, and preload is used as the design variable.

[0072] Specifically, the preload amount generated by the maximum interference fit during installation tolerance will be determined as a design variable. In this embodiment, the actual operating conditions for the transmission assembly life simulation analysis require pre-setting the bearing installation tolerance, including the tolerance grades of the shaft diameter, bore diameter, and inner and outer rings of the bearing, as well as the roughness grades of the shaft diameter, bore diameter, and inner and outer rings of the bearing.

[0073] Furthermore, step S3, which involves setting the detection object and design variables, and using a preset strategy to obtain the target mapping curve of the detection object and design variables, also includes:

[0074] Using design variables as variables, a first set of DOE simulation models is constructed based on pre-configured first configuration parameters, and the initial mapping curve between the detection object and the design variables is output through the first set of DOE simulation models; wherein, the first configuration parameters include the first preset range and the first simulation step size of the design variables;

[0075] Based on the initial mapping curve of the detection object and design variables, the curve interval corresponding to the maximum value of the detection object is obtained as the key interval;

[0076] Using the critical interval as the simulation range, a second set of DOE simulation models with design variables is obtained by adjusting the first configuration parameters (e.g., refining the first simulation step size into the second simulation step size), and the target mapping curve of the detection object and design variables is output through the second set of DOE simulation models.

[0077] like Figure 6 As shown, to establish the DOE simulation model, the bearing installation preload is defined as the research variable, and the bearing ISO16281 modified safety factor is defined as the research object. The variable range is (A~B) μm, the variable step size is X μm, and the grouping settings are completed simultaneously.

[0078] like Figure 7 As shown, simulation calculations were performed on the parametric study conditions. The X-axis variable was selected as the bearing installation preload, and the Y-axis was selected as the bearing safety factor. The parametric study results were output. The safety factor was maximized when the bearing installation preload was 0.16 mm. The above calculation results represent the initial preload selection.

[0079] To further refine the calculation of the installation preload, the variable step size was adjusted to Yµm and the range reduced to Cum based on the above results, followed by another round of simulation calculations. Figure 8 As shown, the simulation results can be exported to an Excel file, charts can be plotted, the safety factor curves of the four bearings can be comprehensively evaluated, and the range of preload for bearing installation can be determined.

[0080] Specifically, in this embodiment, the design variables are the core. A first set of DOE simulation models is constructed based on the first configuration parameters, which include a wide range and large step size. Utilizing the principle of batch scanning of the variable space in DOE experimental design, the initial mapping curve is quickly output. The key interval corresponding to the maximum value of the detection object can be efficiently determined without manual simulation, avoiding the redundancy of computing power and wasted time caused by using a small step size from the beginning. Then, using the key interval as the simulation range, a second set of DOE simulation models is constructed by adjusting the configuration parameters by refining the step size. More refined numerical analysis is achieved near the maximum value of the detection object, accurately obtaining the influence relationship of subtle changes in variables on the detection object. The final output target mapping curve can directly obtain the relationship between the design variables and the detection object, ensuring simulation accuracy and maximizing bearing life.

[0081] It is understood that this embodiment uses finite element software to establish finite element models of the transmission housing and shaft, defines the material properties of the housing and shaft, including elastic modulus, Poisson's ratio, and coefficient of thermal expansion, and uses multibody dynamics software to establish a multibody dynamics model of the transmission assembly to calculate bearing life. Based on the finite element model, simulation operating temperature and installation fit tolerances are added to improve simulation accuracy, thereby enabling rapid output of conclusions and higher efficiency. Moreover, this embodiment has a stronger direct correlation with parts processing and assembly, and has been widely used in small and medium-sized manufacturing enterprises.

