High-speed motor permanent magnet rotor strength analytical calculation method and system

Abstract

The application provides a high-speed motor permanent magnet rotor strength analytical calculation method and system, and relates to the technical field of high-speed motors.The method comprises the following steps: obtaining an initial non-uniform temperature field with specific gradient characteristics formed in the axial direction of a high-speed motor rotor under operating conditions; based on the gradient characteristics of the initial non-uniform temperature field, field characteristic monitoring points are dynamically arranged at key positions of the rotor; the key positions at least include the axial end portions and the middle cross sections of each segmented permanent magnet, the interface regions between the permanent magnets and the carbon fiber retaining sleeves, and the interface transition regions between adjacent permanent magnet segments; temperature data of the field characteristic monitoring points are acquired in real time, and based on the real-time acquired temperature data, a dynamic envelope surface representing the overall temperature field spatial evolution characteristics of the rotor is constructed.The application can accurately quantify the dynamic influence of the temperature field, improve the strength calculation accuracy, and ensure the safe operation of the high-speed permanent magnet motor rotor and the stability of the whole machine.

Description

Technical Field

[0001] This invention relates to the field of high-speed motor technology, and in particular to a method and system for analytical calculation of the strength of a permanent magnet rotor in a high-speed motor. Background Technology

[0002] In high-efficiency drive scenarios for high-end equipment, high-speed permanent magnet motors are widely used in high-speed machine tools, aerospace, and other fields due to their advantages of high power density and high efficiency. For example, they have become the core power unit in the drive system of high-speed precision machining equipment. The rotor, as the core component, is assembled by interference fit of permanent magnets, magnetic shielding blocks, and carbon fiber sheaths. Its operational safety determines the reliability of the entire machine.

[0003] Under high-speed operation, the rotor linear velocity reaches a high level, and the thermal expansion coefficients and heat transfer coefficients of the materials of various components differ significantly. The carbon fiber sheath is anisotropic and has a low radial thermal conductivity, resulting in dynamic heat sources generated by electromagnetic losses during rotor operation. This leads to a non-uniform temperature field with obvious axial and radial gradients. Therefore, the coupling effect between the temperature field, stress field, and material properties is crucial for strength calculation. Existing methods generally suffer from the following technical defects: they fail to accurately capture the dynamic evolution characteristics of the non-uniform temperature field, often employ constant temperature assumptions or static models, ignore the dynamic gradient characteristics of the temperature field, and fail to correct for spatial distortion.

[0004] This defect can lead to the following related problems: not only can it not accurately quantify the nonlinear fluctuations of the material's elastic parameters, resulting in a significant deviation between the material's constitutive relationship and the actual working conditions; but also, when solving for multi-field coupled stress fields based on inaccurate data, it is difficult to accurately reflect the synergistic effect of centrifugal load, assembly interference, and interface contact nonlinearity, ultimately leading to unreliable strength verification results, which can easily cause hidden dangers such as permanent magnet cracks and demagnetization, affecting the stable operation of the motor. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and system for analytical calculation of the strength of permanent magnet rotor of high-speed motor, which can accurately quantify the dynamic influence of temperature field, improve the accuracy of strength calculation, and ensure the safe operation of rotor of high-speed permanent magnet motor and the stability of the whole machine.

[0006] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0007] Firstly, a method for analytically calculating the strength of a permanent magnet rotor in a high-speed motor, the method comprising:

[0008] Obtain the initial non-uniform temperature field with specific gradient characteristics formed axially by the rotor of a high-speed motor under operating conditions;

[0009] Based on the gradient characteristics of the initial non-uniform temperature field, field characteristic monitoring points are dynamically arranged at key parts of the rotor; the key parts include at least the axial ends and middle sections of each segment of permanent magnet, the interface area between the permanent magnet and the carbon fiber sheath, and the interface transition area between adjacent permanent magnet segments.

[0010] The temperature data of the field feature monitoring points are acquired in real time. Based on the acquired temperature data, a dynamic envelope surface is constructed to characterize the spatial evolution of the overall temperature field of the rotor. The surface area change rate of the dynamic envelope surface between adjacent calculation time steps is calculated to generate a temperature field distortion correction factor.

[0011] The initial non-uniform temperature field is corrected in real time by temperature field distortion correction factor to obtain accurate non-uniform temperature field, and at the same time, the nonlinear fluctuation of material elastic parameters caused by accurate non-uniform temperature field is determined.

[0012] Based on the precise non-uniform temperature field and the nonlinear fluctuation of the material's elastic parameters, and simultaneously applying a centrifugal load determined by the rotational speed and an assembly interference fit, the multi-field coupled stress field of the rotor is solved under the condition of considering the nonlinearity of the interface contact.

[0013] In the multi-field coupled stress field, the contact stress state at the interface of the segmented permanent magnet is extracted, and the axial strain compensation coefficient is calculated through a pre-constructed dynamic correlation model.

[0014] The axial stress is corrected based on the axial strain compensation coefficient, and the strength of the permanent magnet rotor is verified by combining radial and tangential stresses.

[0015] Secondly, the high-speed motor permanent magnet rotor strength analytical calculation system includes:

[0016] The temperature field acquisition module is used to acquire the initial non-uniform temperature field with specific gradient characteristics formed axially by the rotor of a high-speed motor under operating conditions.

[0017] The monitoring point layout module is used to dynamically arrange field feature monitoring points at key parts of the rotor according to the gradient characteristics of the initial non-uniform temperature field; the key parts include at least the axial ends and middle sections of each segment of permanent magnet, the interface area between the permanent magnet and the carbon fiber sheath, and the interface transition area between adjacent permanent magnet segments.

