Spline-neutral optimization methods, systems, electronic devices, and storage media

Abstract

This invention discloses a spline alignment optimization method, system, electronic device, and storage medium. The spline alignment optimization method includes: establishing a three-dimensional model of the electric drive system assembly; defining and creating a measurement target for the coaxiality of the motor rotor shaft spline and the reducer input shaft spline; creating a tolerance analysis model using three-dimensional dimensional chain calculations; defining the assembly dimensional chain; configuring component tolerances; performing tolerance analysis to determine the dimensional tolerances that have a significant impact on coaxiality and their contribution; and optimizing the tolerances with high contribution within the allowable range of the process to improve spline alignment. This invention solves the technical problems of complex spline alignment calculations and high manual computation requirements.

Description

Technical Field

[0001] This invention relates to the field of electric drive system technology, and more specifically, to a spline alignment optimization method, system, electronic device, and storage medium. Background Technology

[0002] With the rapid development of new energy vehicle technology, the market share of pure electric vehicles is increasing day by day. As the core powertrain of new energy vehicles, one of the core attractions of the electric drive system is its excellent NVH characteristics. However, with the development of electric drive technology, higher speeds and more demanding operating conditions pose greater challenges to the NVH characteristics of the electric drive system. Clunk noise is a common problem in electric drive systems. Today, as customers pay more attention to ride comfort, the proportion of market problems caused by clutch noise is rising year by year. There are many influencing factors, making analysis and solutions very difficult, and thus it has become one of the most important issues for OEMs. In the process of analyzing and solving the clutch problem, it was found that in addition to spline wear, the alignment of the spline between the motor rotor shaft and the reducer input shaft is also an important influencing factor. Poor alignment will lead to uneven wear, which will aggravate spline wear, and will also increase the load on the bearing, causing bearing damage. Furthermore, because the spline alignment dimension chain is long and the calculation is complex, the amount of manual calculation is huge. Summary of the Invention

[0003] This invention provides a spline alignment optimization method, system, electronic device, and storage medium to at least solve the technical problems of complex spline alignment calculation and large amount of manual computation.

[0004] According to one aspect of the present invention, a spline alignment optimization method is provided, comprising: establishing a three-dimensional model of an electric drive system assembly, the three-dimensional model including a motor housing, a motor rotor shaft, a reducer input shaft, front and rear reducer housings, bearings, and cylindrical pin components; defining and creating a measurement target, the measurement target being the coaxiality of the spline of the motor rotor shaft and the spline of the reducer input shaft; creating a tolerance analysis model of the electric drive system assembly using a three-dimensional dimensional chain calculation method; defining an assembly dimensional chain according to the actual assembly sequence of the electric drive system; configuring the tolerances of each component in the assembly dimensional chain; performing tolerance analysis, setting the analysis target to a 3σ range, and obtaining the analysis results; reviewing the analysis results, determining the dimensional tolerances that have a significant impact on coaxiality and their contribution, and optimizing the tolerances with high contribution within the allowable range of the process to improve spline alignment.

[0005] Optionally, the 3D model can be built using pre-set 3D design software, which has accurate tolerance analysis and dimensional chain calculation functions.

[0006] Optionally, the steps for obtaining part information include reading the geometric parameters and tolerance information of the motor housing, motor rotor shaft, and reducer input shaft components from the design documents.

[0007] Optionally, the geometric tolerances introduced in the tolerance analysis model include, but are not limited to, the positional tolerance of the motor rotor shaft spline, and the roundness and cylindricity of the reducer input shaft spline.

[0008] Optionally, in the tolerance optimization step, the maximum and minimum coaxiality deviations within the tolerance range are determined by analyzing statistical results, and the tolerances with high contribution are optimized.

[0009] Optionally, the steps to optimize tolerances with high contribution also include considering the impact of the assembly tolerances of the motor housing and the front and rear housings of the reducer on spline alignment.

[0010] Optionally, tolerance adjustments within the allowable range of the process can be made by obtaining actual process capability parameters through communication with the manufacturing department to determine the adjustable tolerance range.

[0011] Optionally, the tolerance configuration of the bearing bore diameter and the locating pin hole position is optimized based on the tolerance allocation principle and bearing assembly requirements.

[0012] Optionally, in the step of optimizing the tolerance with high contribution within the limits allowed by the process, the effect of the optimized tolerance on the neutrality of the spline pair can be verified by experimental data.

