Simulation optimization design method of swing motor stator and related equipment thereof
By using simulation-based optimization design methods, the problem of insufficient quantification of axial force in the stator design of traditional swing motors was solved, achieving efficient and accurate stator structure optimization and significantly improving the scientific nature and efficiency of the design.
Patent Information
- Application Number
- CN202511482207.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-16
- Publication Date
- 2026-05-12
AI Technical Summary
Traditional stator design methods for oscillating motors rely on empirical formulas, which cannot accurately quantify axial force, resulting in low design and optimization efficiency.
The simulation optimization design method is adopted. Simulation modeling data is obtained in response to user requests, simulation optimization conditions are set, and electromagnetic simulation software is used to generate a design report, with the goal of reducing axial axial force.
It realizes the full-process automation and intelligent design of the stator of the swing motor, which can accurately predict the trend of axial force change in the early stage of design, identify the structural parameters that cause cross-force, significantly shorten the design cycle, and improve the scientific nature and optimization efficiency of the design.
Smart Images
Figure CN122020944A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of simulation optimization design, specifically relating to a simulation optimization design method for a swing motor stator and related equipment. Background Technology
[0002] In a swing motor system, axial force can cause problems such as focused spot shift, reduced dynamic performance, bearing wear, and overheating, ultimately affecting the accuracy and stability of the swing motor output. Therefore, the generation of axial force should be avoided as much as possible in a swing motor system.
[0003] Axial runout can be caused by various factors, such as unreasonable structural design, improper manufacturing process, and low assembly precision. Among these, the structural design of the motor stator has a significant impact on axial runout. Bearing mounting holes must be provided at the stator ends for internal bearings. If the design of these mounting holes is unreasonable, it will severely disrupt the symmetry of the magnetic field, causing the mover to experience asymmetrical magnetic pull, thus generating axial runout. Traditional stator design methods rely on empirical formulas, which cannot accurately quantify axial runout, resulting in low design and optimization efficiency. Summary of the Invention
[0004] The purpose of this application is to propose a simulation optimization design method for a swing motor stator and related equipment to solve the technical problems of traditional stator design methods relying on empirical formulas, being unable to accurately quantify axial axial force, and having low design and optimization efficiency.
[0005] Firstly, in order to solve the above-mentioned technical problems, this application provides a simulation optimization design method for the stator of a swing motor, which adopts the following technical solution: A simulation optimization design method for the stator of a oscillating motor, applied to an oscillating motor system, includes the following steps: In response to simulation optimization task requests from the user, the simulation modeling data related to the simulation optimization task requests is received and used for simulation modeling of the oscillating motor stator. Obtain the simulation optimization conditions, which are used to guide the number of iterations in the simulation optimization process; The simulation optimization design report is sent to the user terminal. The simulation optimization design report is a design report generated by the system through electromagnetic simulation software to simulate and model the simulation modeling data and simulation optimization conditions. The design goal of the simulation modeling is to reduce the axial force of the stator of the swing motor.
[0006] Secondly, in order to solve the above-mentioned technical problems, this application also provides a simulation optimization design device for the stator of a swing motor, which adopts the following technical solution: A simulation optimization design device for a swing motor stator, the device being equipped with a swing motor system, the device comprising: The data acquisition module is used to respond to simulation optimization task requests from the user terminal and receive simulation modeling data related to the simulation optimization task requests. The simulation modeling data is used for simulation modeling of the oscillating motor stator. The simulation conditions module is used to obtain simulation optimization conditions, which guide the number of iterations in the simulation optimization process. The simulation optimization module is used to send a simulation optimization design report to the user terminal. The simulation optimization design report is a design report generated by the system through electromagnetic simulation software to simulate and model the simulation modeling data and simulation optimization conditions. The design goal of the simulation modeling is to reduce the axial force of the stator of the swing motor.
[0007] Thirdly, in order to solve the above-mentioned technical problems, embodiments of this application also provide a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to execute the simulation optimization design method for the oscillating motor stator in the first aspect described above.
[0008] Fourthly, in order to solve the above-mentioned technical problems, embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the simulation optimization design method for the stator of the swing motor in the first aspect described above.
[0009] Fifthly, embodiments of this application provide a computer program product that, when run on a terminal device, causes the terminal device to execute the simulation optimization design method for the oscillating motor stator described in the first aspect.