[0018] The construction and calculation module is used to acquire temperature data of the field feature monitoring points in real time. Based on the acquired temperature data, a dynamic envelope surface is constructed to characterize the spatial evolution of the overall temperature field of the rotor. The surface area change rate of the dynamic envelope surface between adjacent calculation time steps is calculated to generate a temperature field distortion correction factor.

[0019] The correction and determination module is used to correct the initial non-uniform temperature field in real time through the temperature field distortion correction factor to obtain the accurate non-uniform temperature field, and at the same time determine the nonlinear fluctuation of the material elastic parameters caused by the accurate non-uniform temperature field.

[0020] The stress field solving module is used to solve the multi-field coupled stress field of the rotor based on the accurate non-uniform temperature field and the nonlinear fluctuation of the elastic parameters of the material, while applying the centrifugal load determined by the rotational speed and the assembly interference, and considering the nonlinearity of the interface contact.

[0021] The final processing and verification module is used to extract the contact stress state at the interface of the segmented permanent magnet in the multi-field coupled stress field, calculate the axial strain compensation coefficient through a pre-built dynamic correlation model, correct the axial stress according to the axial strain compensation coefficient, and complete the strength verification of the permanent magnet rotor by combining radial and tangential stresses.

[0022] The above-described solution of the present invention has at least the following beneficial effects:

[0023] By employing techniques such as dynamically arranging field feature monitoring points, constructing a dynamic envelope surface of the temperature field to generate distortion correction factors, combining the corrected precise temperature field to quantify the nonlinear fluctuations of material elastic parameters, and simultaneously considering centrifugal loads, assembly interference, and interface contact nonlinearity to solve multi-field coupled stress fields, and calculating axial strain compensation coefficients through dynamic correlation models to correct stress, this approach effectively overcomes the technical problems of existing methods that cannot accurately capture the dynamic evolution characteristics of non-uniform temperature fields, leading to significant deviations between material constitutive relations and actual working conditions, inaccurate solutions to multi-field coupled stress fields, and unreliable strength verification results. This approach precisely improves the accuracy of strength calculations for permanent magnet rotors in high-speed motors, ensures rotor operating safety, guarantees the stable operation of the entire high-speed permanent magnet motor, and provides reliable technical support for rotor safety design. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating the analytical calculation method for the strength of a permanent magnet rotor in a high-speed motor, provided in an embodiment of the present invention.

[0025] Figure 2 This is a schematic diagram of a high-speed motor permanent magnet rotor strength analytical calculation system provided in an embodiment of the present invention. Detailed Implementation

[0026] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0027] like Figure 1 As shown, embodiments of the present invention propose an analytical calculation method for the strength of a permanent magnet rotor in a high-speed motor, the method comprising the following steps:

[0028] Step 1: Obtain the initial non-uniform temperature field with specific gradient characteristics formed axially by the high-speed motor rotor under operating conditions;

[0029] Step 2: Based on the gradient characteristics of the initial non-uniform temperature field, dynamically arrange field characteristic monitoring points at key parts of the rotor; the key parts include at least the axial ends and middle sections of each segment of permanent magnet, the interface area between the permanent magnet and the carbon fiber sheath, and the interface transition area between adjacent permanent magnet segments.

[0030] Step 3: Acquire the temperature data of the field feature monitoring points in real time. Based on the acquired temperature data, construct a dynamic envelope surface that characterizes the spatial evolution of the overall temperature field of the rotor. Calculate the surface area change rate of the dynamic envelope surface between adjacent calculation time steps and generate a temperature field distortion correction factor.

[0031] Step 4: The initial non-uniform temperature field is corrected in real time by the temperature field distortion correction factor to obtain the accurate non-uniform temperature field, and at the same time, the nonlinear fluctuation of the material elastic parameters caused by the accurate non-uniform temperature field is determined.

[0032] Step 5: Based on the precise non-uniform temperature field and the nonlinear fluctuation of the material's elastic parameters, and simultaneously applying a centrifugal load determined by the rotational speed and an assembly interference, the multi-field coupled stress field of the rotor is solved under the condition of considering the nonlinearity of the interface contact.

[0033] Step 6: In the multi-field coupled stress field, extract the contact stress state at the interface of the segmented permanent magnet, and calculate the axial strain compensation coefficient through the pre-constructed dynamic correlation model.

[0034] Step 7: Correct the axial stress according to the axial strain compensation coefficient, and complete the strength verification of the permanent magnet rotor by combining radial and tangential stresses.

[0035] In this embodiment of the invention, by dynamically arranging field feature monitoring points and generating temperature field distortion correction factors, the dynamic evolution of the rotor's non-uniform temperature field is accurately captured; by combining precise temperature field quantification of the nonlinear fluctuations of material elastic parameters, the accuracy of solving the multi-field coupled stress field is ensured; by calculating the axial strain compensation coefficient and correcting the axial stress through a dynamic correlation model, the rotor strength verification process is optimized; through the above series of technical means, the safe operation of the permanent magnet rotor is effectively guaranteed, supporting the stable operation of the entire high-speed permanent magnet motor and providing strong technical support for rotor safety design.

