Optimization Design Method, Device and Medium for Support Structure of Permanent Magnet Synchronous Motor

Abstract

The present invention discloses an optimized design method, device and medium for the support structure of a permanent magnet synchronous motor, which relates to the technical field of motor structure optimization, and includes: selecting a support structure according to the motor application scenario; calling an initial support model and a standard motor model; importing the initial support model and the standard motor model into the application scenario finite element model; extracting the typical working condition combinations of the motor application scenario to obtain a test working condition combination; performing dynamic working condition simulation and extracting the distribution of weak areas; performing performance iterative optimization on the distribution of weak areas; and performing structural lightweight optimization in the low stress area to obtain a lightweight support structure. The present invention solves the technical problems existing in the prior art, such as weak working condition adaptability, insufficient reliability, structural redundancy and high cost of the support structure of the permanent magnet synchronous motor, and achieves the technical effects of performance improvement and structural lightweight of the support structure of the permanent magnet synchronous motor under multiple working conditions, effectively enhancing the structural reliability and reducing the material cost.

Description

Technical Field

[0001] The present invention relates to the technical field of motor structure optimization, and particularly to an optimized design method, device and medium for the support structure of a permanent magnet synchronous motor. Background Art

[0002] With the continuous improvement of the performance requirements for permanent magnet synchronous motors in fields such as commercial aerospace, new energy vehicles, and industrial automation, the design of their support structures directly affects the operation stability and service life of the motors. In the prior art, the support structures of permanent magnet synchronous motors often have problems of poor working condition adaptability, being difficult to cope with complex and changeable operating environments, resulting in rapid performance degradation under the coupling action of multiple physical fields; at the same time, due to the lack of targeted optimized design, there is generally redundancy in the structure, which not only causes material waste but also increases production costs, and cannot meet the requirements of modern industry for efficient and economic design.

[0003] The prior art has technical problems such as weak working condition adaptability, insufficient reliability, structural redundancy and high cost of the support structure of permanent magnet synchronous motors. Summary of the Invention

[0004] The present application provides an optimized design method, device and medium for the support structure of a permanent magnet synchronous motor, which are used to solve the technical problems of weak working condition adaptability, insufficient reliability, structural redundancy and high cost of the support structure of permanent magnet synchronous motors in the prior art.

[0005] In view of the above problems, the present application provides an optimized design method, device and medium for the support structure of a permanent magnet synchronous motor.

[0006] In the first aspect of the embodiments of the present application, an optimized design method for the support structure of a permanent magnet synchronous motor is provided, and the method includes:

[0007] Select a support structure according to the motor application scenario to obtain an initial support structure; call an initial support model and a standard motor model according to the design parameters of the permanent magnet synchronous motor and the initial support structure; after performing finite element modeling on the motor application scenario on a simulation platform, import the initial support model and the standard motor model into the application scenario finite element model by using multi-physical field coupling; after extracting the typical working condition combinations of the motor application scenario, obtain a test working condition combination through perturbation expansion; perform dynamic working condition simulation on the application scenario finite element model by using the test working condition combination, and identify and extract the distribution of weak areas; perform performance iterative optimization of the distribution of the weak areas on the application scenario finite element model by using local structure replacement to obtain a reference support model; starting from the reference support model, perform structural lightweight optimization in the low stress area of the application scenario finite element model to obtain a lightweight support structure.

[0008] In the second aspect of the embodiments of the present application, the present application provides an electronic device, which includes: a processor; a memory for storing executable instructions of the processor; wherein, the processor is used to execute the method for optimizing the design of the support structure of the permanent magnet synchronous motor provided by the present application.

[0009] In the third aspect of the embodiments of the present application, the present application provides a computer-readable storage medium storing a computer program for executing the method for optimizing the design of the support structure of the permanent magnet synchronous motor provided by the present application.

[0010] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0011] Select a support structure according to the motor application scenario to obtain an initial support structure; call the initial support model and the standard motor model; after performing finite element modeling on the motor application scenario on the simulation platform, import the initial support model and the standard motor model into the application scenario finite element model; after extracting the typical working condition combinations of the motor application scenario, obtain the test working condition combinations through perturbation expansion; perform dynamic working condition simulation on the application scenario finite element model to identify and extract the distribution of weak areas; use local structure replacement to perform performance iterative optimization on the distribution of weak areas in the application scenario finite element model to obtain a reference support model; perform structural lightweight optimization in the low stress area of the application scenario finite element model to obtain a lightweight support structure. It achieves the technical effects of improving the performance of the permanent magnet synchronous motor support structure under multiple working conditions and lightweighting the structure, effectively enhancing the structural reliability and reducing the material cost. Description of the Drawings

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0013] Figure 1 It is a schematic flow chart of the method for optimizing the design of the support structure of the permanent magnet synchronous motor provided by the embodiments of the present application;

[0014] Figure 2 It is a schematic structural diagram of an electronic device provided by the present application.

[0015] Description of the reference numerals: Processor 21, Memory 22, Input device 23, Output device 24. Detailed Description of the Embodiments

[0016] The present application provides an optimized design method, device and medium for the support structure of a permanent magnet synchronous motor, which is used to solve the technical problems of weak working condition adaptability, insufficient reliability, structural redundancy and high cost of the support structure of the permanent magnet synchronous motor in the prior art.

[0017] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0018] Embodiment 1, as Figure 1 shown, the present application provides an optimized design method for the support structure of a permanent magnet synchronous motor, and the method includes:

[0019] Step S100: Select a support structure according to the motor application scenario to obtain an initial support structure.

[0020] Specifically, based on the real-time usage requirements of the permanent magnet synchronous motor, the application scenario is accurately classified to clarify the specific application scenario of the motor. Subsequently, the associated index rules are called according to the application scenario, and the application scenario and the index association rules are used as retrieval conditions to extract the corresponding associated working condition parameter indexes from the local database. Next, the key installation space geometric constraints are extracted from the accommodation space characteristics of the application scenario, which include information such as the installation space shape, installation space size, motor installation position and installation boundary conditions, and at the same time, the support node coordinate set of the permanent magnet synchronous motor is locally called. The installation boundary of the support structure is fitted according to the installation space geometric constraints. On this basis, the support structure is screened in combination with the support node coordinate set to obtain multiple support geometric structures. The main working condition scenario is clarified through the main working condition analysis, and the main support structure is matched. With the installation boundary conditions as constraints, according to the installation space shape, size and motor installation position, the space volume utilization rate of multiple support geometric structures is calculated, and after arranging them in ascending order of the volume utilization rate, the initial geometric structure is extracted with the main support structure as the screening condition. Finally, material matching is performed according to the associated working condition parameter indexes to obtain the initial material information, and the initial geometric structure and the initial material information are fused to obtain the initial support structure that meets the preliminary requirements of the application scenario.

[0021] Step S200: Call the initial support model and the standard motor model according to the design parameters of the permanent magnet synchronous motor and the initial support structure.

[0022] Specifically, after completing the selection of the initial support structure, comprehensively sort out the design parameters of the permanent magnet synchronous motor and the selected initial support structure. These parameters cover key information such as the size specifications, power rating, torque characteristics, number of pole pairs of the motor, and the shape, size, and material properties of the initial support structure. Based on these detailed parameters, conduct accurate retrieval in the model library. Among them, the initial support model is a digital model corresponding to the current initial support structure design, which completely presents the structural characteristics such as the geometric shape and connection method of the support structure; the standard motor model is a permanent magnet synchronous motor model that conforms to industry standards or general design specifications, including important attributes such as the electromagnetic characteristics and mechanical properties of the motor. By calling these two models and using them as the basis for subsequent in-depth analysis and simulation, it provides strong data and model support for building a more realistic model on the simulation platform and then carrying out operations such as finite element modeling and multi-physics field coupling analysis, ensuring that the optimized design of the permanent magnet synchronous motor support structure can be based on an accurate and reliable model.

[0023] Step S300: After performing finite element modeling on the motor application scenario on the simulation platform, import the initial support model and the standard motor model into the application scenario finite element model using multi-physics field coupling.