[0082] Furthermore, in this embodiment, the DOE simulation model 1 takes bearing life as the research object and the initial installation preload of the bearing as the variable. In order to fully cover the simulation range, the variable range is set to (2.5~3)‰ of the bearing span. In order to further improve the simulation accuracy, DOE simulation model 2 is established based on the simulation results of DOE simulation model 1, the variable range is reduced, and the step size is usually equivalent to the shim selection accuracy in the actual production process. Iterative calculations are performed to improve the simulation accuracy.

[0083] In another specific embodiment, step S3, which involves setting the detection object and design variables, and using a preset strategy to obtain the target mapping curve of the detection object and design variables, further includes:

[0084] Using design variables as variables and based on pre-configured multiphysics coupling first configuration parameters, a first set of coupled DOE simulation models is constructed, with design variables as the baseline and key variables as interaction variables. The initial mapping curve between the detection object and the design variables is output through the first set of coupled DOE simulation models, and the thermodynamic mapping curves of the design variables, key variables, and detection object are generated simultaneously. Among them, the key variables are the load, shell temperature, and the thermal deformation of the shell and shaft corresponding to different loads.

[0085] Based on the initial mapping curve and the thermal mapping curve, the dynamic key interval corresponding to the maximum value of the detected object is determined. The dynamic key interval is used as the simulation domain, and the first configuration parameter is adjusted by an adaptive step-size iterative algorithm.

[0086] The adaptive step-size iterative algorithm adjusts the first configuration parameter, specifically including:

[0087] The second simulation step size is generated based on the rate of change of curvature of the initial curve; for example, the step size is automatically reduced in regions with large lifetime gradients, while the step size is retained in regions with small gradients.

[0088] Through the structural and thermal coupling correction module, the contact stress change corresponding to the design variables is input into the temperature field simulation to correct the material properties in the critical range, and a second set of DOE simulation models is constructed accordingly.

[0089] The second set of DOE models outputs the target mapping curves for the detection object and design variables, as well as the table showing the relationship between the optimal preload and key variable constraints.

[0090] Specifically, in this embodiment, a coupled DOE simulation model is constructed with design variables as the baseline and key variables (load, shell temperature, and thermal deformation) as interactive variables. This model correlates the preload with the load, temperature, and structural deformation that interact in actual working conditions, avoiding the technical problem of theoretical discrepancy caused by univariate analysis. Secondly, an adaptive step-size iterative algorithm is adopted to dynamically adjust the step size based on the lifetime gradient of the initial mapping curve, reducing computational resources while ensuring analysis efficiency. Then, through the structural and thermal coupling correction module, the contact stress change caused by the preload is fed back to the temperature field simulation, correcting the material properties in the critical range. This corrects the lifetime calculation from the ideal 3500h to a more realistic 3200h, thus solving the simulation deviation caused by the disconnect between structure and thermal field.

[0091] It is understood that the technical solution provided in this embodiment, by restoring the interaction of multiple elements and the influence of physical fields, is not only applicable to highly complex scenarios, but also has ultra-high simulation accuracy. The only slight drawback is that the simulation cycle is long and the computing resources are consumed in large quantities.

[0092] For example, in the simulation of transmission bearings, the first set of coupled DOE simulation models uses the preload (0.1-0.5mm) as a variable and the load (100N-300N) and housing temperature (60-100℃) as key variables to output the initial life curve and thermogram. It can be seen that the bearing has the longest service life when the preload is 0.15mm, the load is 200N, and the temperature is 80℃.

[0093] Among them, the initial mapping curve has a large lifetime gradient in the range of 0.12-0.24mm, and the step size is reduced from 0.1mm to 0.02mm; the gradient is small in the range of 0.24-0.5mm, and the step size is kept at the original 0.1mm; the advantage of this design is that the overall computing power is reduced by 25%.

[0094] When the preload is 0.2mm, the increased contact stress leads to frictional heat generation, and the housing temperature rises from 80℃ to 95℃. After correction, the elastic modulus of the bearing steel is adjusted. If the elastic modulus is reduced by 4%, the calculated life value is adjusted from 3500h to 3200h. This avoids the disconnect between theoretical design and actual conditions and ensures the optimal preload for stable output.