[0013] Optionally, the implementation strategy for tolerance analysis includes using Monte Carlo simulation methods to evaluate the probability distribution of spline pair neutrality in order to identify the key tolerances that need to be optimized.

[0014] Optionally, in the step of optimizing the tolerances with high contribution within the limits allowed by the process, the manufacturing feasibility under different tolerance settings can be analyzed using process simulation tools.

[0015] Optionally, the steps to optimize tolerances with high contribution also include evaluating the comprehensive impact of the optimized tolerances on the overall system performance to ensure the comprehensiveness and effectiveness of the optimization scheme.

[0016] According to another aspect of the present invention, a spline alignment optimization system is also provided, comprising: a first construction module for establishing a three-dimensional model of an electric drive system assembly, the three-dimensional model including a motor housing, a motor rotor shaft, a reducer input shaft, front and rear reducer housings, bearings, and cylindrical pin components; a first definition module for defining and creating a measurement target, the measurement target being the coaxiality of the spline of the motor rotor shaft and the spline of the reducer input shaft; a second construction module for creating a tolerance analysis model of the electric drive system assembly using a three-dimensional dimensional chain calculation method; a second definition module for defining an assembly dimensional chain according to the actual assembly sequence of the electric drive system; a configuration module for configuring the tolerances of each component in the assembly dimensional chain; an analysis module for performing tolerance analysis, setting the analysis target to a 3σ range, and obtaining the analysis results; and a results module for viewing the analysis results, determining the dimensional tolerances that have a significant impact on coaxiality and their contribution, and optimizing the tolerances with high contribution within the allowable range of the process to improve spline alignment.

[0017] According to another aspect of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the spline neutrality optimization method described in any of the preceding embodiments.

[0018] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the storage medium is located to execute the spline alignment optimization method described in any of the preceding embodiments.

[0019] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the spline alignment optimization method described in any of the preceding embodiments.

[0020] In this embodiment of the invention, a three-dimensional model of the electric drive system assembly is established. This three-dimensional model includes a motor housing, a motor rotor shaft, a reducer input shaft, front and rear reducer housings, bearings, and cylindrical pin components. A measurement target is defined and created, which is the coaxiality of the splines on the motor rotor shaft and the reducer input shaft. A tolerance analysis model of the electric drive system assembly is created using a three-dimensional dimensional chain calculation method. An assembly dimensional chain is defined according to the actual assembly sequence of the electric drive system. Tolerances for each component in the assembly dimensional chain are configured. Tolerance analysis is performed, with the analysis target set to a 3σ range, and the analysis results are obtained. The analysis results are reviewed to determine the dimensional tolerances that have a significant impact on coaxiality and their contribution. Within the allowable range of the process, tolerances with high contribution are optimized to improve spline alignment. The method provided by this invention can significantly improve the assembly accuracy of electric drive system assemblies, reduce mechanical vibration and noise caused by poor spline alignment, and extend the service life of the system. At the same time, through the tolerance analysis function of 3D design software, the key factors affecting spline alignment can be identified more intuitively, guiding the process department to optimize tolerances. Thus, while ensuring product quality, manufacturing costs are reduced and production efficiency is improved, providing strong technical support for the design and manufacturing of electric drive systems in the field of electric vehicles. This solves the technical problems of complex spline alignment calculation and large amount of manual calculation. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0022] Figure 1 This is a flowchart of a spline neutrality optimization method according to one embodiment of the present invention;

[0023] Figure 2 This is a structural block diagram of a spline neutrality optimization system according to one embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] According to an embodiment of the present invention, an embodiment of a spline-alignment optimization method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0027] Figure 1 This is a flowchart of a spline neutrality optimization method according to one embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0028] Step S101: Establish a three-dimensional model of the electric drive system assembly. The three-dimensional model includes components such as the motor housing, motor rotor shaft, reducer input shaft, reducer front and rear housings, bearings, and cylindrical pins.

[0029] Step S102: Define and create a measurement target, which is the coaxiality of the motor rotor shaft spline and the reducer input shaft spline.

[0030] Step S103: Using the three-dimensional dimensional chain calculation method, a tolerance analysis model of the electric drive system assembly is created.

[0031] Step S104: Define the assembly dimension chain according to the actual assembly sequence of the electric drive system.

[0032] Step S105: Configure the tolerances for each component in the assembly dimension chain.

[0033] Step S106: Perform tolerance analysis, set the analysis target to a 3σ range, and obtain the analysis results.