[0036] In a preferred embodiment of the present invention, step 1 above may include:

[0037] Step 1.1: Determine the structural composition of the high-speed motor rotor. The high-speed motor rotor consists of permanent magnets, magnetic shielding blocks, and a carbon fiber sheath assembled with an interference fit. Specifically, this involves: First, clarifying the information acquisition path for the structural composition, prioritizing the retrieval of detailed design drawings, component assembly specifications, and the manufacturer's material list to initially clarify the rotor's component composition and pre-designed assembly method; then, selecting a physical rotor consistent with the design parameters and disassembling it according to a standardized process from the outside in, recording the connection status and relative position of each component throughout the process, focusing on verifying the number and arrangement of permanent magnet segments, the fitting accuracy between the magnetic shielding blocks and permanent magnets, and the number and coverage of the carbon fiber sheath, clarifying the uniform distribution pattern of the magnetic shielding blocks among adjacent permanent magnets; finally, combining the drawing information and the physical disassembly results, confirming that the rotor consists of permanent magnets, magnetic shielding blocks, and a carbon fiber sheath. These three types of components are assembled with an interference fit. The magnetic shielding blocks are responsible for isolating magnetic field interference from adjacent permanent magnets, the carbon fiber sheath provides radial constraint and protective enclosure for internal components, and the interference fit ensures no relative displacement of components during high-speed rotor rotation, ensuring a comprehensive and accurate determination of the structural composition.

[0038] Step 1.2: Based on the actual assembly relationship between the permanent magnet, the magnetic shielding block, and the carbon fiber sheath, construct an equivalent geometric structure model of the rotor considering material anisotropy. Specifically, this includes: Based on the assembly relationship confirmed in Step 1.1, initiate geometric modeling. The rotor equivalent geometric structure model constructed in this step is an improvement upon the parametric-driven mechanical component equivalent modeling architecture. The focus is on optimizing the multi-component assembly constraint modeling module and the material anisotropy parameter embedding module to adapt to the collaborative work of multiple components in a high-speed motor rotor and the anisotropic characteristics of the carbon fiber sheath. First, conduct preliminary preparation work, planning the dimension acquisition process according to the axial and radial dimensions, targeting the permanent magnet, magnetic shielding block, and carbon fiber sheath. The key dimensions of the three core components of the fiber sheath were collected one by one. First, the axial length and radial thickness of the permanent magnet were collected. Then, the length, width, and thickness of the magnetic shielding block and the contour tolerance of the surface in contact with the permanent magnet were accurately collected. Finally, the total axial length, radial wall thickness, and inner surface chamfer dimensions of the carbon fiber sheath were collected. At the same time, key assembly parameters such as the roughness and tolerance range of the mating surfaces of each component were recorded to ensure that the dimensional data completely matched the actual object. Meanwhile, the material properties of each component were collected. The data on the thermal conductivity and elastic modulus of the carbon fiber sheath in the axial and radial directions were sorted out by combining material sample testing and manual consultation to clarify its anisotropic characteristics and lay the foundation for giving the model real material properties.

[0039] The core of the model construction phase follows a process of unified positioning benchmark, precise modeling of individual components, and pre-assembly verification. First, a unified positioning benchmark is established, creating a global unified coordinate system as the positioning benchmark for all component modeling. The central axis of the rotor shaft is used as the Z-axis, corresponding to the rotor's axial direction. The center of the shaft's cross-section is used as the origin, and the radial direction perpendicular to the Z-axis is used as the XY axis. This coordinate system ensures precise alignment of the relative positions of each component during modeling, guaranteeing that the coaxiality of the assembled model meets the requirements of high-speed motor rotor rotation. Next, the permanent magnet components are modeled individually. The number of segments and the distribution pattern of each segment of the permanent magnet are clearly defined. The measured data such as the axial length and radial thickness of each segment are used as the basis for modeling. The cross-sectional outline of each segment of the permanent magnet is outlined using the XZ plane of the global coordinate system as the reference plane. That is, the rectangular outline that matches the measured size is used to complete the solid structure of the segment of the permanent magnet. Then, with the Z-axis as the rotation center, the structure of each segment of the permanent magnet is copied and rotated at equal angles to complete the solid construction of all segments of the permanent magnet. Finally, the number of each segment of the permanent magnet and the gap status between adjacent segments are marked, that is, whether they are fitted or reserved gaps, to ensure that the segment distribution is completely consistent with the actual object.

[0040] Subsequently, the modeling of the magnetic shielding blocks was carried out. Based on the distribution pattern of the magnetic shielding blocks between adjacent permanent magnets, the gap dimensions and mating surface contour data of two adjacent permanent magnet segments were first extracted. A local auxiliary coordinate system was established in the gap area between adjacent permanent magnets, with the X' axis parallel to the mating surface of the permanent magnet and the Z' axis coinciding with the global Z-axis. Using the local coordinate system as a reference, combined with the measured length, width, and thickness data of the magnetic shielding blocks, the cross-sectional contour of the magnetic shielding blocks was outlined and the solid structure was constructed. The modeling of all magnetic shielding blocks was completed in sequence according to the above method. During the process, the mating of the magnetic shielding blocks with adjacent permanent magnets was checked in real time to ensure that the two mating surfaces of the magnetic shielding blocks were completely mated with the mating surfaces of the corresponding permanent magnets, without overlap or gap deviation. Finally, the modeling of the carbon fiber sheath was completed. Based on the measured total axial length, radial wall thickness, and inner surface chamfer dimensions of the sheath, the cross-sectional contour of the sheath, i.e., the annular contour, was first outlined with the Z-axis of the global coordinate system as the center. The outer and inner diameters were accurately calculated according to the measured wall thickness. The hollow cylindrical solid structure of the sheath was constructed according to the outline, with the construction length matching the measured total axial length. Subsequently, the two ends of the inner surface of the sheath were chamfered, with the chamfer dimensions strictly matching the measured data. Finally, the anisotropic parameters of the carbon fiber woven sheath, including axial thermal conductivity, radial thermal conductivity, axial elastic modulus, and radial elastic modulus, were embedded into the model's material property system. The anisotropic characteristics were clearly defined, and the corresponding parameters were associated with the Z-axis (axial) and XY-axis (radial) respectively, ensuring that the model accurately reproduces the anisotropic characteristics of the sheath.