[0024] Specifically, carry out finite element modeling work for the motor application scenario on the simulation platform. Based on the detailed information of the motor application scenario obtained previously, such as the operating environment and working conditions, construct a finite element model that can accurately reflect the actual situation. After completing the modeling, perform the import operation of the initial support model and the standard motor model. Before import, according to the initial material information of the initial support structure, assign corresponding attributes to the initial support model. At the same time, use the support node coordinate set as the coordinate system alignment benchmark to align and assemble the initial support model and the standard motor model to ensure the accuracy of their relative positions and connection relationships. Then, import the aligned and assembled initial support model and standard motor model into the application scenario finite element model according to the installation boundary of the support structure. To improve the accuracy of model simulation, adopt a refined mesh division strategy: locally encrypt the mesh of the initial support model using a hexahedron-dominated mesh, and perform swept mesh layering processing on the motor air gap region, strictly controlling the mesh size ≤ 0.5 mm and the thickness of the first boundary layer ≤ 0.02 mm. Finally, adopt an electromagnetic-force-thermal full-coupling mapping strategy to achieve the synchronous solution of multi-physics fields and the transfer of boundary conditions for the application scenario finite element model, enabling the model to more realistically simulate the multi-physics field interaction situation of the motor during actual operation and providing a solid model foundation for subsequent work such as locating weak areas through simulation analysis and optimizing the performance of the support structure.

[0025] Step S400: After extracting the typical working condition combinations of the motor application scenario, obtain the test working condition combinations through perturbation expansion.

[0026] Specifically, from the numerous working conditions involved in the motor application scenarios, representative working conditions are selected based on the associated working condition parameter indicators collected in the early stage and the actual operation experience. These working conditions are reasonably combined to extract the typical working condition combinations of the motor application scenarios. These typical working condition combinations cover the working states of the motor under normal operation, common load changes, etc. Then, in order to more comprehensively simulate the operation of the motor in a complex actual environment, the extracted typical working condition combinations are perturbed and expanded. By introducing various possible small changes on the basis of the typical working conditions, such as small random fluctuations in parameters such as the load size, operating speed, and ambient temperature in the working conditions, various uncertain factors and interferences that the motor may encounter during actual operation are simulated. After such perturbation and expansion operations, a test working condition combination covering more operation possibilities is obtained. This test working condition combination can more comprehensively and meticulously reflect the working states of the motor under various potential conditions, providing rich and diverse test conditions for subsequent dynamic working condition simulation of the application scenario finite element model using these working condition combinations, and then more accurately identifying and extracting the distribution of weak areas in the model.

[0027] Step S500: Use the test working condition combination to perform dynamic working condition simulation on the application scenario finite element model, and identify and extract the distribution of weak areas.

[0028] Specifically, first, the test condition combinations are serialized according to the power characteristics, and each condition is arranged in an orderly manner according to the power magnitude or the power change trend. Subsequently, these conditions are smoothly connected to make the transition between conditions more natural and avoid sudden changes, thereby obtaining a smoothed ascending condition sequence. This sequence can more realistically simulate the gradual change of the working conditions of the motor during actual operation. Then, the smoothed ascending condition sequence is input into the application scenario finite element model, and dynamic simulation configuration is performed to generate a dynamic simulation task queue. This queue sequentially executes the simulation tasks under each condition in a certain order to ensure the systematicness and accuracy of the simulation process. To improve the calculation efficiency, the powerful ability of HPC cluster distributed computing is utilized to perform parallel processing on the dynamic simulation task queue, thereby quickly obtaining multiple thermo-mechanical coupling response fields corresponding to multiple simulated conditions in the smoothed ascending condition sequence. These response fields reflect the distribution and changes of physical quantities such as heat and force of the motor and its support structure under different conditions. Then, based on the pre-set weak stress conditions, grid-level multi-criterion fusion analysis is performed on multiple thermo-mechanical coupling response fields. This means starting from the grid level and comprehensively considering multiple judgment bases such as stress, strain, and displacement to more accurately determine which grid regions have potential weak problems. Through this multi-criterion fusion analysis, multiple grid distributions are output, and these grid distributions preliminarily identify the possible weak regions. Finally, in order to obtain a continuous and complete weak region distribution, the multiple output grid distributions are spatially aligned to eliminate the position deviation caused by calculation errors or model differences. On this basis, morphological closing operation is adopted to connect adjacent weak grids, so that the scattered weak grids form a coherent region, thereby successfully generating a clear and accurate weak region distribution. These weak region distributions provide a key basis for subsequent targeted optimization and improvement of the support structure.

[0029] Step S600: Use local structure replacement to perform performance iterative optimization of the weak region distribution in the application scenario finite element model to obtain a benchmark support model.

[0030] Specifically, after determining the distribution of weak areas in the application scenario finite element model, first, according to the extracted distribution of weak areas, calculate the peak stress, average strain, and fatigue damage factor for each of the P weak areas respectively, and output P weak sensitivities, where P is a positive integer. Sort the P weak areas from high to low according to the weak sensitivities, and select the top M areas with high sensitivities as high-priority replacement areas, because these areas have a greater impact on the performance of the support structure, and optimizing them first can more significantly improve the overall performance, where M is a positive integer and P≥M. Then, call the M sets of replacement structure type designs corresponding to these M high-priority replacement areas in the replacement structure library, and perform parametric modeling on them to generate M sets of replacement CAD templates. Enumerate the permutations and combinations of these M sets of replacement CAD templates to obtain a large number of candidate replacement combination sets. For each candidate replacement combination, perform local structure iterative replacement on the corresponding weak area in the initial support model. After each replacement, input the previously obtained smoothed ascending working condition sequence into the application scenario finite element model for dynamic simulation, and then obtain multiple combined performance indicators, which reflect the performance of the support structure after replacement from different aspects. Next, use the preset performance weight configuration to comprehensively evaluate the multiple combined performance indicators. This weight configuration is set in advance according to the performance focus of the support structure, such as paying more attention to structural strength, stability, or fatigue life, etc. Through evaluation, select the target replacement combination with the optimal performance from the candidate replacement combination set. Finally, use the target replacement combination to perform local structure replacement on the initial support model. After this series of operations, a benchmark support model with better performance is obtained, laying a foundation for further optimizing the support structure in the future.

[0031] Step S700: Starting from the benchmark support model, perform structural lightweight optimization in the low-stress area of the application scenario finite element model to obtain a lightweight support structure.

[0032] Specifically, the reference support model is replaced into the application scenario finite element model, and based on the high safety margin stress conditions, the grid-level multi-criterion fusion analysis algorithm is used to deeply analyze the reference support model. During the analysis process, various factors such as stress, strain, and displacement are comprehensively considered, and Q high safety margin regions are accurately output, where Q is a positive integer. These regions have the potential for lightweight design while ensuring the structural safety. Then, according to the characteristics of these high safety margin regions, Q sets of lightweight structure designs that are adapted to them are called from the lightweight structure library. These Q sets of lightweight structure designs are sequentially applied to the application scenario finite element model, and dynamic simulation is carried out. During the simulation process, according to the weak stress conditions, the weak region recurrence judgment is performed on the model after each application, that is, to check whether the lightweight design will cause new weak regions to appear, so as to obtain Q weak recurrence judgment results. Then, according to these judgment results, R sets of lightweight structure designs that will not cause new weak regions are selected from the Q sets of lightweight structure designs. For these R sets of lightweight structure designs, production lightweight processing backtracking is carried out, and by calculating factors such as material cost and processing complexity, R lightweight costs are obtained, where R is a positive integer, and Q≥R. Subsequently, the R lightweight costs are serialized and arranged in ascending order of cost. According to the sorting result, the target lightweight structure design with the best cost-benefit is selected from the R sets of lightweight structure designs. Finally, the target lightweight structure design is used to perform structural lightweight compensation on the reference support model, that is, on the basis of not affecting the performance and safety of the support structure, the low stress area of the reference support model is optimized and improved, redundant materials are removed or the structure form is adjusted, and finally a support structure that meets the lightweight requirements is obtained. This lightweight support structure not only reduces its own weight, but also helps to improve the overall performance and operating efficiency of the permanent magnet synchronous motor, reduce energy consumption, and ensure stable and reliable operation under various working conditions.