[0010] Compared with the prior art, the embodiments of this application have the following main advantages: This application discloses a simulation optimization design method and related equipment for a swing motor stator. It introduces parametric modeling and electromagnetic simulation optimization processes during the stator design stage, achieving full automation and intelligence from structural definition and parameter input to optimization calculation. It can automatically generate an electromagnetic simulation model that conforms to physical constraints based on user-input geometric parameters, material type, and structural form. Through an embedded optimization algorithm, it dynamically adjusts design variables in multiple iterative calculations, thereby achieving a quantitative optimization process aimed at minimizing axial force. Compared with traditional stator design methods that rely on empirical formulas and manual calculations, this application can accurately predict and analyze the axial force variation trend of the mover under electromagnetic influence early in the design process, identify structural parameter combinations that lead to excessive force, and automatically generate optimized geometric schemes through electromagnetic simulation and a database-driven parameter feedback mechanism. This provides high-precision design references, significantly shortening the design cycle and improving the scientific rigor, verifiability, and overall optimization efficiency of the stator structure design. Attached Figure Description
[0011] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0012] Figure 1 An exemplary system architecture diagram is shown, in which this application can be applied; Figure 2 A flowchart of one embodiment of the simulation optimization design method for the stator of the oscillating motor according to this application is shown; Figure 3 This application shows a basic structural diagram of the single-sided bearing mounting hole of the magnetic conductor in an embodiment of the present application, wherein, Figure 3 -(a) shows a two-dimensional assembly diagram of the bearing mounting hole on one side of the magnetic conductor. Figure 3 -(b) shows a three-dimensional view of the stator magnet with a bearing mounting hole on one side; Figure 4 A schematic diagram showing the geometric parameter definition window of the bearing mounting hole on one side of the magnetic conductor in an embodiment of this application is illustrated. Figure 5 This application shows a basic structural diagram of the double-sided bearing mounting holes of the magnetic conductor in an embodiment of the present application, wherein, Figure 5 -(a) shows a two-dimensional assembly diagram of the bearing mounting holes on both sides of the magnetic conductor. Figure 5 -(b) shows a three-dimensional view of the stator magnet with bearing mounting holes on both sides; Figure 6A schematic diagram showing the geometric parameter definition window of the bearing mounting holes on both sides of the magnetic conductor in an embodiment of this application is illustrated. Figure 7 This paper shows a basic structural diagram of the bearingless mounting hole of the magnetic conductor in an embodiment of this application, wherein, Figure 7 -(a) shows a two-dimensional assembly diagram of the magnetic conductor without bearing mounting holes. Figure 7 -(b) shows a three-dimensional view of the stator magnet without bearing mounting holes; Figure 8 A schematic diagram showing the geometric parameter definition window of the bearingless mounting hole of the magnetic conductor in an embodiment of this application is illustrated. Figure 9 A schematic diagram of a structure of an embodiment of the simulation optimization design device for the stator of an oscillating motor according to this application is shown; Figure 10 A schematic diagram of the structure of one embodiment of a computer device according to this application is shown. Detailed Implementation
[0013] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.
[0014] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0015] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.
[0016] like Figure 1As shown, system architecture 100 may include terminal device 101, network 102, and server 103. Terminal device 101 may be a laptop 1011, tablet 1012, or mobile phone 1013. Network 102 is used as a medium to provide a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables.
[0017] Users can use terminal device 101 to interact with server 103 via network 102 to receive or send messages, etc. Various communication client applications can be installed on terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.
[0018] Terminal device 101 can be various electronic devices with a display screen and support web browsing. In addition to laptops 1011, tablets 1012, or mobile phones 1013, terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 player (Moving Picture Experts Group Audio Layer IV), a laptop computer, and a desktop computer, etc.
[0019] Server 103 can be a server that provides various services, such as a backend server that provides support for the pages displayed on terminal device 101.
[0020] It should be noted that the simulation optimization design method for the oscillating motor stator provided in this application embodiment is generally executed by a server / terminal device, and correspondingly, the simulation optimization design device for the oscillating motor stator is generally set in the server / terminal device.
[0021] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative; the system can have any number of terminal devices, networks, and servers depending on implementation needs.
[0022] Continue to refer to Figure 2 The flowchart illustrates an embodiment of a simulation optimization design method for a swing motor stator according to this application. The simulation optimization design method for a swing motor stator includes the following steps: S201, responding to the simulation optimization task request from the user terminal, receives simulation modeling data related to the simulation optimization task request. The simulation modeling data is used for the simulation modeling of the oscillating motor stator. Specifically, after the system receives a simulation optimization task request from the user, the system first calls the communication interface module to collect simulation modeling data related to the current task from the user. The simulation modeling data usually includes structural type parameters, geometric dimension parameters, material type parameters, etc. of the stator magnet.
[0023] The structural type parameter is used to determine the basic topology of the simulation model, such as "single-sided bearing mounting hole of the magnet", "double-sided bearing mounting hole of the magnet", or "no bearing mounting hole of the magnet"; the geometric dimension parameter includes information such as the stator outer diameter, inner diameter, length, bearing hole depth and radius difference, which is used to generate a three-dimensional parametric geometric model; the material type parameter includes key magnetic and electrical performance indicators such as permeability, conductivity, and coercivity of the stator and mover materials, which are used to establish an accurate electromagnetic physical field model.
[0024] In addition, the system also receives simulation prerequisite data set by the user, such as the relative positional relationship between the mover and stator, excitation current waveform, frequency, and operating temperature environment. After receiving the data, the system performs data integrity and format verification to confirm that the input parameters meet the requirements of the simulation engine interface. It then uses a data mapping algorithm to convert the data into an input file or parameter matrix that can be recognized by electromagnetic simulation software. This allows for interaction with electromagnetic simulation platforms (such as Ansys Maxwell, JMAG, COMSOL, etc.) through interface scripts, ensuring the accuracy and consistency of the model.
[0025] S202, Obtain simulation optimization conditions. These conditions are used to guide the number of iterations in the simulation optimization process. Specifically, after successfully receiving simulation modeling data, the system enters the simulation optimization condition acquisition stage, which mainly consists of the optimization algorithm configuration stage and the parameter constraint management stage. In the optimization algorithm configuration stage, the system first automatically selects a suitable optimization algorithm based on the user-defined simulation task type and loads the corresponding control parameters. Simultaneously, the system extracts convergence patterns of similar models from the historical simulation database to automatically optimize the initial parameters of the algorithm and improve computational stability. In the parameter constraint management stage, the system establishes a multi-dimensional parameter constraint matrix based on the user-input design variables and their value ranges. It performs validity checks and corrections on the candidate solutions for each iteration to ensure that the optimization variables change within the limits allowed by physical and manufacturing conditions. It also monitors the constraint boundaries in real time to prevent simulation results from being distorted or invalid calculations, thereby ensuring the reliability and controllability of the optimization process.