[0041] After completing the component modeling, based on the interference fit relationships confirmed in step 1.1, the components are assembled in the order of shaft, permanent magnet, magnetic shielding block, and carbon fiber braided sheath. The actual interference fit state is simulated by setting assembly constraints: a contact constraint is set between the permanent magnet and shaft, a contact constraint is set between the magnetic shielding block and permanent magnet, and an interference constraint is set between the sheath and the internal permanent magnet and magnetic shielding block assembly. The interference amount matches the measured values. Finally, model verification and optimization are carried out, which is the model training process adapted to this invention. Two key sections are selected: the axial middle section and the two end sections of the rotor. The dimensional data of the corresponding sections of the actual rotor are measured and compared with the corresponding dimensions of the model sections. If there are deviations, the dimensional parameters of the component model are corrected first, and then the assembly constraints are adjusted. In particular, for the anisotropic parameters of the carbon fiber braided sheath, the model parameters are calibrated by simulating its radial thermal conductivity and comparing it with the measured data. After two to three rounds of iterative optimization, the relative positions and fit relationships of each component in the model are ensured to be completely consistent with the actual rotor, and the anisotropic characteristics of the carbon fiber braided sheath can be accurately reproduced. Finally, the rotor equivalent geometric structure model that meets the requirements of subsequent electromagnetic loss calculation and temperature field calculation is obtained.

[0042] Step 1.3, based on the rotor equivalent geometric structure model, calculates the electromagnetic loss distribution in the permanent magnet and sheath by combining the electromagnetic parameters at the current operating speed, and generates a dynamic electromagnetic heat source. Specifically, this includes: importing the constructed rotor equivalent geometric structure model into the electromagnetic simulation analysis platform as the basic carrier for electromagnetic loss calculation; first, establishing a real-time electromagnetic parameter acquisition link, arranging current, voltage, and magnetic flux density sensors at the stator winding input end, output end, and stator-rotor air gap region, setting the acquisition timing to be synchronized with the rotor operating speed, and setting the acquisition frequency to meet the dynamic parameter capture requirements; capturing core data such as stator three-phase current, peak and effective values ​​of terminal voltage, and air gap magnetic flux density distribution at the current speed in real time through the sensors; performing noise reduction processing on the acquired data, and setting a reasonable amplitude change threshold: combining the normal fluctuation range of electromagnetic parameters during normal motor operation, obtaining the maximum normal fluctuation value through pre-experiment statistics, and determining the threshold by reserving a safety margin of 10% to 20% on this basis, and then comparing the current data with the previous valid data. If the difference exceeds the threshold, the abnormal signal is discarded, and the previous valid data is retained. At the same time, the original data and the processed data are saved for subsequent cross-validation.

[0043] Based on the classical electromagnetic loss calculation theory, relying on the principle of electromagnetic induction and combining key parameters such as the alternating frequency of the magnetic field and the amplitude of the magnetic flux density, the energy loss of different components due to electromagnetic induction under the action of a magnetic field is calculated. Then, combined with the collected electromagnetic parameters and the model structure dimensions, independent calculation areas are divided according to permanent magnets and carbon fiber woven sheaths, and each area is assigned corresponding electromagnetic properties. In the simulation platform, the electromagnetic parameters and model structure characteristics are correlated to obtain the electromagnetic induction distribution of each area. The eddy current loss generated by the permanent magnet in the alternating magnetic field, as well as the hysteresis loss and eddy current loss generated by the carbon fiber woven sheath, are calculated separately to confirm the spatial distribution law of various losses inside the components. The loss distribution data that changes dynamically with the rotational speed is accurately mapped and loaded and transformed according to the model coordinates: first, the correspondence between the spatial coordinates of the loss distribution data and the coordinates of the rotor equivalent geometric model is established; then, the loss density values ​​at each spatial location are matched to the corresponding areas of the model according to the coordinates; finally, these loss data are converted into a heat source input form that can be recognized by the simulation platform to form dynamic electromagnetic heat source data. At the same time, the coordinate matching degree of the mapping results is verified to ensure that the heat source position and intensity are consistent with the actual loss distribution.

[0044] Step 1.4 uses a dynamic electromagnetic heat source as input and, by combining the radial thermal conductivity of the carbon fiber sheath, analytically calculates the initial non-uniform temperature field with specific gradient characteristics formed in the axial direction of the high-speed motor rotor. Specifically, this includes: firstly, collecting and verifying thermal properties; for the radial thermal conductivity of the carbon fiber braided sheath, selecting material samples from the same batch as the rotor sheath and conducting experimental measurements; reducing random errors through repeated testing; and taking the average of the measurement results to obtain accurate radial thermal conductivity data; simultaneously, consulting authoritative material performance handbooks to collect key thermal properties such as thermal conductivity, specific heat capacity, and heat dissipation coefficient of permanent magnets and magnetic shielding blocks; cross-referencing experimental measurement data with handbook data; and eliminating abnormal data exceeding reasonable deviation ranges through deviation analysis to ensure the consistency and reliability of all thermal properties.

[0045] Using the generated dynamic electromagnetic heat source as the core energy input condition, and combining the verified thermophysical parameters of each component, the heat transfer zone is divided according to the actual structural characteristics of the rotor. Specifically, the zone is divided according to different functional sections in the axial direction and different material layers in the radial direction, confirming the range of each zone and the heat transfer interface between adjacent zones. Within the divided heat transfer zone, the heat transfer boundary conditions are defined. For the convective heat transfer boundary between the rotor outer surface and the air, the basic value of the convective heat transfer coefficient is initially estimated based on the operating conditions of the high-speed motor and common industrial experience. Then, by tracking the changes in the rotor's real-time operating speed, the value of the heat transfer coefficient is dynamically adjusted: the coefficient is appropriately increased when the speed increases to match a stronger convective heat transfer effect, and the coefficient is correspondingly decreased when the speed decreases. For the thermal conductivity boundary between the rotor inner hole and the shaft, the contact state after actual assembly is observed first, and the interference data recorded in the assembly process is used to determine the tightness of the contact. Then, the corresponding contact thermal resistance is set. The tighter the contact, the smaller the set thermal resistance. When there is a small gap in the contact, the thermal resistance is appropriately increased.