[0033] In a possible implementation manner, step S500 further includes:

[0034] Step S510: After serializing the test condition combinations according to the power characteristics, perform smooth connection of the test condition combinations to obtain a smoothed ascending test condition sequence.

[0035] Step S520: Input the smoothed ascending test condition sequence into the application scenario finite element model for dynamic simulation configuration to obtain a dynamic simulation task queue.

[0036] Step S530: Perform HPC cluster distributed computing on the dynamic simulation task queue to obtain multiple thermo-mechanical coupling response fields corresponding to multiple simulation conditions in the smoothed ascending test condition sequence.

[0037] Step S540: Based on the weak stress condition, perform grid-level multi-criterion fusion analysis on the multiple thermo-mechanical coupling response fields, and output multiple grid distributions.

[0038] Step S550: After spatially aligning the multiple grid distributions, connect adjacent weak grids by using morphological closing operation to generate the weak area distribution.

[0039] Specifically, extract two key power characteristics, i.e., thermal power and mechanical power, for each working condition in the test working condition combination. Based on these two power characteristics, construct a comprehensive power index (weighted sum of thermal power and mechanical power), and then use a sorting algorithm (such as quicksort) to serialize the test working condition combination in ascending order according to the comprehensive power index, so that each working condition shows an increasing power arrangement. Then, in order to make the transition between working conditions more natural and smooth, use an interpolation algorithm for smooth connection of working conditions. For two adjacent working conditions, according to their power characteristics and other relevant operating parameters, use an interpolation algorithm (such as linear interpolation) to generate a series of intermediate working condition points between them. The power and parameter values of these intermediate working condition points will gradually transition with the calculation results of the interpolation algorithm, avoiding sudden changes in working conditions. In this way, all adjacent working conditions are smoothed and connected, and finally a smoothed ascending working condition sequence is obtained. This sequence can more accurately simulate the continuous change of working conditions of the permanent magnet synchronous motor during actual operation, providing a reliable data basis for subsequent more accurate dynamic working condition simulation.

[0040] Convert the data of each working condition in the smoothed ascending working condition sequence into a format that the finite element model of the application scenario can recognize. For example, map parameters such as power and speed in the working condition to the corresponding physical quantity input interface of the model. Then, start the dynamic simulation configuration process in the finite element software platform. For the setting of the time step, use an adaptive time step algorithm to automatically adjust the step size according to the severity of the working condition change. When the working condition changes slowly, use a larger step size to improve the calculation efficiency, and when the change is severe, use a smaller step size to ensure the simulation accuracy. In the selection of the solver, according to the characteristics of the model and the computing resources, if the model scale is small and the accuracy requirement is extremely high, select a direct solver; if the model scale is large, use an iterative solver. At the same time, use an optimization algorithm to fine-tune the parameters of the solver to improve the solving efficiency and stability. For the setting of boundary conditions and initial conditions, according to the environmental parameters and the initial state of the motor in the working condition sequence, automatically generate the corresponding boundary condition and initial condition files and import them into the finite element model. After the above configuration is completed, according to the order of the smoothed ascending working condition sequence, generate corresponding simulation tasks for each working condition. These tasks contain information such as working condition data, simulation parameters, boundary conditions, and initial conditions, and finally form an ordered dynamic simulation task queue waiting for subsequent calculation execution.

[0041] Submit the dynamic simulation task queue to the HPC cluster. The job scheduling system of the HPC cluster will reasonably allocate tasks to different nodes according to the resource status of each computing node (such as CPU usage, available memory, etc.). After each node receives a task, it reads the finite element model data of the application scenario related to the task and the corresponding working condition information in the smoothed ascending working condition sequence from the storage system. Based on the given database DB= , where L is the index number used to distinguish the stress field, strain field, and temperature field under different working conditions. The computing node performs thermo-mechanical coupling calculations on the finite element model for each working condition. During the calculation, the change of the working condition is simulated by iteratively solving the heat conduction equation and the mechanical equilibrium equation. For example, the heat conduction equation is solved according to Fourier's law to determine the temperature field distribution, and Hooke's law, etc. is used to solve the mechanical equilibrium equation to obtain the stress field and strain field. The node updates the numerical values of each field in real time during the calculation to simulate the real physical response of the motor under the working condition. After each computing node completes the calculation, it transmits the thermo-mechanical coupling response data such as the stress field, strain field, and temperature field under the corresponding working condition back to the storage system. After sorting and integrating, multiple thermo-mechanical coupling response fields corresponding to multiple simulated working conditions in the smoothed ascending working condition sequence are finally obtained, providing basic data for subsequent work such as analyzing weak areas based on these response fields.

[0042] Define the weak stress conditions, which are a series of stress thresholds and related constraint conditions determined based on factors such as the design requirements of the motor, material properties, and actual operation experience. Subsequently, grid-level multi-criterion fusion analysis is carried out for multiple thermo-mechanical coupling response fields. In each thermo-mechanical coupling response field, the model is divided into numerous small grid units, and for each grid unit, multiple criteria are comprehensively considered for evaluation. These criteria may include but are not limited to stress amplitude, stress change rate, coupling effect of thermal stress and mechanical stress, etc. For example, when the stress amplitude of a certain grid unit exceeds the stress threshold in the weak stress conditions, or its stress change rate is abnormally high, and at the same time the coupling effect of thermal stress and mechanical stress significantly affects the mechanical properties of this area, it is marked as a potential weak area. During the analysis, corresponding weights are assigned to each criterion to reflect its importance in judging weak areas. Through weighted calculation, the evaluation results of multiple criteria are fused to obtain the comprehensive evaluation score of each grid unit. According to the comprehensive evaluation score, it is determined whether each grid unit belongs to a weak area. Finally, based on the analysis results of each thermo-mechanical coupling response field, multiple grid distributions are output, which clearly identify the areas in the motor model where potential weak problems may exist under different simulated working conditions, providing accurate target areas for subsequent optimization of the support structure.

[0043] Multiple grid distributions obtained through multi-criterion fusion analysis may have deviations in spatial positions. Therefore, spatial alignment operations need to be carried out first. Using a spatial coordinate transformation algorithm, with a certain fixed reference coordinate system as the benchmark, the spatial positions of each grid distribution are calibrated to ensure that the grid distributions under different working conditions can accurately correspond in space and eliminate the recognition errors caused by position deviations. After completing the spatial alignment, in order to obtain continuous and complete weak areas, morphological closing operations are used to process adjacent weak grids. Morphological closing operations consist of two basic operations: dilation and erosion. First, dilation operations are performed on the weak grids. By increasing the boundary range of the weak grids, adjacent weak grids that are close but not connected are connected, and the tiny gaps between them are filled. Then, erosion operations are carried out to remove the redundant boundary parts generated by dilation, making the shape of the finally obtained weak area more regular. After such morphological closing operation processing, the originally scattered weak grids are effectively connected, thus generating a clear and complete weak area distribution, providing an intuitive and accurate basis for the subsequent optimization of the support structure.

[0044] In a possible implementation manner, step S600 further includes:

[0045] Step S610: Calculate and output P weak sensitivities based on the P peak stresses, P average strains, and P fatigue damage factors of the P weak areas extracted from the obtained weak area distribution.

[0046] Step S620: Arrange the P weak areas in descending order according to the P weak sensitivities to extract the first M high-priority replacement areas before sorting.

[0047] Step S630: After calling the M groups of replacement structure types of the M high-priority replacement areas in the replacement structure library for design, perform parametric modeling to obtain M groups of replacement CAD templates.

[0048] Step S640: Enumerate the M groups of replacement CAD templates in permutations and combinations to generate a candidate replacement combination set.

[0049] Step S650: After performing local structure iterative replacement of the initial support model using the candidate replacement combination set, input the smoothed ascending working condition sequence into the application scenario finite element model for dynamic simulation to obtain multiple combined performance indicators.

[0050] Step S660: Perform performance comprehensive evaluation of the multiple combined performance indicators using a preset performance weight configuration, and extract the target replacement combination from the candidate replacement combination set according to the evaluation results.