[0026] First, the system automatically loads the simulation optimization solver based on the user's task type (single simulation or optimization simulation) and obtains the control conditions related to the optimization process. The simulation optimization conditions include the optimization objective function, optimization variables, variable value ranges, optimization algorithm type, and iteration termination conditions. The optimization objective function is typically set to "minimize the axial movement force of the stator," but the system also supports multi-objective settings, such as simultaneously considering electromagnetic efficiency, temperature rise distribution, or torque ripple. Optimization variables may include geometric parameters (such as the difference between the bearing bore depth, the outer radius of the bearing bore, and the inner radius of the stator magnetic conductor) or material properties.
[0027] The system also reads algorithm strategy parameters from the database, such as the population size, crossover rate, and mutation rate for genetic algorithms, or the inertia weight and learning factor for particle swarm optimization. Regarding the setting of the number of iterations, the system automatically recommends an initial iteration limit based on the convergence trends of similar models in the historical simulation database, while also allowing users to adjust it manually. After the simulation optimization conditions are loaded, they are input into the optimization engine along with the simulation modeling data. In each iteration, the system dynamically adjusts the design variables based on the simulation results until the iteration termination criteria are met (such as the objective function convergence threshold or the maximum number of iterations). This process ensures the efficiency and controllability of the optimization computation.
[0028] S203, send a simulation optimization design report to the user terminal. The simulation optimization design report is a design report generated by the system through electromagnetic simulation software to simulate and model the simulation modeling data and simulation optimization conditions. The design goal of the simulation modeling is to reduce the axial axial force of the stator of the swing motor.
[0029] Specifically, after the system completes all simulation and optimization calculations, the results analysis and report generation module will automatically summarize the simulation process data and optimization results to generate a simulation optimization design report containing complete data.
[0030] The report is generated based on the system's built-in report template engine, which can extract multi-dimensional data from the simulation database, including electromagnetic field distribution results, torque curves, mover force curves, magnetic flux density contour maps, optimization convergence curves, and final design parameter values. The report typically includes the following sections: ① Basic Information Section: Records simulation task number, user input parameters, optimization objectives, and algorithm settings; ② Simulation model section: The stator and mover are shown in three-dimensional view or two-dimensional cross-section, with annotations of the main geometric dimensions; ③ Simulation results section: Provides tables of calculation results for each key parameter, axial force curve of the mover, magnetic flux distribution diagram, etc.; ④ Optimization process section: Shows the iterative change trend of the optimization variables, the convergence curve, and the final convergence accuracy; ⑤ Design Recommendations: Based on the optimization results, list the recommended geometric dimensions and material combinations.
[0031] Finally, the system automatically exports the report to PDF or Word format and sends it to the user's device via the communication module, while simultaneously archiving it on the system server. Users can view the report content through the interface and choose to import the results data back into subsequent experimental verification or further simulation analysis modules, achieving closed-loop data management. The entire report generation and transmission process is executed automatically by the system without manual intervention.
[0032] Furthermore, after responding to the simulation optimization task request from the user, the method also includes: Identify the simulation modeling objects that match the simulation optimization task request. The simulation modeling objects include stator magnets and / or mover permanent magnets. The simulation modeling object is used to adapt to the simulation database, simulation modeling method, and optimization method used in the simulation modeling process.
[0033] In this embodiment, after receiving a simulation optimization task request from the user, the system performs semantic recognition and structured parsing of the request content through task parsing to determine the simulation modeling object matching the task. The simulation modeling object can be a stator magnet, a mover permanent magnet, or a combination of both. Based on the task type and target parameters (such as axial force), the system retrieves the corresponding modeling template and material parameter set from the simulation database. Subsequently, the system automatically matches the appropriate simulation modeling method, such as the two-dimensional cross-sectional finite element method, the three-dimensional parametric modeling method, or the hybrid magnetic circuit modeling method, and selects the corresponding optimization strategy (such as global optimization or local iterative optimization). For tasks involving stator and mover co-analysis, the system will simultaneously load the coupled solution model to ensure the consistency of magnetic field distribution and mechanical response. Through this matching mechanism, the system can quickly generate simulation models that meet the target requirements under different structural topologies and material combinations, achieving automated model adaptation and efficient solution.
[0034] By following the steps above, the system can automatically identify and match the most suitable simulation modeling object and method, improve the accuracy of simulation modeling and the pertinence of optimization calculation, thereby significantly improving the overall intelligence and design efficiency of the system.
[0035] Furthermore, the simulation modeling data includes the motor structure data, geometric parameter data, and material type data of the modeling object. It also receives simulation modeling data related to the simulation optimization task request, including: When the first window on the user terminal is triggered, motor structure data is obtained from the user terminal. The first window is configured to identify the simulation modeling object selected by the user. When the second window on the user's end is triggered, geometric parameter data is obtained from the user's end. The second window is configured to obtain the geometric parameters set by the user for the simulation modeling object. When the third window on the user's end is triggered, material type data is obtained from the user's end. The third window is configured to obtain the material type selected by the user for the simulation modeling object.
[0036] In this embodiment, after receiving a user's simulation optimization task request, the system initiates a data acquisition process based on a multi-window interaction mechanism. First, when the first window on the user's end is triggered, the system guides the user to select the motor structure type of the simulation modeling object through a graphical interface, such as "single-sided bearing mounting hole for the magnet," "double-sided bearing mounting hole for the magnet," or "no bearing mounting hole for the magnet." This window identifies the structure through drop-down selection or graphical preview and transmits the selected structure's coding information to the simulation database to call the corresponding structure template. Subsequently, when the second window is triggered, the system automatically loads the geometric parameter input interface corresponding to the selected structure. The user can input various feature dimensions in this window, such as stator outer diameter, stator inner diameter, stator length, mover outer diameter, and bearing hole depth. Next, when the third window is triggered, the system retrieves a list of selectable materials from the material database. The user selects the material type for the stator magnet and the mover permanent magnet. The system then encapsulates the selected material type and geometric data into a complete simulation modeling data package.