[0046] A segmented, progressive approach was adopted for heat transfer analysis. First, for each radially layered region, the heat transfer path and temperature changes in the radial direction were calculated one by one to obtain the temperature distribution data of each radial layer. Then, the temperature data of each radial layer was correlated with the axial heat transfer process. Along the rotor axis from one end to the other, the efficiency decay law of heat transfer in the axial process was analyzed step by step, and the temperature change trend at different axial positions was tracked. Temperature monitoring nodes were set up in each segmented region of the axial direction. By comparing the temperature values ​​of different nodes, the formation process and gradient change law of the axial temperature gradient were accurately captured. The calculated temperature distribution results were compared with the measured temperature data under simplified operating conditions, and the deviation value was statistically analyzed. Based on the magnitude of the deviation, the values ​​of thermophysical parameters or the setting of boundary conditions were adjusted accordingly. After multiple rounds of such iterative verification and parameter optimization, the deviation between the calculated results and the measured data was gradually reduced. Finally, the initial non-uniform temperature field with specific gradient characteristics formed by the high-speed motor rotor in the axial direction was obtained.

[0047] In a preferred embodiment of the present invention, step 2 above may include:

[0048] Step 2.1: Analyze the axial and radial gradient distribution of the initial non-uniform temperature field and determine the extreme values ​​and rates of change of the gradient field. Specifically, based on the obtained initial non-uniform temperature field data, divide the analysis region according to the rotor's structural segments, material layer boundaries, and potential temperature-sensitive areas. Axially, prioritize dividing the analysis segment according to the permanent magnet segments, the distribution range of the magnetic shielding blocks, and the axial boundary of the sheath. Radially, strictly follow the material layer interfaces of the shaft, permanent magnet, and carbon fiber woven sheath to divide the analysis layer. Simultaneously, separate the interface regions where gradient changes may be drastic as key analysis sub-regions. First, for the axial direction, extract temperature data point-by-point along the analysis segment from one end of the rotor to the other, calculate the temperature difference between adjacent positions point-by-point and normalize it to a unit length, and plot the axial temperature... Gradient distribution curves are generated, and abrupt changes in the curves are marked. Then, for the radial direction, temperature data is extracted along the analytical layers from the rotor center to the outer surface. The temperature difference between adjacent layers is calculated and normalized to a unit length, and a radial temperature gradient distribution curve is plotted to clarify the gradient change trend within each material layer. Subsequently, the correspondence between gradient values ​​and axial, radial, and circumferential three-dimensional coordinates is established. Gradient data from all analytical regions and key sub-regions are traversed. By sorting and filtering, the three-dimensional spatial coordinates corresponding to the maximum and minimum temperature gradient values ​​are selected as extreme value locations. Simultaneously, the change in gradient value at each location with respect to the three-dimensional coordinates is calculated, and a correlation matrix between the gradient change rate and spatial location is established. Matrix verification ensures no gradient data is missed, thus fully grasping the gradient distribution characteristics of the initial non-uniform temperature field.

[0049] Step 2.2: Based on the extreme locations and rate of change of the gradient field, a preliminary set of initial field characteristic monitoring points is selected at key locations on the rotor. These key locations include the axial end sections of each segmented permanent magnet, the middle sections of each segmented permanent magnet, the interface region between the permanent magnet and the carbon fiber sheath, and the interface transition region between adjacent permanent magnet segments. Specifically, this includes: combining the determined gradient field distribution characteristics with the actual structure of the rotor, and conducting a preliminary selection of the initial field characteristic monitoring point set around the preset key locations, prioritizing gradient sensitivity and structural criticality; for the axial end sections of each segmented permanent magnet, monitoring points are evenly selected based on the boundary positions of the radial material layers, with at least one monitoring point at each material layer boundary, covering the complete radial range from the inner side of the permanent magnet where it contacts the shaft to the outer side where it intersects with the sheath, ensuring the capture of the temperature gradient of each material layer at the end section; for the middle sections of each segmented permanent magnet, the monitoring points are selected with the center of the section as the base... Monitoring points are selected in a multi-ring distribution, with the radius of the rings corresponding to the center positions of different radial material layers. Monitoring points are evenly distributed in each ring to ensure the capture of temperature uniformity differences in different radial regions of the cross-section. For the interface region between the permanent magnet and the carbon fiber woven sheath, sampling segments are divided at equal intervals along the axial length of the interface. Monitoring points are then evenly distributed in the circumferential range of each sampling segment to ensure coverage of the entire axial length and circumferential range of the interface. For the interface transition region between adjacent permanent magnet segments, two monitoring points are added before and after the transition interface along the axial direction. The added points are kept at equal distances from the transition interface to form a symmetrically distributed monitoring point group, enabling continuous capture of temperature changes in the transition region. Finally, the monitoring points of each key part are integrated, overlapping points are eliminated by spatial coordinate comparison, and missing points are added for gradient extreme value positions. The complete coverage of the point set for the entire key region is verified, and the initial field feature monitoring point set is finally formed.