[0051] Step S670: Perform local structure replacement of the initial support model using the target replacement combination to obtain the benchmark support model.

[0052] Specifically, based on the obtained weak area distribution, the calculation of weak sensitivity is carried out. First, the P weak areas in the distribution are analyzed, where P is a positive integer, and the key parameters corresponding to each weak area, namely, peak stress, average strain and fatigue damage factor, are accurately extracted. These three parameters reflect the mechanical properties and damage degree of the weak area from different angles. Subsequently, in order to comprehensively consider the influence of these three parameters on the weak area, the weighted summation calculation method is used to determine the weak sensitivity of each weak area. Pre-set weights are assigned to the peak stress, average strain and fatigue damage factor, respectively. These weights are determined according to the actual application scenarios, design requirements and the importance of each parameter in affecting the structural performance of the permanent magnet synchronous motor support structure. By multiplying the peak stress, average strain and fatigue damage factor of each weak area with the corresponding weights, and then adding the results, the weak sensitivity of the weak area is obtained. After calculating the P weak areas one by one, P weak sensitivities are finally output.

[0053] By arranging these sensitivity values in descending order, the high priority replacement areas are screened, and the P weak areas are arranged in order from large to small according to their weak sensitivity, so that the weak areas with high sensitivity are at the front of the sequence. Since the higher the weak sensitivity value, the greater the negative impact of the area on the overall performance of the supporting structure, the M weak areas in the front are selected as high priority replacement areas, where M is a positive integer and P ≥ M.

[0054] According to the specific characteristics and optimization requirements of these high-priority replacement areas, we go deep into the replacement structure library for precise matching. The replacement structure library reserves a rich variety of structural design solutions, covering different geometric types such as stiffeners, fillet transitions, lattice fillings, and various material types such as titanium alloys and carbon fiber composites. By comparing the stress distribution, space constraints and other factors of the region, M groups of replacement structure type designs corresponding to M high-priority replacement areas are retrieved from the library. After obtaining a suitable design solution, parametric modeling begins. With the help of CAD software, parametric modeling defines key parameters in structural design (such as the size of stiffeners, the radius of fillet transitions, the density of lattice filling, and the various physical properties of the selected materials) as flexibly adjustable variables. These parameters can be adjusted and optimized according to actual engineering requirements and performance indicators. The software will automatically update the geometry and physical properties of the model according to the pre-set parameter association rules, and quickly generate an accurate three-dimensional model. After a series of parameter adjustments and model optimization, M groups of replacement CAD templates were successfully obtained.

[0055] After obtaining M sets of replacement CAD templates, all possible structural replacement schemes are explored by means of permutation and combination enumeration. Regarding the M sets of templates as independent element sets, the full permutation and combination algorithm is adopted to exhaustively list different usage scenarios of each set of templates. Starting from using only 1 set of templates for local replacement, to using 2 sets, 3 sets in combination, and finally using all M sets of templates simultaneously, every possible combination method and replacement order are considered. During the enumeration process, in order to ensure the integrity and accuracy of the scheme, each combination is numbered and recorded, generating a series of candidate replacement schemes. These schemes cover the possibilities of structural modification in different degrees and different combination forms, and finally are integrated to form a candidate replacement combination set.

[0056] Each combination scheme is successively selected from the candidate replacement combination set to perform iterative replacement of the local structure of the initial support model. Each replacement precisely applies the CAD template in the combination scheme to the high-priority replacement area corresponding to the initial support model to simulate different structural improvement methods. After completing a replacement operation, the previously obtained smoothed ascending working condition sequence is input into the finite element model of the application scenario. This finite element model can accurately simulate various physical phenomena of the permanent magnet synchronous motor support structure during actual operation. It will perform dynamic simulation on the replaced support model according to different working conditions in the smoothed ascending working condition sequence, such as changes in thermal power, mechanical power, etc. During the dynamic simulation process, the finite element model will simulate the mechanical response and thermal response of the support structure under different working conditions. Through the analysis and processing of the simulation results, multiple key combined performance indicators are extracted, such as the maximum stress reduction of the structure, fatigue life gain, total cost, production time consumption, etc. These performance indicators comprehensively reflect the impact of each candidate replacement combination scheme on the performance of the support structure under different working conditions. The above-mentioned replacement, simulation, and indicator extraction processes are repeated for each combination scheme in the candidate replacement combination set, and finally multiple combined performance indicators are obtained.

[0057] After obtaining multiple combined performance indicators, comprehensive evaluation and screening are carried out on each combination scheme through a preset performance weight configuration. The preset performance weight configuration is an importance parameter set in advance for different performance indicators based on the actual application requirements of the permanent magnet synchronous motor support structure. For example, a higher weight is given to the maximum stress index reflecting structural strength, and a relatively lower weight is assigned to secondary indicators such as heat dissipation efficiency, so as to reflect the priority of different performances in the overall design goal. For each combination scheme in the candidate replacement combination set, its corresponding multiple combined performance indicators are weighted and calculated with the preset weights. If the performance indicator set of a certain combination scheme is , and the corresponding preset weight set is , then the comprehensive evaluation score S of this combination scheme = × , where S represents the comprehensive evaluation score of the combined solution, and n represents the total number of performance indicators of the combined solution. represents the specific value of the i-th combined performance indicator. is the preset weight corresponding to the i-th performance indicator. In this way, each combined solution is quantitatively scored. The higher the score, the better the solution performs in meeting the comprehensive performance requirements. After scoring all combined solutions, the candidate replacement combination set is sorted according to the scores, and the combination with the highest score is selected as the target replacement combination. Based on considering multiple performance requirements such as structural strength, durability, and heat dissipation, the target replacement combination achieves the optimal balance of the support structure performance and will be used as the core solution for subsequent improvement of the initial support model.

[0058] After determining the target replacement combination, it is applied to the initial support model to complete the structural optimization. According to the high-priority replacement areas corresponding to each replacement CAD template in the target replacement combination, the corresponding parts are accurately located in the initial support model. Using 3D modeling software or CAD tools, the structural design in the template is precisely embedded into the initial model to replace the original weak structural parts. During the replacement process, the design specifications and assembly requirements are strictly followed to ensure the connection accuracy and structural integrity between the new structure and other parts of the original model. After the replacement, through geometric repair, detail improvement, etc., the overall structure of the model becomes more smooth and reasonable, and finally the reference support model is obtained.

[0059] In a possible implementation manner, step S700 further includes:

[0060] Step S710: After replacing the reference support model into the application scenario finite element model, perform grid-level multi-criterion fusion analysis on the reference support model based on the high safety margin stress condition, and output Q high safety margin regions.

[0061] Step S720: Call Q groups of lightweight structure designs for the Q high safety margin regions in the lightweight structure library.

[0062] Step S730: After performing dynamic simulation on the Q groups of lightweight structure designs in the application scenario finite element model, perform weak area recurrence judgment based on the weak stress condition to obtain Q weak recurrence judgment results.

[0063] Step S740: Extract R groups of lightweight structure designs from the Q groups of lightweight structure designs according to the Q weak recurrence judgment results.

[0064] Step S750: Perform production lightweight processing backtracking according to the R groups of lightweight structure designs to obtain R lightweight costs.

[0065] Step S760: Serialize the R lightweight costs, and extract the target lightweight structural design from the R groups of lightweight structural designs according to the sorting result.

[0066] Step S770: Perform structural lightweight compensation on the benchmark support model using the target lightweight structural design to obtain the benchmark support model.

[0067] Specifically, after replacing the benchmark support model into the application scenario finite element model, taking the pre-set high safety margin stress condition as the evaluation benchmark, carry out grid-level multi-criterion fusion analysis work. Perform fine meshing on the benchmark support model and disassemble the model into a large number of tiny grid elements. For each grid element, extract key parameters from multiple dimensions for evaluation. The criteria cover stress amplitude, stress concentration factor, fatigue life prediction value, and the degree of plastic deformation of the material, etc. For example, obtain the stress amplitude of each grid element under different working conditions through finite element calculation and compare it with the stress threshold in the high safety margin stress condition; calculate the stress concentration factor by combining theoretical formulas with the geometric characteristics of the model to judge the stress concentration risk in the local area; predict the fatigue life based on the S-N curve of the material and the cyclic load condition; judge whether the material is close to the yield state by analyzing the plastic strain data. To comprehensively consider the influence of each criterion on the structural safety, according to engineering experience and structural design requirements, assign corresponding weights to each criterion. Use the weighted summation method to perform fusion calculation on the evaluation results of each criterion for each grid element to obtain a comprehensive evaluation value. Set the threshold standard of the high safety margin, screen out the grid elements with a comprehensive evaluation value higher than the threshold, and then use the regional clustering algorithm to aggregate the spatially adjacent and qualified grid elements into one region. After the above processing, finally output Q high safety margin regions, where Q is a positive integer.