[0095] In summary, the optimal preload is determined to be 0.028-0.032mm based on the target mapping curve. According to the constraint table, when the load is greater than 250N, the preload needs to be reduced to 0.025mm to guide the assembly work under different working conditions.

[0096] On the other hand, this application provides a system for calculating the installation preload of a transmission bearing, the system comprising:

[0097] The first simulation module is configured to construct a finite element mesh model of the transmission housing and shaft using finite element simulation software based on predefined material properties; the material properties include the elastic modulus, Poisson's ratio, and coefficient of thermal expansion of the transmission housing and shaft.

[0098] The second simulation module is configured to simulate the actual working conditions based on the life simulation analysis of the transmission assembly. It imports the finite element mesh model of the transmission housing and shaft into the pre-built multibody dynamics simulation model of the transmission housing and establishes node connections between it and the transmission components in the multibody dynamics simulation model.

[0099] The strategy module is configured to set the detection objects and design variables, adopt a preset strategy, and obtain the target mapping curves of the detection objects and design variables.

[0100] It is worth noting that although this system only discloses the first simulation module, the second simulation module, and the strategy module, it does not mean that this system is limited to the above-mentioned basic functional modules. On the contrary, what this invention intends to express is that, based on the above-mentioned basic functional modules, those skilled in the art can add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. That is to say, this system is open rather than closed. It should not be assumed that the scope of protection of the claims of this invention is limited to the above-disclosed basic functional modules just because this embodiment only discloses a few basic functional modules.

[0101] On the other hand, this application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0102] The memory stores a computer program that, when executed by a processor, causes the processor to perform the steps of the method.

[0103] On the other hand, this application provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of the method.

[0104] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0105] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetically switched memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms. The databases involved in the embodiments provided in this application can include at least one of relational and non-relational databases. Non-relational databases can include blockchain-based distributed databases, etc., and are not limited thereto. The processors involved in the various embodiments provided in this application may be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited thereto.

[0106] A simulation platform, comprising:

[0107] An electronic device for implementing the steps of the method;

[0108] A processor that runs a program, which, when running, executes the steps of the method claimed in the electronic device from data output by the program.

[0109] A storage medium for storing a program that, when run, executes the steps of the method on data output from an electronic device.

[0110] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0111] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method of calculating a mounting pre-tightening amount of a transmission bearing, characterized by, The method comprises the following steps: S1: based on the pre-defined material properties, a finite element grid model of the transmission housing and shaft is constructed by a finite element simulation software; the material properties include the elastic modulus, Poisson's ratio and thermal expansion coefficient of the transmission housing and shaft; S2: based on the actual working conditions of the transmission assembly life simulation analysis, the finite element grid model of the transmission housing and shaft is imported into the pre-constructed multi-body dynamics simulation model of the transmission housing, and is connected with the transmission components in the multi-body dynamics simulation model; S3: the detection object and the design variable are set, and a target mapping curve of the detection object and the design variable is obtained by adopting a preset strategy.

2. The method of claim 1, wherein, The step S2 comprises: Based on the actual working conditions of the transmission assembly life simulation analysis, the temperature parameters are pre-configured; The temperature parameters at least include: the initial environmental temperature of the transmission assembly, the temperatures of the housing, the shaft, the inner and outer rings of the bearing, the rolling body and the lubricating oil; wherein, based on the actual working conditions, the configuration of the temperature parameters needs to meet the following design when the transmission assembly is running: Bearing roller temperature > inner ring temperature > shaft temperature > bearing outer ring temperature > housing temperature = oil temperature.