[0050] Step 2.3: Based on the temperature data fed back by the initial field feature monitoring point set within the first calculation time step, evaluate the completeness of the point set in capturing the spatial features of the temperature field, and based on a preset gradient change rate threshold, identify insufficiently covered areas where the gradient change rate exceeds the threshold. Specifically, this includes: starting the temperature field simulation for the first calculation time step, simultaneously enabling the data acquisition function of the initial field feature monitoring point set, setting a continuous acquisition cycle, and collecting multiple sets of temperature data for each monitoring point; firstly, filtering the collected temperature data for validity, eliminating abnormal fluctuation data by calculating the standard deviation of the data, and retaining valid temperature data with a standard deviation within a reasonable range to ensure data reliability; then, statistically analyzing the effective temperature data coverage of each key location to determine whether each key location has continuous and complete temperature data feedback without data gaps; subsequently, combining the full gradient determined in Step 2.1... The distribution range is compared with the gradient intervals covered by the monitoring points. The focus is on evaluating the capture of temperature characteristics of high gradient regions, gradient abrupt change points, and extreme value locations by the monitoring point set. If there are continuous intervals in high gradient regions that are not covered by monitoring points, or if no monitoring points are set at extreme value locations, the capture is considered incomplete. At the same time, a preset gradient change rate threshold is retrieved. The preset gradient change rate threshold is determined by fitting and deducing multiple sets of experimental data under different working conditions in the early stage, taking into account the balance between the accuracy of temperature field calculation and the computational efficiency. The gradient change rate data of all analytical regions and key sub-regions are traversed, and the gradient change rate of each region is compared with the preset threshold one by one. Regions with gradient change rates exceeding the threshold but not fully covered by the initial monitoring point set are marked. The axial start and end coordinates, radial upper and lower boundaries, and circumferential distribution range of these regions are confirmed, and the peak position and trend of gradient change in the region are marked.

[0051] Step 2.4: Based on the identified insufficiently covered areas, dynamically adjust the position and density of field feature monitoring points to increase the number of field feature monitoring points in the insufficiently covered areas. Optimize the distribution of field feature monitoring points in areas where the gradient change rate is below the threshold, forming an optimized dynamic monitoring point layout scheme. Specifically, this includes: for the identified insufficiently covered areas, first establish a regional feature analysis table, recording in detail the spatial range, gradient change peak, change trend, and adjacent structural features of the area; then, formulate targeted adjustment strategies based on the analysis results. If the area is small and the gradient change is concentrated, dynamically set the densification interval within the area according to the intensity of the gradient change; the more intense the gradient change, the smaller the interval, ensuring that the spacing between adjacent newly added monitoring points can completely cover the continuous interval of the gradient change, avoiding missing gradient abrupt changes. If the area is large, divide it into secondary sub-regions according to the uniformity of the gradient change, so that each sub-region... The gradient change trend within the region is consistent. Monitoring points are added at equal intervals within each sub-region, and transition monitoring points are added at the boundaries of the sub-regions to ensure the continuity of temperature data between sub-regions. For regions where the gradient change rate is lower than a preset threshold, the temperature correlation coefficient between adjacent monitoring points is calculated. If the coefficient is higher than the preset correlation threshold, it indicates that there is redundancy in the monitoring points. Monitoring points that are too close are merged first, and points with stronger temperature representativeness are retained. Redundant points that can be completely derived from the data of surrounding monitoring points are directly deleted to reduce invalid data collection. During the adjustment process, the location coordinates, coverage area, and corresponding gradient characteristics of each monitoring point are recorded simultaneously. After the adjustment is completed, the coverage integrity of the new point set is checked to ensure that there are no newly added uncovered high gradient areas. At the same time, the density of the point set is checked to avoid excessive densification that leads to a decrease in computational efficiency. Finally, an optimized dynamic monitoring point layout scheme is formed.

[0052] Step 2.5: Based on the optimized dynamic monitoring point layout scheme, starting from the second calculation step, the field feature monitoring points are dynamically arranged. Specifically, after the first calculation step, based on the optimized dynamic monitoring point layout scheme, the three-dimensional spatial coordinates, distribution density, and corresponding monitoring area parameters of the monitoring points are updated. A three-dimensional reference table of monitoring points, rotor structure, and gradient features is generated, clarifying the rotor material layer, structural segment, gradient interval, and monitoring priority corresponding to each monitoring point. Starting from the second calculation step, the dynamic layout of the field feature monitoring points is executed according to the updated monitoring point layout scheme. Before layout, the coordinates of the monitoring points are precisely aligned with the coordinate system of the rotor's equivalent geometric model, and minor deviations are corrected through coordinate deviation calculation. The system moves the data to ensure that each monitoring point is accurately positioned within the target monitoring area. Then, it simultaneously activates the temperature data acquisition function of each monitoring point, establishing a real-time data transmission and caching link. The acquired valid temperature data is categorized and stored according to the calculation time step, and synchronously fed back to the temperature field calculation unit, providing accurate measured data for subsequent iterative updates of the temperature field in the calculation time step. Simultaneously, a real-time diagnostic mechanism for the monitoring point's operational status is established to continuously track the data acquisition success rate, transmission delay, and data stability of each monitoring point. If a monitoring point experiences acquisition failure or data anomalies, it is immediately marked and an alternative plan is activated. A backup point with similar characteristics to the original point is temporarily selected from a pre-set backup point library to ensure the stability of the dynamic layout and the continuity and completeness of temperature data acquisition.