[0034] Step S107: Review the analysis results, identify the dimensional tolerances that have a significant impact on coaxiality and their contribution, and optimize the tolerances with high contribution within the limits allowed by the process to improve spline alignment.

[0035] In this embodiment of the invention, a three-dimensional model of the electric drive system assembly is established. This three-dimensional model includes a motor housing, a motor rotor shaft, a reducer input shaft, front and rear reducer housings, bearings, and cylindrical pin components. A measurement target is defined and created, which is the coaxiality of the splines on the motor rotor shaft and the reducer input shaft. A tolerance analysis model of the electric drive system assembly is created using a three-dimensional dimensional chain calculation method. An assembly dimensional chain is defined according to the actual assembly sequence of the electric drive system. Tolerances for each component in the assembly dimensional chain are configured. Tolerance analysis is performed, with the analysis target set to a 3σ range, and the analysis results are obtained. The analysis results are reviewed to determine the dimensional tolerances that have a significant impact on coaxiality and their contribution. Within the allowable range of the process, tolerances with high contribution are optimized to improve spline alignment. The method provided by this invention can significantly improve the assembly accuracy of electric drive system assemblies, reduce mechanical vibration and noise caused by poor spline alignment, and extend the service life of the system. At the same time, through the tolerance analysis function of 3D design software, the key factors affecting spline alignment can be identified more intuitively, guiding the process department to optimize tolerances. Thus, while ensuring product quality, manufacturing costs are reduced and production efficiency is improved, providing strong technical support for the design and manufacturing of electric drive systems in the field of electric vehicles. This solves the technical problems of complex spline alignment calculation and large amount of manual calculation.

[0036] Optionally, the 3D model is built using specific 3D design software with precise tolerance analysis and dimensional chain calculation capabilities. This functionality allows for virtual assembly of the electric drive system assembly, identifying potential assembly problems in advance and enabling adjustments during the design phase. This avoids rework due to assembly issues in later production, saving time and costs. This technology also has broad application prospects in the aerospace and precision machinery manufacturing fields.

[0037] Optionally, the steps for obtaining part information include reading the geometric parameters and tolerance information of the motor housing, motor rotor shaft, and reducer input shaft components from design documents. Accurate acquisition of this information is fundamental for tolerance analysis and ensures the reliability of the analysis results. In automobile manufacturing and the production of industrial automation equipment, such precise tolerance control is crucial for improving product consistency and reducing failure rates.

[0038] Optionally, the geometrical tolerances introduced into the tolerance analysis model include, but are not limited to, the positional tolerance of the motor rotor shaft spline and the roundness and cylindricity of the reducer input shaft spline. The introduction of these geometrical tolerances makes the analysis model more realistic, enabling more accurate prediction of spline alignment issues. This helps to address potential manufacturing challenges during the design phase, improves the assembly accuracy of the electric drive system, reduces mechanical vibration and noise, and extends the system's service life.

[0039] Optionally, in the tolerance optimization step, the maximum and minimum coaxiality deviations within the tolerance range are determined by analyzing statistical results, thereby optimizing tolerances with high contribution. This statistically-based optimization method can adjust tolerances more scientifically, ensuring the stability and consistency of the electric drive system in mass production. In the manufacturing of precision instruments and high-end electronic equipment, the application of this method can significantly improve product quality and market competitiveness.

[0040] Optionally, optimizing tolerances that contribute significantly to the overall performance can also include considering the impact of assembly tolerances of the motor housing and the front and rear housings of the reducer on spline alignment. By comprehensively considering various tolerances during the assembly process, the combined impact of spline alignment can be more accurately assessed, contributing to the optimal design of the electric drive system. In the design of robot joints and precision transmission devices, such comprehensive tolerance considerations can significantly improve the system's accuracy and reliability.

[0041] Optionally, tolerance adjustments within the allowable range of the process are made by obtaining actual process capability parameters through communication with the manufacturing department to determine the adjustable tolerance range. This tolerance adjustment based on actual process capability ensures the feasibility of the design and avoids production problems caused by mismatch between design and manufacturing capabilities. In the manufacturing of automotive parts and aerospace equipment, the application of this method can effectively improve production efficiency and reduce production costs.

[0042] Optionally, the tolerance configuration of the bearing bore diameter and locating pin hole position is optimized based on tolerance allocation principles and bearing assembly requirements. By optimizing these key tolerances, the assembly accuracy of the electric drive system can be significantly improved, performance degradation caused by tolerance accumulation can be reduced, and the system's service life can be extended. In the manufacturing of high-speed rotating equipment and precision transmission devices, the application of this tolerance optimization technology can significantly improve product performance and reliability.