[0068] According to the characteristics of the Q high safety margin regions, retrieve in the lightweight structure library and call the Q groups of lightweight structural designs that match them. This library stores a variety of lightweight design schemes, such as hollow design, thin-walled structure, etc., which can adapt to the structural characteristics and mechanical requirements of different regions.

[0069] Import the Q sets of lightweight structure designs called from the lightweight structure library into the finite element model of the application scenario in sequence. For each set of lightweight structure designs, input the smoothed ascending working condition sequence, and use the finite element algorithm to dynamically simulate its operating state under different working conditions, simulate the response process of the structure under the coupling action of multiple physical fields such as heat and force, and obtain data such as the stress distribution, strain change, and temperature field of the structure under each working condition. After the simulation is completed, conduct a detailed analysis of the simulation results according to the preset weak stress conditions. The weak stress conditions include key indicators such as stress thresholds, strain limits, and fatigue damage critical values. Compare the stress, strain, and other data of each grid element obtained in the simulation of each lightweight structure design with the thresholds in the weak stress conditions. If the stress in a certain area exceeds the stress threshold, or the strain reaches the strain limit, or the fatigue damage exceeds the critical value, it is determined that there is a weak situation in that area. For each set of lightweight structure designs, determine whether there are weak areas through the above analysis, so as to obtain Q weak recurrence judgment results.

[0070] After obtaining the Q weak recurrence judgment results, screen out the lightweight design schemes that meet the structural performance requirements. Check each judgment result one by one, and screen out the lightweight structure design schemes whose judgment results are that the weak areas are not reproduced. These schemes mean that in the dynamic simulation of the finite element model of the application scenario, when evaluated based on the weak stress conditions, their structural performance is good, and there are no weak situations such as stress concentration and excessive strain that may lead to structural failure. By traversing and screening the Q judgment results, finally extract R sets of lightweight structure designs that meet the requirements, where R is a positive integer and Q≥R.

[0071] After determining the R sets of lightweight structure designs, analyze each of the R sets of lightweight structure designs according to the production process database. First, for each design scheme, clarify the types, specifications, and usage amounts of the raw materials required, and calculate the raw material costs in combination with the current market price data; secondly, judge the required processing processes according to the structural complexity of the design scheme, such as 3D printing, numerical control machining, casting, etc., and estimate the processing costs according to the unit working hour costs, equipment loss costs, and processing accuracy requirements of different processes; at the same time, consider other costs such as mold costs, assembly costs, and quality inspection costs that may be involved in the production process. In addition, trace back the historical production data, analyze data such as the material loss rate and scrap rate of similar structure designs in the production process, and correct the cost calculation. By comprehensively considering the above cost factors, calculate the corresponding lightweight costs for each scheme in the R sets of lightweight structure designs, so as to obtain R lightweight cost data. These cost data provide important economic index references for the subsequent selection of the optimal lightweight design scheme, and help to effectively control the production cost on the premise of ensuring the structural performance.

[0072] Sequence the R lightweight costs and use a sorting algorithm (such as quicksort) to sort them from smallest to largest. The solutions with lower costs and meeting the performance requirements are ranked at the front. According to the sorting results, extract the target lightweight structure design with the best combination of cost and performance.

[0073] Apply the target lightweight structure design to the benchmark support model and perform structural lightweight compensation on it. By modifying the geometric shape of the model, adjusting the material distribution, etc., effectively reduce the weight of the model without affecting the key performance of the structure, and finally obtain the benchmark support model optimized by lightweight, achieving the balance between structural performance and cost.

[0074] In a possible implementation manner, step S100 further includes:

[0075] Step S110: Divide the scenario types based on the real-time usage requirements of the permanent magnet synchronous motor to obtain the motor application scenarios.

[0076] Step S120: Invoke the index association rules according to the motor application scenarios, and use the motor application scenarios and index association rules as retrieval conditions to locally extract the associated operating condition parameter indexes.

[0077] Step S130: Select the support structure according to the accommodation space characteristics of the motor application scenarios and the associated operating condition parameter indexes to obtain the initial support structure.

[0078] Specifically, determine the motor application scenarios through in-depth analysis of the real-time usage requirements of the permanent magnet synchronous motor. First, collect various information on the actual application of the motor. For example, in the field of new energy vehicles, it is necessary to pay attention to its range, acceleration performance, etc. requirements, corresponding to the requirements that the motor has high torque density and high efficiency characteristics; in the industrial servo system, focus on the positioning accuracy, response speed, etc. requirements of the motor. Based on these requirement characteristics and combined with the preset scenario division rules, divide the motor application scenarios into different types such as transportation, industrial manufacturing, household appliances, etc. During the division process, use a clustering algorithm to classify the requirement information. When the similarity of a certain type of requirement reaches the set threshold, it is classified into the same application scenario, and finally accurately obtain the motor application scenarios that fit the actual use of the motor.

[0079] After clarifying the motor application scenario, according to the determined motor application scenario, retrieve the corresponding rule sets from the pre-constructed index association rule library. These rule sets are formed based on a large amount of engineering practices and test data, and detail the corresponding relationships between different application scenarios and operating condition parameter indexes. For example, in the application scenario of electric vehicles, the rule sets clearly stipulate that the motor needs to meet specific requirements such as peak torque, continuous power, and speed range. Subsequently, using the motor application scenario and the retrieved index association rules as retrieval conditions, conduct a deep retrieval in the local database. The local database stores a vast amount of data covering various motor parameters. Through an intelligent matching algorithm, screen out the associated operating condition parameter indexes that meet the retrieval conditions from the database. These indexes include not only the electrical parameters (such as voltage, current, power factor) during motor operation, mechanical parameters (such as torque, speed, vibration frequency), but also environmental adaptability parameters (such as operating temperature range, protection level), etc. After precise retrieval and screening, finally extract the complete and accurate associated operating condition parameter indexes.

[0080] Comprehensively consider the accommodation space characteristics of the motor application scenario and the associated operating condition parameter indexes to carry out the selection of the support structure, thereby determining the initial support structure. First, for the accommodation space characteristics of the motor application scenario, analyze its space size, shape, layout, etc. For example, in the compact joint part of an industrial robot, the space is relatively narrow, which requires the support structure to be small and light; while in large wind power generation equipment, the space is relatively spacious, but higher requirements are placed on the stability and load-bearing capacity of the support structure. At the same time, the associated operating condition parameter indexes are also the key basis for selection. Parameters such as the power, speed, and torque of the motor will affect the force and vibration conditions that the support structure needs to bear. High-power and high-speed motors often generate greater vibration and impact forces, which requires the support structure to have sufficient strength and rigidity to ensure the stable operation of the motor. Combining these two factors, screen from a variety of pre-designed support structure types. For example, for a scenario with limited space and large operating condition vibration, select an integrated support structure with good shock absorption performance; for a situation with sufficient space and large load, preferentially consider using a strengthened frame-type support structure. Through comprehensive weighing and comparison, finally determine the initial support structure that is most suitable for the current motor application scenario, laying a foundation for the subsequent stable operation and performance optimization of the motor.

[0081] In a possible implementation manner, step S130 further includes:

[0082] Step S131: Extract the installation space geometric constraints from the accommodation space characteristics, where the installation space geometric constraints include the installation space shape, installation space size, motor installation position, and installation boundary conditions.

[0083] Step S132: Locally call the support node coordinate set of the permanent magnet synchronous motor.

[0084] Step S133: Fit the installation boundary of the support structure according to the geometric constraints of the installation space.