[0053] In a preferred embodiment of the present invention, step 3 above may include:

[0054] Step 3.1: According to the dynamically arranged field feature monitoring points, obtain the temperature data of each monitoring point at the current calculation time step in real time, which specifically includes: Based on the dynamically arranged field feature monitoring points, first start the full-process monitoring point status pre-check mechanism, which includes three core verification contents: First, data transmission link verification. By sending test signals, confirm that the wired or wireless links between each monitoring point and the temperature field calculation unit are unobstructed, without packet loss or latency exceeding the standard. Second, spatial position calibration. Compare the real-time coordinates of each monitoring point with the preset target coordinates, calculate the coordinate deviation value, and ensure that the deviation is within the allowable range. If it exceeds the range, trigger a position correction instruction. Third, sensor status verification. Check the power supply stability of the monitoring points and the response sensitivity of the sensing elements, and eliminate the failed monitoring points with response latency exceeding the standard. After the pre-check passes, based on the trigger signal of the calculation time step, start the synchronous data acquisition process to ensure that all valid monitoring points complete the temperature data acquisition at the same time stamp, and the time stamp accuracy is controlled at the microsecond level to ensure the accurate matching of the data with the current calculation time step. After the acquisition is completed, perform two-level screening on the original temperature data: The first level eliminates the abnormal data that exceeds the normal operating temperature range of the rotor material. The second level eliminates the data with fluctuation values exceeding the preset stability threshold by calculating the data fluctuation values of the adjacent 3 acquisition cycles, and retains the valid temperature data. Finally, establish an association index for the valid data and the three-dimensional spatial coordinates (x, y, z) of the corresponding monitoring points in the format of monitoring point number, coordinates (x, y, z), current time step, and temperature value, and store it in the dedicated data table of the real-time database to form a structured dataset of the monitoring point coordinates corresponding to the temperature at the current time step.

[0055] Step 3.2: Based on the temperature data at the current calculation time step and combined with the spatial position coordinates of each monitoring point, construct an instantaneous envelope surface that characterizes the spatial distribution characteristics of the overall temperature field of the rotor at the current time step, which specifically includes: Retrieve the formed structured dataset. First, conduct a deep verification of data integrity: Statistically calculate the data coverage rate of the monitoring points in each rotor structure area (permanent magnet segment, magnetic isolation block area, sheath area). If the data coverage rate of a certain area is lower than the preset threshold, it is determined that there is data missing. For the monitoring points with missing data, draw a circular search range with a radius of r centered on them. The value of r is 1.5 times the average distance between adjacent monitoring points. Select the temperature data of the valid monitoring points within the range. The process is as follows: First, use the reciprocal of the distance from each valid monitoring point to the missing point as the basic weight, ensuring that the weight ratio of the monitoring points closer in distance is larger. Then, normalize all the basic weights so that the sum of all weights is 1. Finally, calculate the supplementary value through the formula, and the formula can be expressed as T_supp = (T1×w1 + T2×w2 + … + T n ×w n ), where T_supp is the supplementary temperature value of the missing point, T1 to T n are the temperature values of n valid monitoring points within the search range, and w1 to w nThe normalized weights corresponding to the valid monitoring points are: w1 + w2 + ... + w n =1; This method ensures that the supplementary data conforms to the surrounding temperature distribution pattern; After ensuring that the data completely covers all core structural areas of the rotor, the spatial range of the interpolation calculation is then confirmed: Based on the largest circumscribed cuboid of the rotor's equivalent geometric structure model, the boundary coordinates in the x, y, and z directions are set to ensure that the interpolation range completely covers the rotor entity, while reserving a very small expansion margin to avoid loss of boundary data; Next, the interpolation sub-regions are divided according to the rule of structural segmentation + material layering. The rotor is divided into the main region along the axial direction according to the permanent magnet segment, and the sub-regions are divided radially according to the material layers of the shaft, permanent magnet, and carbon fiber braided sheath, so that the monitoring points in each sub-region are relatively evenly distributed, reducing interpolation errors.

[0056] Then, a spatial interpolation method is used to construct the instantaneous envelope surface. The core process is as follows: uniformly distributed interpolation nodes are generated in each sub-region. Based on the known coordinates and temperature values ​​of the monitoring points, the temperature value of each interpolation node is calculated using an interpolation formula, which can be expressed as follows: ,in The temperature values ​​for the interpolation nodes. Let i be the temperature value of the i-th adjacent valid monitoring point. The weight of the interpolation node corresponding to the i-th monitoring point is inversely proportional to the distance from the monitoring point to the interpolation node. After completing the interpolation calculation for all sub-regions, the temperature values ​​of the boundary interpolation nodes of adjacent sub-regions are smoothed to eliminate splicing gaps. Then, the interpolation results of all sub-regions are integrated to construct a continuous and smooth instantaneous envelope surface. Each three-dimensional spatial coordinate (x, y, z) of the instantaneous envelope surface uniquely corresponds to a temperature value T, forming a global mapping relationship between coordinates and temperature, which fully characterizes the spatial distribution characteristics of the rotor's overall temperature field at the current calculation step. In this invention, the dynamic envelope surface is composed of a series of instantaneous envelope surfaces for continuous calculation steps, used to characterize the spatial evolution characteristics of the rotor's overall temperature field over time. The instantaneous envelope surface constructed for each calculation step is a static snapshot of the dynamic envelope surface at that moment, reflecting the spatial distribution of the temperature field at that time step. The dynamic envelope surface embodies its dynamic evolution characteristics through the sequence of instantaneous envelope surfaces for continuous time steps. The two are conceptually unified and are both mathematical expressions of the spatial characteristics of the temperature field.