[0037] The entire data acquisition process is driven by an event listening mechanism. Data transfer between windows is completed through memory mapping and a data bus, ensuring that the simulation modeling data is structured, complete, and highly consistent when transmitted to the simulation engine, thereby achieving accurate definition and parametric expression of the motor model.
[0038] Through the above steps, the system can achieve hierarchical acquisition and dynamic binding of motor structure, geometric parameters and material information, ensuring the accuracy and flexibility of the simulation modeling data input process.
[0039] Furthermore, when the second window on the user's device is detected to be triggered, geometric parameter data is obtained from the user's device, including: Based on the simulation modeling object selected by the user, obtain a set of standard geometric parameter examples that match the simulation modeling object. The simulation modeling objects in the set of standard geometric parameter examples carry pre-annotated geometric parameters. The second window displays either a global or sequential set of standard geometric parameter examples for the simulation modeling object. The second window captures the target standard example selected by the user and obtains the geometric parameter data of the target standard example; Alternatively, a geometric parameter input box for the simulation modeling object can be generated in the second window, and the geometric parameter data input by the user can be obtained through the geometric parameter input box.
[0040] In this embodiment, when the system detects that the second window on the user's end is triggered, it starts the geometric parameter acquisition interface. Based on the simulation modeling object type selected by the user in the first window (e.g., "single-sided bearing mounting hole of magnetic conductor", "double-sided bearing mounting hole" or "no bearing mounting hole"), the interface automatically calls the standard geometric parameter example set that matches the structure type from the database.
[0041] The standard geometric parameter example set contains 3D structural models of several typical design schemes and their corresponding geometric dimension annotations. Each example presents the location and name of key parameters in a visual manner. In the second window, the system allows users to choose between "global display mode" or "single example step-by-step display mode" to achieve different levels of geometric reference display. If the user selects a target standard example in the window, the system will automatically extract the corresponding geometric parameter data and populate it into the parameter form for the user to directly use or modify.
[0042] On the other hand, if the user selects a custom input method, the system dynamically generates a geometric parameter input box in the window and captures the user's input data through the input box. To improve input accuracy, the system executes parameter validation rules in the background, including unit consistency, size rationality judgment, and boundary constraint verification, to prevent input data from exceeding the model's computable range. Finally, all geometric parameter data will be structurally bound to the modeling object information and written to the simulation modeling data file.
[0043] Through the above steps, the system can flexibly adapt to different user needs, realize dual-mode interaction of standard geometric parameter reference and custom input, and improve the efficiency and accuracy of geometric parameter acquisition.
[0044] Furthermore, when the simulation modeling object includes the stator magnet and the mover permanent magnet, the geometric parameter data includes the stator magnet length, the mover permanent magnet length, the outer diameter of the stator magnet outer circle, the inner diameter of the stator magnet inner circle, the outer diameter of the mover permanent magnet outer circle, the bearing hole depth, and the difference between the outer radius of the bearing hole and the inner radius of the stator magnet inner circle.
[0045] In one specific embodiment of this application, when the user selects the simulation modeling object type as a single-sided bearing mounting hole for a magnetic conductor in the first window, please refer to... Figure 3 , Figure 3The diagram shows the basic structure of a bearingless mounting hole for a magnetic conductor. Its basic structure includes a stator magnetic conductor 11, a mover permanent magnet 12, two bearings (first bearing 21 and second bearing 22), two bearing sleeves (first bearing sleeve 31 and second bearing sleeve 32), and two shafts (first shaft 41 and second shaft 42). The stator magnetic conductor 11 is a hollow cylinder. The mover permanent magnet 12 is coaxially inserted into the hollow cylinder of the stator magnetic conductor 11. The first bearing sleeve 31 and the first shaft 41 are coaxially fitted on one side of the mover permanent magnet 12, and the second bearing sleeve 32 and the second shaft 42 are coaxially fitted on the other side of the mover permanent magnet 12.
[0046] A first bearing mounting groove 51 is provided on one side of the stator magnetic conductor 11 with a single-sided bearing mounting hole. The first bearing 21 is installed in the first bearing mounting groove 51. When the second bearing sleeve 32 and the second shaft 42 are sleeved on the other side of the mover permanent magnet 12, a second bearing mounting groove 52 is formed. The second bearing 22 is installed in the second bearing mounting groove 52.
[0047] When the user selects the single-sided bearing mounting hole for the magnetic conductor, the system pops up the first geometric parameter definition window, which displays as follows: Figure 4 As shown in the figure. Where L1 is the length of the stator magnet, L2 is the length of the mover permanent magnet, D1 is the outer diameter of the stator magnet, D2 is the inner diameter of the stator magnet, D3 is the outer diameter of the mover permanent magnet, B1 is the bearing hole depth, and B2 is the difference between the outer radius of the bearing hole and the inner radius of the stator magnet.
[0048] Please refer to Figure 5 , Figure 5 The diagram shows the basic structure of the double-sided bearing mounting hole of the magnetic conductor. The stator magnetic conductor 11 with the double-sided bearing mounting hole has two first bearing mounting slots 51 on both sides. The first bearing 21 and the second bearing 22 are respectively installed in the two first bearing mounting slots 51.