[0085] Step S134: Screen the support structure according to the installation boundary of the support structure and the support node coordinate set to obtain the initial geometric structure.

[0086] Step S135: Perform material matching according to the associated working condition parameter indicators to obtain the initial material information.

[0087] Step S136: Integrate the initial geometric structure and the initial material information to obtain the initial support structure.

[0088] Specifically, systematically deconstruct the accommodation space characteristics of the motor application scenario to extract the geometric constraints of the installation space. First, through methods such as three-dimensional laser scanning and engineering drawing analysis, accurately obtain the three-dimensional shape of the installation space. Whether it is a regular cuboid, cylinder, or complex irregular space, it can be presented as a high-precision geometric model. At the same time, measure the length, width, height and key part dimensions of the installation space to clarify the size boundary of the space. For the motor installation position, according to the overall equipment layout plan, combined with the center of gravity balance and power transmission requirements during motor operation, determine its specific coordinate position in the installation space. The extraction of the installation boundary conditions focuses on the key elements related to the installation of the support structure: on the one hand, determine the fixed interface position to clarify the specific points and connection methods of the support structure connected to the equipment main body and the motor; on the other hand, identify the avoidance area and mark the areas where existing pipelines, components, etc. in the installation space cannot be touched to prevent interference with other components after the support structure is installed. Finally, integrate the installation space shape, size, motor installation position and installation boundary conditions to form the geometric constraints of the installation space, providing an accurate space limit basis for the subsequent support structure design.

[0089] After completing the extraction of the geometric constraints of the installation space, access the local database, which pre-stores various detailed data during the design and manufacturing process of the permanent magnet synchronous motor. Among them, the support node coordinate set, as an important data subset, accurately records the position information of each support point on the motor in three-dimensional space. These support nodes are the key parts where the motor is connected to the support structure, and the accuracy of their positions directly affects the stability and reliability of the motor during operation. Through data retrieval, according to index information such as motor model and specifications, quickly and accurately retrieve the corresponding support node coordinate set.

[0090] Import geometric constraint data such as the shape, size of the installation space, the installation position of the motor, and the installation boundary conditions into professional computer-aided design (CAD) software. For the shape of the installation space, whether it is a regular geometric body or a complex special-shaped structure, NURBS (Non-Uniform Rational B-Spline) curve or surface modeling technology is used to accurately transform it into a digital model. At the same time, according to the installation space size data, the model is scaled and positioned for calibration to ensure complete consistency with the actual space. For the installation position of the motor, the motor contour and key installation points are accurately marked in the space model. For installation boundary conditions such as the position of fixed interfaces and avoidance areas, they are clearly defined by setting special marks in the model, constructing virtual barriers, etc. Then, using the boundary fitting algorithm, based on meeting all geometric constraint conditions, with the goal of optimizing the stability of the support structure and space utilization rate, the possible installation boundaries of the support structure are calculated and adjusted. Through iterative calculations, this algorithm continuously tries different boundary shapes and positions. On the premise of ensuring not exceeding the installation space range, not conflicting with the avoidance area, and being able to stably connect the motor, it generates the most suitable support structure installation boundary contour, laying a foundation for subsequent screening of suitable support structures.

[0091] Carry out the main working condition analysis based on the associated working condition parameters, comprehensively consider various working conditions of the permanent magnet synchronous motor during actual operation, such as different load, speed, temperature conditions, etc., and determine the most representative and influential main working condition scenario from them. Then, for this main working condition scenario, match the main support structure from the pre-set structure type library to find the structural form that can provide the optimal support performance under the main working condition. Subsequently, based on the support structure installation boundary and the support node coordinate set, the existing support structures are preliminarily screened to select multiple support geometric structures that meet the basic requirements in terms of spatial layout and connection method. After that, using the installation boundary conditions as constraints, combined with information such as the shape of the installation space, the size of the installation space, and the installation position of the motor, accurately calculate the space volume utilization rate of these multiple support geometric structures in the installation space. This utilization rate reflects the effective utilization degree of the structure to the space. After the calculation is completed, the multiple support geometric structures are sorted in ascending order according to the space volume utilization rate, and structures with high space utilization efficiency are given priority. Finally, taking the main support structure obtained from the previous matching as the screening condition, structures that not only meet the main working condition performance requirements but also have a high space volume utilization rate are extracted from the sorting result and determined as the initial geometric structure, laying a foundation for subsequent material matching and overall structure design.

[0092] Orienting towards the associated operating condition parameter indicators, match the materials of the support structure. The associated operating condition parameter indicators cover multi-dimensional information such as the load characteristics, operating temperature range, vibration frequency, environmental corrosivity, etc. during the operation of the motor. For example, if the operating condition shows that high-frequency vibrations will occur during the operation of the motor, materials with high damping characteristics will be preferentially screened from the material library; if the motor needs to work continuously in a high-temperature environment, materials with excellent high-temperature resistance properties will be focused on, such as ceramic matrix composites, special alloy steels, etc. By cross-comparing the operating condition parameters with the properties of the materials such as mechanical properties, thermal properties, and chemical stability, and combining factors such as cost and processing technology, the suitable materials are finally determined to obtain the initial material information including the material type, specifications, performance parameters, etc.

[0093] Using 3D modeling software, take the 3D model of the initial geometric structure as the basic framework, and then accurately assign data such as the material type and physical property parameters (such as density, elastic modulus, Poisson's ratio) in the initial material information to each part of the geometric structure in a parametric manner. For example, if the initial material information selects aluminum alloy, the software will automatically associate the material properties of aluminum alloy to the corresponding structural area, making the model possess the mechanical characteristics of the real material. At the same time, according to the processing characteristics of the material (such as the applicability of casting, forging, and machining), optimize the details of the initial geometric structure. For materials suitable for casting processes, adjust details such as the fillet and wall thickness of the structure to avoid casting defects; for materials that need to be machined, optimize the clamping and positioning features of the structure. In addition, considering the overall performance after the combination of the material and the structure, strengthen the design of the key connection parts and stress concentration areas of the structure. Through the above operations, deeply integrate the initial geometric structure with the initial material information to finally form a complete initial support structure that meets the actual engineering requirements.

[0094] In a possible implementation manner, step S134 further includes:

[0095] Step S1341: Conduct a main operating condition analysis based on the associated operating condition parameters to obtain a main operating condition scenario.

[0096] Step S1342: Perform a main support structure matching for the main operating condition scenario.

[0097] Step S1343: Screen the support structure according to the support structure installation boundary and the support node coordinate set to obtain multiple support geometric structures.

[0098] Step S1344: With the installation boundary conditions as constraints, calculate the multiple space volume utilization rates of the multiple support geometric structures according to the installation space shape, installation space size, and motor installation position.

[0099] Step S1345: After arranging the multiple support geometric structures in ascending order according to the multiple space utilization rates, use the main support structure as a screening condition to extract the initial geometric structure from the sorting result.

[0100] Specifically, the main working condition analysis is carried out based on the associated working condition parameters to determine the main working condition scenario. First, collect the associated working condition parameters of the permanent magnet synchronous motor, which cover multi-dimensional data such as power, speed, torque, temperature, vibration frequency, etc. during motor operation, comprehensively reflecting the working state of the motor under different usage scenarios. Then, use the clustering analysis algorithm to classify the working condition data with similar characteristics. For example, the high-speed and high-torque working conditions are classified into one category, and the low-speed and low-load working conditions are classified into another category. Subsequently, combined with engineering practical experience and statistical methods, calculate the probability and duration of each working condition category. For the working condition category with a high occurrence probability, a long duration, and a great impact on the motor performance and support structure design, it is determined as the main working condition scenario. For example, in the application of electric vehicles, the working conditions corresponding to frequent start-up, acceleration, and braking processes are identified as the main working condition scenario because of their high occurrence frequency and high requirements for motor power output.

[0101] For the main working condition scenario, match it from the support structure type library. The type library stores various structural forms such as truss type, frame type, box type, etc. According to the load characteristics, vibration frequency, force direction, etc. requirements under the main working condition scenario, screen out the main support structure that can provide stable support and meet the mechanical performance requirements in this scenario.