[0043] Optionally, within the limits of process allowances, in the step of optimizing tolerances with high contribution, the impact of optimized tolerances on spline neutrality can be verified through experimental data. This verification method based on experimental data ensures the effectiveness of the optimization scheme and avoids design errors caused by inconsistencies between theoretical analysis and actual production. In the production of new energy vehicles and industrial automation equipment, the application of this method can significantly improve product quality and market competitiveness.

[0044] Optionally, tolerance analysis implementation strategies include using Monte Carlo simulation methods to evaluate the probability distribution of spline alignment in order to identify critical tolerances that need optimization. This probability distribution-based tolerance analysis strategy can more scientifically identify key factors affecting spline alignment, guiding designers to optimize tolerances and improve the assembly accuracy and reliability of electric drive systems. In the manufacturing of precision machinery and high-end electronic equipment, the application of this method can significantly improve product quality and market competitiveness.

[0045] Optionally, in the step of optimizing high-contribution tolerances within the limits of process allowance, the manufacturing feasibility under different tolerance settings can be analyzed using process simulation tools to ensure that the optimized tolerances meet production requirements. This tolerance optimization strategy based on process simulation can ensure the feasibility and production efficiency of the optimization scheme, avoiding production problems caused by unreasonable tolerance settings. In the fields of automobile manufacturing and precision machining, the application of this method can significantly improve production efficiency and reduce production costs.

[0046] Optionally, optimizing tolerances with high contribution also includes assessing the comprehensive impact of the optimized tolerances on the overall system performance to ensure the comprehensiveness and effectiveness of the optimization scheme. By comprehensively evaluating the impact of the optimized tolerances on the overall system performance, optimal design of the electric drive system can be ensured, improving system stability and reliability. In the design and manufacturing of new energy vehicles and industrial automation equipment, the application of this method can significantly improve product performance and market competitiveness.

[0047] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device) to execute the methods described in the various embodiments of the present invention.

[0048] This invention also provides a spline alignment optimization system for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0049] Figure 2This is a structural block diagram of a spline alignment optimization system 200 according to one embodiment of the present invention, as shown below. Figure 2 As shown, the device includes: a first construction module 201, used to establish a three-dimensional model of the electric drive system assembly, the three-dimensional model including the motor housing, motor rotor shaft, reducer input shaft, reducer front and rear housings, bearings, and cylindrical pin components; a first definition module 202, used to define and create a measurement target, the measurement target being the coaxiality of the spline of the motor rotor shaft and the spline of the reducer input shaft; a second construction module 203, used to create a tolerance analysis model of the electric drive system assembly using a three-dimensional dimensional chain calculation method; a second definition module 204, used to define an assembly dimensional chain according to the actual assembly sequence of the electric drive system; a configuration module 205, used to configure the tolerances of each component in the assembly dimensional chain; an analysis module 206, used to perform tolerance analysis, setting the analysis target to a 3σ range, and obtaining the analysis results; and a results module 207, used to view the analysis results, determine the dimensional tolerances that have a significant impact on coaxiality and their contribution, and optimize the tolerances with high contribution within the allowable range of the process to improve spline alignment.

[0050] It should be noted that the above modules are also used to assist in implementing the following embodiments:

[0051] Optionally, the 3D model is built using specific 3D design software with precise tolerance analysis and dimensional chain calculation capabilities. This functionality allows for virtual assembly of the electric drive system assembly, identifying potential assembly problems in advance and enabling adjustments during the design phase. This avoids rework due to assembly issues in later production, saving time and costs. This technology also has broad application prospects in the aerospace and precision machinery manufacturing fields.

[0052] Optionally, the steps for obtaining part information include reading the geometric parameters and tolerance information of the motor housing, motor rotor shaft, and reducer input shaft components from design documents. Accurate acquisition of this information is fundamental for tolerance analysis and ensures the reliability of the analysis results. In automobile manufacturing and the production of industrial automation equipment, such precise tolerance control is crucial for improving product consistency and reducing failure rates.

[0053] Optionally, the geometrical tolerances introduced into the tolerance analysis model include, but are not limited to, the positional tolerance of the motor rotor shaft spline and the roundness and cylindricity of the reducer input shaft spline. The introduction of these geometrical tolerances makes the analysis model more realistic, enabling more accurate prediction of spline alignment issues. This helps to address potential manufacturing challenges during the design phase, improves the assembly accuracy of the electric drive system, reduces mechanical vibration and noise, and extends the system's service life.