[0049] When the user selects the single-sided bearing mounting hole for the magnetic conductor, the system will pop up the corresponding second geometric parameter definition window, which displays as follows: Figure 6 As shown in the diagram. Where L1 is the length of the stator magnet, L2 is the length of the mover permanent magnet, D1 is the outer diameter of the stator magnet, D2 is the inner diameter of the stator magnet, D3 is the outer diameter of the mover permanent magnet, B1 is the depth of the left bearing hole, B2 is the difference between the outer radius of the left bearing hole and the inner radius of the stator magnet, B3 is the depth of the right bearing hole, and B4 is the difference between the outer radius of the right bearing hole and the inner radius of the stator magnet.
[0050] Please refer to Figure 7 , Figure 7The diagram shows the basic structure of the bearingless mounting hole of the stator magnet 11. Neither side of the stator magnet 11 has a first bearing mounting groove 51. When the first bearing sleeve 31 and the first shaft 41 are coaxially fitted on one side of the mover permanent magnet 12, a second bearing mounting groove 52 is formed. When the second bearing sleeve 32 and the second shaft 42 are fitted on the other side of the mover permanent magnet 12, another second bearing mounting groove 52 is formed. The first bearing 21 and the second bearing 22 are respectively installed in the two second bearing mounting grooves 52.
[0051] When the user selects the bearingless mounting hole for the magnetic conductor, the system will pop up the corresponding third geometric parameter definition window, which displays as follows: Figure 8 As shown in the figure. Where L1 is the length of the stator magnet, D1 is the outer diameter of the stator magnet, D2 is the inner diameter of the stator magnet, and D3 is the outer diameter of the mover permanent magnet.
[0052] In one specific embodiment of this application, it is assumed that the current user selects the single-sided bearing mounting hole of the magnetic conductor and inputs various geometric parameter data in sequence, such as L1:50mm, L2:50mm, D1:30mm, D2:16mm, D3:10mm, B1:7.3mm, B2:1.5mm.
[0053] Then comes the material selection stage. Here, the system already includes relevant parameters for various materials commonly used in galvanometer motors, such as 1J50 (magnetic conductor), NdFe35 (magnetic material), and NdFe30 (magnetic material). Users can set the materials for the stator magnetic conductor and the mover permanent magnet according to their needs, such as setting the material of the stator magnetic conductor to 1J50 and the material of the mover permanent magnet to NdFe35.
[0054] Next, the user selects the environment, specifically the simulation optimization conditions. Selecting "Calculate Only Once" means the simulation will only be performed once; selecting "Optimize Calculation" means the simulation aims to minimize axial axial force. The system will then display a window allowing the user to select optimization parameters and their ranges. In this example, parameters B1 and B2 are selected as optimization parameters, with the optimization range for B1 set to 4-10 mm and for B2 to 0.8-2.5 mm. The data set by the user in these steps is automatically stored in the simulation database.
[0055] After confirming the geometric definition, materials, and simulation requirements of the analysis object, the system will automatically enter the simulation modeling stage. In this stage, the system will automatically generate simulation models of the relevant simulation objects and perform simulation calculations or optimization calculations respectively. Table 1 shows the simulation and optimization results of the single-sided bearing mounting hole of the magnetic conductor under a set of exemplary parameters.
[0056] Table 1 Simulation and optimization results of bearing mounting holes on one side of the magnetic conductor
[0057] As shown in Table 1, the original design geometric parameters are shown in Calculation 1, which yielded a mover axial axial force of 0.846 N. After optimization, the final optimized result is 0.439 N (minimum mover axial axial force), representing a reduction of 48.1%. It can also be seen that parameter B2 has a greater impact on the mover axial axial force and should be minimized during design. After the simulation or optimization calculations are completed, the simulation and optimization results will be output for user review.
[0058] Furthermore, when the third window on the user's device is triggered, material type data is retrieved from the user's device, including: Based on the simulation modeling object selected by the user, obtain a standard material type example set that matches the simulation modeling object. The standard material type example set records all material types that can be used by the simulation modeling object. In the third window, generate material type selection buttons for the simulation modeling objects, and fill in a standard material type example in each material type selection button; When the material type selection button on the third window is triggered, the material type data selected by the user is obtained.
[0059] In this embodiment, When the system detects that the third window on the user's end has been triggered, it immediately launches the material type selection interface. This interface, based on the simulation modeling object type selected by the user in the first window, precisely retrieves a set of standard material type examples from the material database that match the selected type. This set of examples covers all material types that can be used for the modeling object, such as magnetic conductive materials and permanent magnet materials, ensuring the comprehensiveness and accuracy of the user's selection.
[0060] In the third window, the system dynamically generates material type selection buttons, each corresponding to a standard material type example. These buttons are presented in a clear and intuitive way, making it easy for users to quickly identify and select. For example, when the user selects a single-sided bearing mounting hole for a magnetic conductor, the window may display buttons for magnetic conductor materials such as "1J50 (magnetic conductor)" and "1J22 (magnetic conductor)," as well as buttons for permanent magnet materials such as "NdFe35 (magnetic material)" and "SmCo5 (magnetic material)."
[0061] When a user clicks a material type selection button, the system immediately captures the trigger event and obtains the material type data selected by the user. This data, along with the previously acquired motor structure data and geometric parameter data, is then packaged into a complete simulation modeling data package.
[0062] Through the above steps, the system not only improves the efficiency and accuracy of material selection, but also provides users with more flexible and personalized material configuration solutions. Users can easily select the most suitable material type according to their actual needs, thereby optimizing the performance and effect of the motor model.
[0063] Furthermore, before responding to a simulation optimization task request from the user and receiving simulation modeling data related to the simulation optimization task request, the method also includes: Construct a simulation database to store simulation data; Obtain all simulation modeling results generated during the simulation optimization process; each simulation optimization calculation will generate a simulation modeling result. The simulation modeling data, simulation optimization conditions, all simulation modeling results, and simulation optimization design reports are stored in the simulation database.