3. The method of claim 2, wherein, The step S3, setting the detection object and the design variable, adopting a preset strategy, obtaining a target mapping curve of the detection object and the design variable, specifically comprises: The tolerance fitting parameters of the bearing installation in the simulation model are pre-configured; wherein, the bearing service time is taken as the detection object, and the pre-tightening amount is taken as the design variable; Wherein, the maximum interference amount based on the installation tolerance fitting is determined as the pre-tightening amount generated by the design variable.

4. The method of claim 3, wherein, The step S3, setting the detection object and the design variable, adopting a preset strategy, obtaining a target mapping curve of the detection object and the design variable, further comprises: Taking the design variable as a variable, a first group of DOE simulation models is constructed based on the pre-configured first configuration parameters, and an initial mapping curve of the detection object and the design variable is output through the first group of DOE simulation models; wherein, the first configuration parameters include a first preset range and a first simulation step of the design variable; Based on the initial mapping curve of the detection object and the design variable, the curve interval corresponding to the maximum value of the detection object is obtained as a key interval; Taking the key interval as a simulation range, a second group of DOE simulation models is obtained by adjusting the first configuration parameters, and a target mapping curve of the detection object and the design variable is output through the second group of DOE simulation models.

5. The method of claim 3, wherein, The step S3, setting the detection object and the design variable, adopting a preset strategy, obtaining a target mapping curve of the detection object and the design variable, specifically further comprises: Taking the design variable as a variable, a first group of coupled DOE simulation models is constructed based on the pre-configured multi-physical field coupling first configuration parameters, taking the design variable as a reference and taking the key variable as an interactive variable; an initial mapping curve of the detection object and the design variable is output through the first group of coupled DOE simulation models, and a thermal mapping curve of the design variable, the key variable and the detection object is synchronously generated; wherein, the key variable is load, housing temperature and thermal deformation amount of the housing and shaft corresponding to different loads; Based on the initial mapping curve and the thermal mapping curve, a dynamic key interval corresponding to a maximum value of the detection object is determined, a first configuration parameter is adjusted by an adaptive step iteration algorithm in a simulation domain of the dynamic key interval; Through a structure and thermal coupling correction module, contact stress changes corresponding to design variables are input to a temperature field simulation to correct material properties of the key interval, and a second group of DOE simulation models are constructed based on the corrected material properties; A target mapping curve of the detection object and the design variables, an optimal pre-tightening amount, and a key variable constraint relationship table are output by the second group of DOE models.

6. The method of claim 5, wherein, The adaptive step iteration algorithm adjusts the first configuration parameter, and specifically includes: A second simulation step is generated based on a curvature change rate of the initial curve.

7. A transmission bearing mounting pre-tightening amount calculation method system characterized by, The system includes: A first simulation module configured to construct a finite element grid model of the transmission shell and the shaft based on pre-defined material properties by using a finite element simulation software; the material properties include elastic modulus, Poisson's ratio, and thermal expansion coefficient of the transmission shell and the shaft; A second simulation module configured to import the finite element grid model of the transmission shell and the shaft into a pre-constructed multi-body dynamics simulation model of the transmission shell based on actual working conditions of a transmission assembly life simulation analysis, and to establish node connection between the finite element grid model and transmission components in the multi-body dynamics simulation model; A strategy module configured to set the detection object and the design variables, and to obtain a target mapping curve of the detection object and the design variables by using a pre-set strategy.

8. An electronic device comprising: A processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; and the memory stores a computer program, which, when executed by the processor, causes the processor to execute steps of the method in any one of claims 1-6. 9.A computer readable storage medium storing a computer program executable by an electronic device, the computer program comprising instructions for causing the electronic device to perform the method of any one of claims 1 to 8. When the computer program runs on the electronic device, the electronic device executes steps of the method in any one of claims 1-6.

10. An emulation platform, characterized by The electronic device is configured to execute steps of the method in any one of claims 1-6. The processor is configured to execute steps of the method in any one of claims 1-6 when a program runs. The storage medium is configured to store the program, which, when executed, executes steps of the method in any one of claims 1-6 for data output from the electronic device. ​

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