[0054] Optionally, in the tolerance optimization step, the maximum and minimum coaxiality deviations within the tolerance range are determined by analyzing statistical results, thereby optimizing tolerances with high contribution. This statistically-based optimization method can adjust tolerances more scientifically, ensuring the stability and consistency of the electric drive system in mass production. In the manufacturing of precision instruments and high-end electronic equipment, the application of this method can significantly improve product quality and market competitiveness.

[0055] Optionally, optimizing tolerances that contribute significantly to the overall performance can also include considering the impact of assembly tolerances of the motor housing and the front and rear housings of the reducer on spline alignment. By comprehensively considering various tolerances during the assembly process, the combined impact of spline alignment can be more accurately assessed, contributing to the optimal design of the electric drive system. In the design of robot joints and precision transmission devices, such comprehensive tolerance considerations can significantly improve the system's accuracy and reliability.

[0056] Optionally, tolerance adjustments within the allowable range of the process are made by obtaining actual process capability parameters through communication with the manufacturing department to determine the adjustable tolerance range. This tolerance adjustment based on actual process capability ensures the feasibility of the design and avoids production problems caused by mismatch between design and manufacturing capabilities. In the manufacturing of automotive parts and aerospace equipment, the application of this method can effectively improve production efficiency and reduce production costs.

[0057] Optionally, the tolerance configuration of the bearing bore diameter and locating pin hole position is optimized based on tolerance allocation principles and bearing assembly requirements. By optimizing these key tolerances, the assembly accuracy of the electric drive system can be significantly improved, performance degradation caused by tolerance accumulation can be reduced, and the system's service life can be extended. In the manufacturing of high-speed rotating equipment and precision transmission devices, the application of this tolerance optimization technology can significantly improve product performance and reliability.

[0058] Optionally, within the limits of process allowances, in the step of optimizing tolerances with high contribution, the impact of optimized tolerances on spline neutrality can be verified through experimental data. This verification method based on experimental data ensures the effectiveness of the optimization scheme and avoids design errors caused by inconsistencies between theoretical analysis and actual production. In the production of new energy vehicles and industrial automation equipment, the application of this method can significantly improve product quality and market competitiveness.

[0059] Optionally, tolerance analysis implementation strategies include using Monte Carlo simulation methods to evaluate the probability distribution of spline alignment in order to identify critical tolerances that need optimization. This probability distribution-based tolerance analysis strategy can more scientifically identify key factors affecting spline alignment, guiding designers to optimize tolerances and improve the assembly accuracy and reliability of electric drive systems. In the manufacturing of precision machinery and high-end electronic equipment, the application of this method can significantly improve product quality and market competitiveness.

[0060] Optionally, in the step of optimizing high-contribution tolerances within the limits of process allowance, the manufacturing feasibility under different tolerance settings can be analyzed using process simulation tools to ensure that the optimized tolerances meet production requirements. This tolerance optimization strategy based on process simulation can ensure the feasibility and production efficiency of the optimization scheme, avoiding production problems caused by unreasonable tolerance settings. In the fields of automobile manufacturing and precision machining, the application of this method can significantly improve production efficiency and reduce production costs.

[0061] Optionally, optimizing tolerances with high contribution also includes assessing the comprehensive impact of the optimized tolerances on the overall system performance to ensure the comprehensiveness and effectiveness of the optimization scheme. By comprehensively evaluating the impact of the optimized tolerances on the overall system performance, optimal design of the electric drive system can be ensured, improving system stability and reliability. In the design and manufacturing of new energy vehicles and industrial automation equipment, the application of this method can significantly improve product performance and market competitiveness.

[0062] Embodiments of the present invention also provide an electronic device, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the spline neutrality optimization method described in any of the above embodiments during runtime.

[0063] Optionally, in this embodiment, the processor in the above-described electronic device can be configured to run an executable program to perform the following steps:

[0064] Step S101: Establish a three-dimensional model of the electric drive system assembly. The three-dimensional model includes the motor housing, motor rotor shaft, reducer input shaft, reducer front and rear housings, bearings, and cylindrical pin components.

[0065] Step S102: Define and create a measurement target, which is the coaxiality of the motor rotor shaft spline and the reducer input shaft spline.

[0066] Step S103: Using the three-dimensional dimensional chain calculation method, a tolerance analysis model of the electric drive system assembly is created.

[0067] Step S104: Define the assembly dimension chain according to the actual assembly sequence of the electric drive system.