[0064] In this embodiment, The simulation database employs a structured storage architecture, categorizing and storing data of different dimensions in dedicated data tables. The simulation modeling data table records raw input information such as motor geometric parameters and material properties; the simulation optimization conditions table stores user-defined calculation modes, optimization objectives, and parameter ranges; the simulation results table saves the output data of each calculation by timestamp, including performance indicators such as axial force; and the design report table stores the parameter comparisons and analysis conclusions before and after optimization.
[0065] The system interacts with the simulation calculation module in real time via a data interface, automatically triggering a data storage process after each optimization calculation. This process first verifies the validity of the simulation results, removing abnormal data caused by parameters exceeding limits, and then writes the qualified data into the corresponding data table according to a preset format. For optimization calculation tasks, the system additionally generates an intermediate result table containing iterative process data, recording the performance change trend after each parameter adjustment.
[0066] The simulation database can employ index optimization techniques to establish composite indexes in key fields such as geometric parameter combinations and material types. When users need to retrieve historical simulation data, the system can quickly locate target records through multi-dimensional condition filtering. For example, conditions such as "magnetic conductor single-sided bearing mounting hole", "1J50 material", and "B1 parameter range of 4-10mm" can be specified simultaneously for precise retrieval.
[0067] Through the above steps and this structured storage scheme, the simulation database not only enables complete traceability of data throughout the simulation process, but also allows technicians to conduct statistical analysis based on historical data and discover the correlation between material parameters and performance indicators.
[0068] In the above embodiments, this application discloses a simulation optimization design method for a swing motor stator. It introduces parametric modeling and electromagnetic simulation optimization processes during the stator design stage, achieving full automation and intelligence from structural definition and parameter input to optimization calculation. It can automatically generate an electromagnetic simulation model that conforms to physical constraints based on user-input geometric parameters, material types, and structural forms. Through an embedded optimization algorithm, it dynamically adjusts design variables in multiple iterative calculations, thereby achieving a quantitative optimization process aimed at minimizing axial force. Compared with traditional stator design methods that rely on empirical formulas and manual calculations, this application can accurately predict and analyze the axial force variation trend of the mover under electromagnetic influence in the early stages of design, identify structural parameter combinations that lead to excessive force, and automatically generate optimized geometric schemes. Through electromagnetic simulation and database-driven parameter feedback mechanisms, designers can obtain high-precision design references without repeatedly conducting physical prototype tests, significantly shortening the design cycle, reducing modification and debugging costs caused by later structural defects, and improving the scientific nature, verifiability, and overall optimization efficiency of stator structure design.
[0069] In this embodiment, the simulation optimization design method for the oscillating motor stator operates on the electronic equipment (e.g., Figure 1 The server shown can receive instructions or acquire data via wired or wireless connection. It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra-wideband) connections, and other currently known or future wireless connection methods.
[0070] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware through computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).
[0071] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.
[0072] Further reference Figure 10 As a response to the above Figure 2 The implementation of the method shown in this application provides an embodiment of a simulation optimization design device for a swing motor stator. This device embodiment is similar to... Figure 2 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.
[0073] like Figure 10 As shown, the simulation optimization design device 900 for the stator of the oscillating motor in this embodiment is equipped with an oscillating motor system. The simulation optimization design device 900 for the stator of the oscillating motor includes: The data acquisition module 901 is used to respond to the simulation optimization task request from the user terminal and receive the simulation modeling data related to the simulation optimization task request. The simulation modeling data is used for the simulation modeling of the oscillating motor stator. The simulation condition module 902 is used to obtain simulation optimization conditions, which are used to guide the number of iterations in the simulation optimization process. The simulation optimization module 903 is used to send a simulation optimization design report to the user terminal. The simulation optimization design report is a design report generated by the system through electromagnetic simulation software to simulate and model the simulation modeling data and simulation optimization conditions. The design goal of the simulation modeling is to reduce the axial axial force of the stator of the swing motor.
[0074] Furthermore, the simulation optimization design device 900 for the oscillating motor stator also includes: The modeling object module is used to determine the simulation modeling objects that match the simulation optimization task request. The simulation modeling objects include stator magnets and / or mover permanent magnets. The simulation adaptation module is used to adapt simulation modeling objects to the simulation database, simulation modeling methods, and optimization methods used in the simulation modeling process.
[0075] Furthermore, the simulation modeling data includes the motor structure data, geometric parameter data, and material type data of the modeling object. The data acquisition module 901 includes: The first triggering unit is used to obtain motor structure data from the user terminal when the first window of the user terminal is triggered. The first window is configured to identify the simulation modeling object selected by the user. The second triggering unit is used to obtain geometric parameter data from the user terminal when the second window of the user terminal is triggered. The second window is configured to obtain the geometric parameters set by the user for the simulation modeling object. The third triggering unit is used to obtain material type data from the user terminal when the third window of the user terminal is triggered. The third window is configured to obtain the material type selected by the user for the simulation modeling object.
[0076] Furthermore, the second triggering unit includes: The geometric parameter example sub-unit is used to obtain a set of standard geometric parameter examples that match the simulation modeling object selected by the user. The simulation modeling objects in the set of standard geometric parameter examples carry pre-annotated geometric parameters. Example display sub-cells are used to display a global or sequential set of standard geometric parameter examples of simulation modeling objects on a second window; The target example sub-unit is used to capture the target standard example selected by the user through the second window and obtain the geometric parameter data of the target standard example; Alternatively, a user-defined input sub-unit can be used to generate a geometric parameter input box for the simulation modeling object on the second window, and to obtain the geometric parameter data input by the user through the geometric parameter input box.