[0102] Combined with the space limitation conditions of the support structure installation boundary and the position information of the support node coordinate set, conduct a preliminary screening of all the structures in the support structure library. By comparing whether the structure shape conflicts with the installation boundary and whether the connection points can correspond to the motor support nodes, filter out multiple support geometric structures that meet the basic requirements in terms of spatial layout and connection method.

[0103] Taking the installation boundary conditions as hard constraints, combining the shape, size of the installation space and the motor installation position, calculate the space volume utilization rate of multiple support geometric structures. First, use 3D modeling software to respectively construct the installation space, the motor model and multiple support geometric structures into accurate 3D digital models, clearly presenting their respective shapes and spatial position relationships. Subsequently, based on the installation boundary conditions, clearly define the installable area in the 3D model environment. For each support geometric structure model, obtain its own volume data through the built-in volume calculation function of the software; at the same time, use Boolean operations to calculate the effective space volume actually occupied by the support geometric structure in the installation space. Divide the effective space volume by the volume of the support geometric structure itself to obtain the value of the space volume utilization rate. During the calculation process, fully consider the impact of the motor installation position on space utilization. If there is a spatial conflict between the support geometric structure and the motor installation position, resulting in part of the structure being unable to be installed normally or affecting the operation of the motor, then correct the space volume utilization rate of this structure, deducting the proportion of the unusable space volume. Through the above steps, calculate the accurate space volume utilization rate for each support geometric structure.

[0104] Arrange multiple support geometric structures in ascending order according to the space volume utilization rate, and preferentially retain the structures with high space utilization efficiency. On this basis, take the main support structure as the key screening condition, select the structures that match the main support structure type and have a relatively high space volume utilization rate from the sorting results, and determine them as the initial geometric structures, ensuring that this structure can not only meet the performance requirements of the motor under the main working conditions, but also efficiently utilize the installation space, providing a reliable basis for subsequent material selection and structure optimization.

[0105] In a possible implementation manner, step S300 further includes:

[0106] Step S310: After assigning attributes to the initial support model according to the initial material information, use the support node coordinate set as the coordinate system alignment benchmark to perform the alignment and assembly of the initial support model and the standard motor model.

[0107] Step S320: According to the support structure installation boundary, import the initial support model and the standard motor model in the alignment and assembly state into the application scenario finite element model.

[0108] Step S330: Adopt hexahedron-dominated meshing to locally refine the mesh of the initial support model, and use swept meshing to layer the motor air gap region, where the mesh size ≤ 0.5 mm and the thickness of the first boundary layer ≤ 0.02 mm.

[0109] Step S340: Adopt the electromagnetic-force-thermal full-coupling mapping strategy to perform multi-physical field synchronous solution and boundary condition transfer of the application scenario finite element model.

[0110] Specifically, using computer-aided design (CAD) software, various parameters in the initial material information are assigned to the initial support model, automatically identifying the material type (such as aluminum alloy, alloy steel, etc.), mechanical property parameters (elastic modulus, yield strength, etc.), and thermophysical properties (thermal conductivity, specific heat capacity, etc.) in the initial material information, and corresponding these properties to each component or area of the initial support model one by one, so that the model has the physical characteristics of real materials. After the attribute assignment is completed, the support node coordinate set is used as the benchmark for coordinate system alignment. The support node coordinate set details the precise positions of the key support points on the permanent magnet synchronous motor in three-dimensional space. By reading the coordinate data in the coordinate set, a coordinate system is constructed in the three-dimensional modeling environment, and the initial support model is assembled in alignment with the standard motor model. During the assembly process, an automatic alignment algorithm is used to match the connection points of the initial support model with the motor support node coordinates. By adjusting the position and angle of the model, the connection parts of the two are made to correspond exactly, ensuring the assembly accuracy. At the same time, a visualization tool is used to display the assembly status in real time, enabling the visual inspection of the assembly effect. Manual fine-tuning is performed if necessary, and finally, the precise alignment assembly of the initial support model and the standard motor model is achieved.

[0111] After the precise alignment assembly of the initial support model and the standard motor model is completed, the spatial constraint information defined by the support structure installation boundary is read, including data such as the shape, size, fixed interface position, and avoidance area of the installation space. This information exists in the form of a three-dimensional model or coordinate parameters. Subsequently, through finite element analysis software (such as ANSYS, ABAQUS, etc.), the initial support model and the standard motor model in the alignment assembly state are taken as a complete assembly body and imported into the pre-constructed finite element model of the application scenario according to the position and direction defined by the installation boundary conditions. During the import process, the software automatically performs spatial position verification, using algorithms such as Boolean operations to check whether the model coincides with the installation boundary or exceeds the boundary range, and at the same time confirming whether the model invades the avoidance area. If there is a spatial conflict, an alarm will be issued in a timely manner, and a visual conflict prompt will be provided to help adjust the model position to ensure that the imported model fully meets the requirements of the support structure installation boundary, so that the finite element model can truly restore the actual application scenario and provide a reliable model basis for subsequent accurate multi-physics field analysis.

[0112] For the key areas such as the bearing seat and connection holes of the initial support model, hexahedral dominant grids are used for local encryption. In the finite element analysis software (such as ANSYS and COMSOL), the grid generation rules are set through the grid division module, and the grid size is limited to no more than 0.5mm to ensure that the stress and strain distribution of the key area under stress can be captured in detail; at the same time, in order to ensure the quality of the grid, the Jacobian is set to be greater than 0.7 to avoid the occurrence of deformed grids that affect the calculation accuracy, so that the grid unit can still maintain good geometric shape and calculation stability during the deformation process. For the motor air gap area, the sweeping grid layering technology is used for division. Based on the regularity of the air gap structure, the relative position of the motor rotor and stator is used as the reference, and the grid is swept and generated along a specific direction to ensure that the grid is evenly distributed along the air gap thickness direction. When dividing, the grid size is strictly controlled within 0.5mm, and the air gap boundary layer is refined so that the thickness of the first boundary layer does not exceed 0.02mm, so as to accurately simulate the distribution characteristics of the complex electromagnetic field in the air gap, as well as the flow and heat transfer process of the fluid in the air gap. Through the above-mentioned meshing strategy, while improving the calculation efficiency, the simulation accuracy of the finite element model for physical phenomena is significantly improved, providing a reliable data basis for subsequent multi-physical field analysis.

[0113] Apply the electromagnetic-force-thermal fully coupled mapping strategy to process the finite element model of the application scenario. First, regard the electromagnetic field, structural mechanics field, and thermal field during the operation of the motor as an integrated whole that is interrelated and mutually influential. Based on the multi-physics coupling module of finite element analysis software (such as ANSYS Multiphysics, COMSOL Multiphysics), establish the coupling relationship between each physical field. In the calculation of the electromagnetic field, solve the magnetic field distribution and electromagnetic force generated by the motor winding current through Maxwell's equations; for the structural mechanics field, analyze the stress, strain, and deformation of the support structure and motor components under the action of electromagnetic force and external loads according to Newton's laws of mechanics; the thermal field calculation is based on Fourier's law of heat conduction, considering heat generation factors such as copper loss and iron loss of the motor and heat dissipation conditions, and solve the temperature distribution. During the synchronous solution process, each physical field is not calculated independently, but realizes real-time interaction through data mapping and iterative calculation. For example, the electromagnetic force obtained from the electromagnetic field calculation is transferred as the load boundary condition of the structural mechanics field, enabling the structural mechanics field to accurately reflect the structural response caused by the electromagnetic force; the deformation obtained from the structural mechanics field calculation affects the air gap size, which in turn feeds back to the electromagnetic field calculation to correct the magnetic field distribution; the temperature change obtained from the thermal field calculation will change the material properties (such as conductivity, elastic modulus), and these changes are transferred back to the electromagnetic field and structural mechanics field as input parameters, affecting the subsequent calculation results. At the same time, accurately apply external boundary conditions such as the voltage, current, and ambient temperature of the motor operation to the corresponding physical field models, and transfer them between each physical field through the fully coupled mapping strategy to ensure the coordination and accuracy of the multi-physics field calculation, and finally obtain the simulation results that conform to the actual working conditions, providing a scientific basis for evaluating and optimizing the initial support structure.