[0068] Step S105: Configure the tolerances for each component in the assembly dimension chain.

[0069] Step S106: Perform tolerance analysis, set the analysis target to a 3σ range, and obtain the analysis results.

[0070] Step S107: Review the analysis results, identify the dimensional tolerances that have a significant impact on coaxiality and their contribution, and optimize the tolerances with high contribution within the limits allowed by the process to improve spline alignment.

[0071] Optionally, the 3D model is built using specific 3D design software that has precise tolerance analysis and dimensional chain calculation capabilities.

[0072] Optionally, the steps for obtaining part information include reading the geometric parameters and tolerance information of the motor housing, motor rotor shaft, and reducer input shaft components from the design documents.

[0073] Optionally, the geometric tolerances introduced in the tolerance analysis model include, but are not limited to, the positional tolerance of the motor rotor shaft spline, and the roundness and cylindricity of the reducer input shaft spline.

[0074] Optionally, in the tolerance optimization step, the maximum and minimum coaxiality deviations within the tolerance range are determined by analyzing statistical results, thereby optimizing the tolerances with high contribution.

[0075] Optionally, the steps to optimize tolerances with high contribution also include considering the impact of the assembly tolerances of the motor housing and the front and rear housings of the reducer on spline alignment.

[0076] Optionally, tolerance adjustments within the allowable range of the process can be made by obtaining actual process capability parameters through communication with the manufacturing department to determine the adjustable tolerance range.

[0077] Optionally, the tolerance configuration of the bearing bore diameter and the locating pin hole position is optimized based on the tolerance allocation principle and bearing assembly requirements.

[0078] Optionally, in the step of optimizing the tolerance with high contribution within the limits allowed by the process, the effect of the optimized tolerance on the neutrality of the spline pair can be verified by experimental data.

[0079] Optionally, the implementation strategy for tolerance analysis includes using Monte Carlo simulation methods to evaluate the probability distribution of spline pair neutrality in order to identify the key tolerances that need to be optimized.

[0080] Optionally, in the step of optimizing the tolerance with high contribution within the range allowed by the process, the manufacturing feasibility under different tolerance settings can be analyzed by process simulation tools to ensure that the optimized tolerance meets production requirements.

[0081] Optionally, the steps to optimize tolerances with high contribution also include evaluating the comprehensive impact of the optimized tolerances on the overall system performance to ensure the comprehensiveness and effectiveness of the optimization scheme.

[0082] Embodiments of the present invention also provide a computer-readable storage medium comprising a stored executable program, wherein, when the executable program is executed, it controls the device where the storage medium is located to perform the spline alignment optimization method described in any of the above embodiments.

[0083] Optionally, in this embodiment, the executable program can be configured to store an executable program for performing the following steps:

[0084] Step S101: Establish a three-dimensional model of the electric drive system assembly. The three-dimensional model includes the motor housing, motor rotor shaft, reducer input shaft, reducer front and rear housings, bearings, and cylindrical pin components.

[0085] Step S102: Define and create a measurement target, which is the coaxiality of the motor rotor shaft spline and the reducer input shaft spline.

[0086] Step S103: Using the three-dimensional dimensional chain calculation method, a tolerance analysis model of the electric drive system assembly is created.

[0087] Step S104: Define the assembly dimension chain according to the actual assembly sequence of the electric drive system.

[0088] Step S105: Configure the tolerances for each component in the assembly dimension chain.

[0089] Step S106: Perform tolerance analysis, set the analysis target to a 3σ range, and obtain the analysis results.

[0090] Step S107: Review the analysis results, identify the dimensional tolerances that have a significant impact on coaxiality and their contribution, and optimize the tolerances with high contribution within the limits allowed by the process to improve spline alignment.

[0091] Optionally, the 3D model is built using specific 3D design software that has precise tolerance analysis and dimensional chain calculation capabilities.

[0092] Optionally, the steps for obtaining part information include reading the geometric parameters and tolerance information of the motor housing, motor rotor shaft, and reducer input shaft components from the design documents.

[0093] Optionally, the geometric tolerances introduced in the tolerance analysis model include, but are not limited to, the positional tolerance of the motor rotor shaft spline, and the roundness and cylindricity of the reducer input shaft spline.

[0094] Optionally, in the tolerance optimization step, the maximum and minimum coaxiality deviations within the tolerance range are determined by analyzing statistical results, thereby optimizing the tolerances with high contribution.