[0077] Furthermore, when the simulation modeling object includes the stator magnet and the mover permanent magnet, the geometric parameter data includes the stator magnet length, the mover permanent magnet length, the outer diameter of the stator magnet outer circle, the inner diameter of the stator magnet inner circle, the outer diameter of the mover permanent magnet outer circle, the bearing hole depth, and the difference between the outer radius of the bearing hole and the inner radius of the stator magnet inner circle.
[0078] Furthermore, the third triggering unit includes: The Material Type Example Sub-unit is used to obtain a set of standard material type examples that match the simulation modeling object selected by the user. The set of standard material type examples records all material types that can be used by the simulation modeling object. The material type display sub-unit is used to generate material type selection buttons for simulation modeling objects on the third window, and to fill in a standard material type example in each material type selection button; The button trigger subunit is used to obtain the material type data selected by the user when the material type selection button on the third window is triggered.
[0079] Furthermore, the simulation optimization design device 90 for the oscillating motor stator also includes: The database construction module is used to build the simulation database, which is used to store simulation data. The modeling results module is used to obtain all simulation modeling results generated during the simulation optimization process. Each simulation optimization calculation will generate a simulation modeling result. The data storage module is used to store simulation modeling data, simulation optimization conditions, all simulation modeling results, and simulation optimization design reports into the simulation database.
[0080] In the above embodiments, this application discloses a simulation optimization design device for a swing motor stator. It introduces parametric modeling and electromagnetic simulation optimization processes during the stator design stage, achieving full automation and intelligence from structural definition and parameter input to optimization calculation. It can automatically generate an electromagnetic simulation model that conforms to physical constraints based on user-input geometric parameters, material type, and structural form. Through an embedded optimization algorithm, it dynamically adjusts design variables in multiple iterative calculations, thereby achieving a quantitative optimization process aimed at minimizing axial force. Compared with traditional stator design methods that rely on empirical formulas and manual calculations, this application can accurately predict and analyze the axial force change trend of the mover under electromagnetic influence in the early stages of design, identify structural parameter combinations that lead to excessive force, and automatically generate optimized geometric schemes. Through electromagnetic simulation and a database-driven parameter feedback mechanism, designers can obtain high-precision design references without repeatedly conducting physical prototype tests, significantly shortening the design cycle, reducing modification and debugging costs caused by later structural defects, and improving the scientific nature, verifiability, and overall optimization efficiency of stator structure design.
[0081] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 10 , Figure 10 This is a basic structural block diagram of the computer device in this embodiment.
[0082] Computer device 6 includes a memory 61, a processor 62, and a network interface 63 that are interconnected via a system bus. It should be noted that only computer device 6 with memory 61, processor 62, and network interface 63 is shown in the figure; however, it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described herein is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.
[0083] Computer devices can include desktop computers, laptops, handheld computers, and cloud servers. These devices allow for human-computer interaction with users through keyboards, mice, remote controls, touchpads, or voice-activated devices.
[0084] The memory 61 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 61 may be an internal storage unit of the computer device 6, such as the hard disk or memory of the computer device 6. In other embodiments, the memory 61 may also be an external storage device of the computer device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 6. Of course, the memory 61 may also include both the internal storage unit and the external storage device of the computer device 6. In this embodiment, the memory 61 is typically used to store the operating system and various application software installed on the computer device 6, such as computer-readable instructions for the simulation optimization design method of the oscillating motor stator. In addition, memory 61 can also be used to temporarily store various types of data that have been output or will be output.
[0085] In some embodiments, processor 62 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. This processor 62 is typically used to control the overall operation of the computer device 6. In this embodiment, processor 62 is used to execute computer-readable instructions stored in memory 61 or to process data, such as computer-readable instructions for executing a simulation optimization design method for the stator of a swing motor.
[0086] The network interface 63 may include a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the computer device 6 and other electronic devices.
[0087] This application also provides an implementation method, namely, a computer device including a memory and a processor. The memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, it implements the steps of the simulation optimization design method for the stator of the swing motor as described above, that is, it implements: A simulation optimization design method for the stator of a oscillating motor, applied to an oscillating motor system, includes the following steps: In response to simulation optimization task requests from the user, the simulation modeling data related to the simulation optimization task requests is received and used for simulation modeling of the oscillating motor stator. Obtain the simulation optimization conditions, which are used to guide the number of iterations in the simulation optimization process; The simulation optimization design report is sent to the user terminal. The simulation optimization design report is a design report generated by the system through electromagnetic simulation software to simulate and model the simulation modeling data and simulation optimization conditions. The design goal of the simulation modeling is to reduce the axial force of the stator of the swing motor.
[0088] This application also provides another implementation, namely, a computer-readable storage medium storing computer-readable instructions that can be executed by at least one processor to cause the at least one processor to perform the steps of the simulation optimization design method for the oscillating motor stator described above, i.e., to achieve: A simulation optimization design method for the stator of a oscillating motor, applied to an oscillating motor system, includes the following steps: In response to simulation optimization task requests from the user, the simulation modeling data related to the simulation optimization task requests is received and used for simulation modeling of the oscillating motor stator. Obtain the simulation optimization conditions, which are used to guide the number of iterations in the simulation optimization process; The simulation optimization design report is sent to the user terminal. The simulation optimization design report is a design report generated by the system through electromagnetic simulation software to simulate and model the simulation modeling data and simulation optimization conditions. The design goal of the simulation modeling is to reduce the axial force of the stator of the swing motor.