[0114] Embodiment 2 Figure 2 The structural schematic diagram of the electronic device provided in the second embodiment of the present application is a block diagram of an exemplary electronic device suitable for implementing the embodiments of the present invention. Figure 2 The displayed electronic device is only an example and should not bring any restrictions to the functions and usage scope of the embodiments of the present invention. As Figure 2 shown, the electronic device includes a processor 21, a memory 22, an input device 23, and an output device 24; the number of processors 21 in the electronic device can be one or more. Figure 2 Taking one processor 21 as an example, the processor 21, memory 22, input device 23, and output device 24 in the electronic device can be connected through a bus or other means. Figure 2 Taking the connection through the bus as an example.

[0115] Embodiment 3. The memory 22, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the method for optimizing the support structure of the permanent magnet synchronous motor in the embodiments of the present application. The processor 21 executes various functional applications and data processing of the computer device by running the software programs, instructions, and modules stored in the memory 22, that is, implements the above-mentioned method for optimizing the support structure of the permanent magnet synchronous motor.

[0116] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above describes specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0117] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included within the protection scope of the present application.

[0118] This specification and the drawings are only exemplary descriptions of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. An optimized design method for the support structure of a permanent magnet synchronous motor, characterized in that The method includes: Selecting a support structure according to the motor application scenario to obtain an initial support structure; Calling an initial support model and a standard motor model according to the design parameters of the permanent magnet synchronous motor and the initial support structure; After performing finite element modeling on the motor application scenario in the simulation platform, importing the initial support model and the standard motor model into the application scenario finite element model by using multi-physics field coupling; After extracting the typical working condition combinations of the motor application scenario, obtaining a test working condition combination through perturbation expansion; Performing dynamic working condition simulation on the application scenario finite element model by using the test working condition combination, and identifying and extracting the distribution of weak areas, including: Serializing the test working condition combination according to the power characteristics, and performing smooth connection of the working conditions on the test working condition combination to obtain a smoothed ascending working condition sequence; Inputting the smoothed ascending working condition sequence into the application scenario finite element model for dynamic simulation configuration to obtain a dynamic simulation task queue; Performing HPC cluster distributed computing on the dynamic simulation task queue to obtain multiple thermo-mechanical coupling response fields corresponding to multiple simulated working conditions in the smoothed ascending working condition sequence; Performing grid-level multi-criterion fusion analysis on the multiple thermo-mechanical coupling response fields based on weak stress conditions, and outputting multiple grid distributions; After spatially aligning the multiple grid distributions, generating the weak area distribution by using morphological closing operation to connect adjacent weak grids; Performing performance iterative optimization of the weak area distribution in the application scenario finite element model by using local structure replacement to obtain a reference support model, including: Calculating and outputting P weak sensitivities based on the P peak stresses, P average strains, and P fatigue damage factors of the P weak areas extracted from the obtained weak area distribution; Arranging the P weak areas in descending order according to the P weak sensitivities to extract the top M high-priority replacement areas before sorting; After calling the design of M groups of replacement structure types for the M high-priority replacement areas in the replacement structure library, performing parametric modeling to obtain M groups of replacement CAD templates; Enumerating the M groups of replacement CAD templates in permutation and combination to generate a candidate replacement combination set; After performing local structure iterative replacement of the initial support model by using the candidate replacement combination set, inputting the smoothed ascending working condition sequence into the application scenario finite element model for dynamic simulation to obtain multiple combined performance indicators; Performing performance comprehensive evaluation on the multiple combined performance indicators by using a preset performance weight configuration, and extracting a target replacement combination from the candidate replacement combination set according to the evaluation result; Performing local structure replacement of the initial support model by using the target replacement combination to obtain the reference support model; Starting from the reference support model, performing structural lightweight optimization in the low stress area of the application scenario finite element model to obtain a lightweight support structure, including: After replacing the reference support model into the application scenario finite element model, performing grid-level multi-criterion fusion analysis on the reference support model based on high safety margin stress conditions, and outputting Q high safety margin areas; Calling the design of Q groups of lightweight structures for the Q high safety margin areas in the lightweight structure library; After performing dynamic simulation on the Q groups of lightweight structure designs using the application scenario finite element model, based on the weak stress conditions, weak area reproduction judgment is performed to obtain Q weak reproduction judgment results; According to the Q weak reproduction judgment results, R groups of lightweight structure designs are extracted from the Q groups of lightweight structure designs; Based on the R groups of lightweight structure designs, production lightweight processing backtracking is carried out to obtain R lightweight costs; Serialize the R lightweight costs, and according to the sorting results, extract the target lightweight structure design from the R groups of lightweight structure designs; Use the target lightweight structure design to perform structural lightweight compensation on the reference support model to obtain the reference support model.

2. The optimized design method for the support structure of the permanent magnet synchronous motor according to claim 1, characterized in that Select a support structure according to the motor application scenario to obtain an initial support structure. The method includes: Based on the real-time usage requirements of the permanent magnet synchronous motor, divide the scenario types to obtain the motor application scenario; According to the motor application scenario, call the index association rules, and use the motor application scenario and index association rules as retrieval conditions to locally extract associated working condition parameter indicators; According to the accommodation space characteristics of the motor application scenario and the associated working condition parameter indicators, select a support structure to obtain the initial support structure.

3. The optimized design method for the support structure of the permanent magnet synchronous motor according to claim 2, wherein According to the accommodation space characteristics of the motor application scenario and the associated working condition parameter indicators, select a support structure to obtain the initial support structure. The method includes: Extract the installation space geometric constraints from the accommodation space characteristics, where the installation space geometric constraints include the installation space shape, installation space size, motor installation position, and installation boundary conditions; Locally call the support node coordinate set of the permanent magnet synchronous motor; Fit the support structure installation boundary according to the installation space geometric constraints; According to the support structure installation boundary and the support node coordinate set, perform support structure screening to obtain an initial geometric structure; Perform material matching according to the associated working condition parameter indicators to obtain initial material information; Integrate the initial geometric structure and the initial material information to obtain the initial support structure.

4. The optimized design method for the support structure of the permanent magnet synchronous motor according to claim 3, characterized in that According to the support structure installation boundary and the support node coordinate set, perform support structure screening to obtain an initial geometric structure. The method includes: Based on the associated working condition parameters, perform main working condition analysis to obtain the main working condition scenario; Perform main support structure matching on the main working condition scenario; According to the support structure installation boundary and the support node coordinate set, perform support structure screening to obtain multiple support geometric structures; Taking the installation boundary conditions as constraints, according to the installation space shape, installation space size, and motor installation position, calculate the multiple space volume utilization rates of the multiple support geometric structures; After arranging the multiple support geometric structures in ascending order according to the multiple space volume utilization rates, use the main support structure as the screening condition to extract the initial geometric structure from the sorting results.

5. The optimization design method of the support structure of the permanent magnet synchronous motor according to claim 4, characterized in that After performing finite element modeling on the motor application scenario in the simulation platform, use multi-physics field coupling to import the initial support model and the standard motor model into the application scenario finite element model. The method includes: After the attribute assignment to the initial support model according to the initial material information, the support node coordinate set is used as the coordinate system alignment reference for the alignment and assembly of the initial support model and the standard motor model; According to the installation boundary of the support structure, the initial support model and the standard motor model in the alignment and assembly state are imported into the application scenario finite element model; The initial support model is locally mesh-refined using hexahedron-dominated meshes, and the motor air-gap region is stratified using swept meshes, where the mesh size ≤ 0.5 mm and the thickness of the first boundary layer ≤ 0.02 mm; Using the electromagnetic-force-thermal fully coupled mapping strategy, multi-physics field synchronous solution and boundary condition transfer of the application scenario finite element model are carried out.

6. An electronic device, characterized in that, The electronic device includes: A memory for storing executable instructions; A processor for implementing the support structure optimization design method of the permanent magnet synchronous motor according to any one of claims 1-5 when executing the executable instructions stored in the memory.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the support structure optimization design method of the permanent magnet synchronous motor according to any one of claims 1-5.

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