[0095] Optionally, the steps to optimize tolerances with high contribution also include considering the impact of the assembly tolerances of the motor housing and the front and rear housings of the reducer on spline alignment.

[0096] Optionally, tolerance adjustments within the allowable range of the process can be made by obtaining actual process capability parameters through communication with the manufacturing department to determine the adjustable tolerance range.

[0097] Optionally, the tolerance configuration of the bearing bore diameter and the locating pin hole position is optimized based on the tolerance allocation principle and bearing assembly requirements.

[0098] Optionally, in the step of optimizing the tolerance with high contribution within the limits allowed by the process, the effect of the optimized tolerance on the neutrality of the spline pair can be verified by experimental data.

[0099] Optionally, the implementation strategy for tolerance analysis includes using Monte Carlo simulation methods to evaluate the probability distribution of spline pair neutrality in order to identify the key tolerances that need to be optimized.

[0100] Optionally, in the step of optimizing the tolerance with high contribution within the range allowed by the process, the manufacturing feasibility under different tolerance settings can be analyzed by process simulation tools to ensure that the optimized tolerance meets production requirements.

[0101] Optionally, the steps to optimize tolerances with high contribution also include evaluating the comprehensive impact of the optimized tolerances on the overall system performance to ensure the comprehensiveness and effectiveness of the optimization scheme.

[0102] Embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the spline neutrality optimization method described in any of the above embodiments.

[0103] Optionally, in this embodiment, the computer program, when executed by the processor, performs the following steps:

[0104] Step S101: Establish a three-dimensional model of the electric drive system assembly. The three-dimensional model includes the motor housing, motor rotor shaft, reducer input shaft, reducer front and rear housings, bearings, and cylindrical pin components.

[0105] Step S102: Define and create a measurement target, which is the coaxiality of the motor rotor shaft spline and the reducer input shaft spline.

[0106] Step S103: Using the three-dimensional dimensional chain calculation method, a tolerance analysis model of the electric drive system assembly is created.

[0107] Step S104: Define the assembly dimension chain according to the actual assembly sequence of the electric drive system.

[0108] Step S105: Configure the tolerances for each component in the assembly dimension chain.

[0109] Step S106: Perform tolerance analysis, set the analysis target to a 3σ range, and obtain the analysis results.

[0110] Step S107: Review the analysis results, identify the dimensional tolerances that have a significant impact on coaxiality and their contribution, and optimize the tolerances with high contribution within the limits allowed by the process to improve spline alignment.

[0111] Optionally, the 3D model is built using specific 3D design software that has precise tolerance analysis and dimensional chain calculation capabilities.

[0112] Optionally, the steps for obtaining part information include reading the geometric parameters and tolerance information of the motor housing, motor rotor shaft, and reducer input shaft components from the design documents.

[0113] Optionally, the geometric tolerances introduced in the tolerance analysis model include, but are not limited to, the positional tolerance of the motor rotor shaft spline, and the roundness and cylindricity of the reducer input shaft spline.

[0114] Optionally, in the tolerance optimization step, the maximum and minimum coaxiality deviations within the tolerance range are determined by analyzing statistical results, thereby optimizing the tolerances with high contribution.

[0115] Optionally, the steps to optimize tolerances with high contribution also include considering the impact of the assembly tolerances of the motor housing and the front and rear housings of the reducer on spline alignment.

[0116] Optionally, tolerance adjustments within the allowable range of the process can be made by obtaining actual process capability parameters through communication with the manufacturing department to determine the adjustable tolerance range.

[0117] Optionally, the tolerance configuration of the bearing bore diameter and the locating pin hole position is optimized based on the tolerance allocation principle and bearing assembly requirements.

[0118] Optionally, in the step of optimizing the tolerance with high contribution within the limits allowed by the process, the effect of the optimized tolerance on the neutrality of the spline pair can be verified by experimental data.

[0119] Optionally, the implementation strategy for tolerance analysis includes using Monte Carlo simulation methods to evaluate the probability distribution of spline pair neutrality in order to identify the key tolerances that need to be optimized.

[0120] Optionally, in the step of optimizing the tolerance with high contribution within the range allowed by the process, the manufacturing feasibility under different tolerance settings can be analyzed by process simulation tools to ensure that the optimized tolerance meets production requirements.

[0121] Optionally, the steps to optimize tolerances with high contribution also include evaluating the comprehensive impact of the optimized tolerances on the overall system performance to ensure the comprehensiveness and effectiveness of the optimization scheme.