[0089] To address the aforementioned technical problems, this application also provides a computer program product that employs the following technical solution: A computer program product, when run on a terminal device, causes the terminal device to execute the steps of the simulation optimization design method for the stator of the oscillating motor as described above, i.e., to achieve: A simulation optimization design method for the stator of a oscillating motor, applied to an oscillating motor system, includes the following steps: In response to simulation optimization task requests from the user, the simulation modeling data related to the simulation optimization task requests is received and used for simulation modeling of the oscillating motor stator. Obtain the simulation optimization conditions, which are used to guide the number of iterations in the simulation optimization process; The simulation optimization design report is sent to the user terminal. The simulation optimization design report is a design report generated by the system through electromagnetic simulation software to simulate and model the simulation modeling data and simulation optimization conditions. The design goal of the simulation modeling is to reduce the axial force of the stator of the swing motor.
[0090] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of the various embodiments of this application.
[0091] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.
[0092] It should be noted that the software tools or components not belonging to this company that appear in the various embodiments of this application are merely illustrative examples and do not represent actual use.
[0093] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.
Claims
1. A simulation optimization design method for the stator of an oscillating motor, characterized in that, Applied to a swing motor system, the method includes: In response to a simulation optimization task request from the user terminal, simulation modeling data related to the simulation optimization task request is received, and the simulation modeling data is used for simulation modeling of the stator of the swing motor. Obtain simulation optimization conditions, which are used to guide the number of iterations in the simulation optimization process; A simulation optimization design report is sent to the user terminal. The simulation optimization design report is a design report generated by the system through electromagnetic simulation software to simulate and model the simulation modeling data and the simulation optimization conditions. The design goal of the simulation modeling is to reduce the axial axial force of the stator of the swing motor.
2. The simulation optimization design method for the stator of the oscillating motor as described in claim 1, characterized in that, After responding to the simulation optimization task request from the user, the method further includes: Identify the simulation modeling object that matches the simulation optimization task request, the simulation modeling object including stator magnet and / or mover permanent magnet; The simulation modeling object is used to adapt to the simulation database, simulation modeling method, and optimization method used in the simulation modeling process.
3. The simulation optimization design method for the stator of the oscillating motor as described in claim 2, characterized in that, The simulation modeling data includes the motor structure data, geometric parameter data, and material type data of the modeling object. Receiving the simulation modeling data related to the simulation optimization task request includes: When the first window of the user terminal is triggered, the motor structure data is obtained from the user terminal. The first window is configured to identify the simulation modeling object selected by the user. When the second window of the user terminal is triggered, the geometric parameter data is obtained from the user terminal. The second window is configured to obtain the geometric parameters set by the user for the simulation modeling object. When the third window of the user terminal is triggered, the material type data is obtained from the user terminal. The third window is configured to obtain the material type selected by the user for the simulation modeling object.
4. The simulation optimization design method for the stator of the oscillating motor as described in claim 3, characterized in that, The step of obtaining the geometric parameter data from the user terminal when the second window of the user terminal is triggered includes: Based on the simulation modeling object selected by the user, obtain a set of standard geometric parameter examples that match the simulation modeling object. The simulation modeling objects in the set of standard geometric parameter examples carry pre-annotated geometric parameters. The second window displays either a global or sequential set of standard geometric parameter examples for the simulation modeling object. The second window captures the target standard example selected by the user and obtains the geometric parameter data of the target standard example; Alternatively, a geometric parameter input box for the simulation modeling object can be generated on the second window, and the geometric parameter data input by the user can be obtained through the geometric parameter input box.
5. The simulation optimization design method for the stator of the oscillating motor as described in claim 4, characterized in that, When the simulation modeling object includes a stator magnet and a mover permanent magnet, the geometric parameter data includes the stator magnet length, the mover permanent magnet length, the outer diameter of the stator magnet outer circle, the inner diameter of the stator magnet inner circle, the outer diameter of the mover permanent magnet outer circle, the bearing hole depth, and the difference between the outer radius of the bearing hole and the inner radius of the stator magnet inner circle.
6. The simulation optimization design method for the stator of the oscillating motor as described in claim 3, characterized in that, When the third window of the user terminal is triggered, the process of obtaining the material type data from the user terminal includes: Based on the simulation modeling object selected by the user, obtain a standard material type example set that matches the simulation modeling object. The standard material type example set records all material types that can be used by the simulation modeling object. On the third window, generate material type selection buttons for the simulation modeling object, and fill in a standard material type example in each material type selection button; When the material type selection button on the third window is triggered, the material type data selected by the user is obtained.
7. The simulation optimization design method for the stator of the oscillating motor as described in claim 1, characterized in that, Before responding to the simulation optimization task request from the user and receiving the simulation modeling data related to the simulation optimization task request, the method further includes: Construct a simulation database, which is used to store simulation data; Obtain all simulation modeling results generated during the simulation optimization process; each simulation optimization calculation will generate a simulation modeling result. The simulation modeling data, the simulation optimization conditions, all the simulation modeling results, and the simulation optimization design report are stored in the simulation database.
8. A simulation optimization design device for the stator of a swing motor, characterized in that, The device is equipped with a swing motor system, and the device includes: The data acquisition module is used to respond to simulation optimization task requests from the user terminal and receive simulation modeling data related to the simulation optimization task request. The simulation modeling data is used for simulation modeling of the stator of the swing motor. The simulation conditions module is used to obtain simulation optimization conditions, which are used to guide the number of iterations in the simulation optimization process. The simulation optimization module is used to send a simulation optimization design report to the user terminal. The simulation optimization design report is a design report generated by the system through electromagnetic simulation software to simulate and model the simulation modeling data and the simulation optimization conditions. The design goal of the simulation modeling is to reduce the axial axial force of the stator of the swing motor.
9. A computer device, characterized in that, The computer device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the simulation optimization design method for the stator of the oscillating motor as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the simulation optimization design method for the stator of the oscillating motor as described in any one of claims 1 to 7.