[0122] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0123] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0124] In the embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0125] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0126] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0127] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0128] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A spline-pair neutrality optimization method, characterized in that, include: A three-dimensional model of the electric drive system assembly is established, which includes the motor housing, motor rotor shaft, reducer input shaft, reducer front and rear housings, bearings, and cylindrical pin components. Define and create a measurement target, which is the coaxiality of the motor rotor shaft spline and the reducer input shaft spline; A tolerance analysis model for the electric drive system assembly was created using a three-dimensional dimensional chain calculation method. Define the assembly dimension chain according to the actual assembly sequence of the electric drive system; Configure the dimensional tolerances of each component in the assembly dimension chain; Tolerance analysis is performed, with the analysis target set as a 3σ range, and the analysis results are obtained. The analysis results are used to represent the degree of influence of each component on coaxiality. Review the analysis results and identify the components whose impact exceeds the 3σ range from the aforementioned components; Within the limits allowed by the process, optimize the dimensional tolerances of components whose influence exceeds the 3σ range to improve spline alignment.

2. The spline neutrality optimization method according to claim 1, characterized in that, The three-dimensional model is built using a pre-set three-dimensional design software, which has precise tolerance analysis and dimensional chain calculation functions.

3. The spline neutrality optimization method according to claim 1, characterized in that, The steps to obtain part information include reading the geometric parameters and tolerance information of the motor housing, motor rotor shaft, and reducer input shaft components from the design documents.

4. The spline neutrality optimization method according to claim 1, characterized in that, The geometric tolerances introduced in the tolerance analysis model include, but are not limited to, the positional tolerance of the motor rotor shaft spline, and the roundness and cylindricity of the reducer input shaft spline.

5. The spline neutrality optimization method according to claim 1, characterized in that, In the step of dimensional tolerance optimization, the maximum and minimum coaxiality deviations within the tolerance range are determined by analyzing statistical results, and the dimensional tolerances of components whose influence exceeds the 3σ range are optimized.

6. The spline neutrality optimization method according to claim 1, characterized in that, The step of optimizing the dimensional tolerances of components whose influence exceeds the 3σ range also includes considering the influence of the assembly tolerances of the motor housing and the front and rear housings of the reducer on the spline alignment.

7. The spline neutrality optimization method according to claim 1, characterized in that, The tolerance adjustment within the allowable range of the process is determined by obtaining actual process capability parameters through communication with the manufacturing department.

8. The spline neutrality optimization method according to claim 1, characterized in that, The dimensional tolerances of each component in the assembly dimension chain include: tolerance configuration for bearing hole diameter and locating pin hole position based on tolerance allocation principles and bearing assembly requirements.

9. The spline neutrality optimization method according to claim 1, characterized in that, In the step of optimizing the dimensions of components whose influence exceeds 3σ within the range allowed by the process, the effect of the optimized tolerance on the neutrality of the spline is verified by experimental data.

10. The spline neutrality optimization method according to claim 1, characterized in that, The tolerance analysis implementation strategy includes: using Monte Carlo simulation methods to evaluate the probability distribution of spline pair neutrality and identify the key tolerances that need to be optimized.

11. The spline neutrality optimization method according to claim 1, characterized in that, In the step of optimizing the dimensional tolerances of components whose influence exceeds 3σ within the range allowed by the process, the manufacturing feasibility under different tolerance settings is analyzed using process simulation tools.

12. A spline-pair neutral optimization system, characterized in that, include: The first building module is used to create a three-dimensional model of the electric drive system assembly. This three-dimensional model includes the motor housing, motor rotor shaft, reducer input shaft, reducer front and rear housings, bearings, and cylindrical pin components. The first definition module is used to define and create the measurement target, which is the coaxiality of the spline of the motor rotor shaft and the spline of the reducer input shaft. The second building module is used to create a tolerance analysis model of the electric drive system assembly using a three-dimensional dimensional chain calculation method. The second definition module is used to define the assembly dimension chain according to the actual assembly sequence of the electric drive system; The configuration module is used to configure the dimensional tolerances of each component in the assembly dimension chain. The analysis module is used to perform tolerance analysis, setting the analysis target to a 3σ range, and obtaining analysis results, wherein the analysis results are used to represent the degree of influence of each component on coaxiality; The results module is used to view the analysis results and identify components whose influence exceeds the 3σ range from the various components; within the limits allowed by the process, the dimensional tolerances of the components whose influence exceeds the 3σ range are optimized to improve spline alignment.

13. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 1 to 11.

15. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 11.

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