[0057] Step 3.3 involves obtaining the instantaneous envelope surface from the previous calculation time step to calculate the surface area change between the instantaneous envelope surface of the current time step and the instantaneous envelope surface of the previous calculation time step. Specifically, this includes: first, retrieving the instantaneous envelope surface data from the previous calculation time step, and simultaneously initiating a dual data validity check: first, format verification to confirm that the storage format, coordinate dimensions, and data precision of the historical data and the current time step data are completely consistent; second, content verification to check whether the spatial range of the historical surface data is complete, without missing boundaries or data corruption, ensuring that both... The time-step data are comparable; then, a precise spatial coordinate alignment operation is performed on the two surfaces: using the global coordinate system of the rotor equivalent geometric structure model as a reference, three non-collinear feature reference points are selected, such as the center of the two end faces of the rotor and the corner point of a certain permanent magnet segment. The coordinate values ​​of the two time-step surfaces at the reference points are extracted respectively, and the coordinate deviation vector is calculated. Based on the deviation vector, the surface data of the previous calculation time step is translated and rotated to ensure that the spatial positions of the two surfaces in the global coordinate system are completely coincident, eliminating the calculation error caused by coordinate system drift.

[0058] Next, we proceed to the uniform mesh generation and subsurface decomposition stage. The core is to ensure the consistency of the surface division between the two time steps. The specific process is as follows: First, determine the unified benchmark and parameters for mesh generation. Based on the rotor axial length and maximum radial radius, set the edge length threshold of the mesh. The threshold value is determined according to the distribution density of monitoring points to ensure that each mesh contains at least two effective monitoring points, thus ensuring the accuracy of subsequent area calculations. Using the same generation rules, triangular meshes are preferred because they have a higher fitting degree to the surface profile. If the profile of a certain area of ​​the surface is regular, quadrilateral meshes can be used. This is done for the current time step and the previous calculation. The instantaneous envelope surface of the time step is meshed. During the meshing process, the vertex coordinates and boundary range of each mesh are recorded synchronously, and the meshes corresponding to the positions on the two time step surfaces are assigned the same number to form a one-to-one correspondence between mesh number and vertex coordinate. After the meshing is completed, the correspondence consistency of the sub-surfaces is checked by comparing the number of meshes on the two time step surfaces and the deviation of the vertex coordinates of the corresponding meshes. If there is a deviation, the mesh parameters are readjusted and the meshing is repeated until the boundaries and vertices of all corresponding sub-surfaces are completely matched. Finally, both surfaces are decomposed into several uniquely numbered, one-to-one corresponding triangular or quadrilateral sub-surfaces.

[0059] Next, the surface area of ​​the subsurface is calculated precisely, and the subsurfaces are processed separately in two categories: For triangular subsurfaces, the three-dimensional coordinates of its three vertices (x1, y1, z1), (x2, y2, z2), and (x3, y3, z3) are extracted first, and the lengths of the three sides are calculated using the distance formula between two points in space. The formula is as follows:

[0060]

[0061] in Let i be the side lengths of the i-th vertex and the j-th vertex, where i and j are 1, 2, and 3 respectively, and i ≠ j. Then, substitute the three side lengths into Heron's formula to calculate the area, which is: Where p is the semi-perimeter of the triangle, For a quadrilateral subsurface, it is first split into two adjacent triangular subsurfaces along one of its diagonals, prioritizing the shorter diagonal to reduce the error in calculating the area after splitting. The vertex coordinates of the two split triangles are extracted separately, and the areas of the two triangles are calculated sequentially using the triangle area calculation method described above. The two areas are then added together to obtain the total surface area of ​​the quadrilateral subsurface. After splitting, the integrity of the splicing of the two triangles needs to be verified to ensure that the vertex coordinates of the split triangles are completely consistent with the vertices of the original quadrilateral, without omissions or repetitions.

[0062] After calculating the area of ​​all corresponding subsurfaces, the surface area is summarized: First, the area of ​​all subsurfaces in the current time step is summarized according to the grid number to obtain the total surface area S1 of the instantaneous envelope surface in the current time step; the area of ​​all corresponding subsurfaces in the previous calculation time step is summarized in the same way to obtain the total surface area S0 of the previous calculation time step; during the summarization process, the number of subsurfaces in the two time steps is checked simultaneously to avoid deviations in the total surface area due to omissions or duplicate calculations; finally, the surface area change ΔS is calculated using the formula ΔS = S1 - S0; when ΔS is positive, it represents the expansion of the temperature field envelope surface in the current time step relative to the previous time step, which is essentially an overall increase in temperature in all regions of the rotor, leading to an expansion of the spatial distribution range of the temperature field; when ΔS is negative, it represents the contraction of the surface, corresponding to an overall decrease in temperature in all regions of the rotor, leading to a reduction in the spatial distribution range of the temperature field; the absolute value of ΔS directly reflects the magnitude of the surface area change, and the larger the absolute value, the more obvious the change in the spatial shape of the temperature field between the two time steps.

[0063] Step 3.4: Based on the ratio of the surface area change to the surface area of ​​the instantaneous envelope surface in the previous calculation step, calculate the surface area change rate of the envelope surface between adjacent calculation steps. Specifically, this includes: first, extracting the calculated surface area change ΔS and the total surface area S0 of the previous calculation step; then initiating a secondary validity check of the surface area of ​​the previous step: first, checking whether S0 is within a reasonable value range, which is determined based on the surface area design value of the rotor equivalent geometric structure model. If S0 exceeds ±10% of the design value, it is considered abnormal data and historical data needs to be retrieved and verified again; second, ensuring that S0 is not zero to avoid division by... The calculation of zero was incorrect; after confirming the validity of S0, the calculation of the rate of change of the surface area of ​​the envelope surface at adjacent time steps was carried out: using the absolute value of ΔS as the numerator, focusing on the magnitude of change, ignoring the difference in the direction of expansion / contraction, and using S0 as the denominator, the ratio was calculated to obtain the preliminary rate of change R0=|ΔS| / S0; since ΔS may be abnormally large under extreme conditions, R0 needs to be standardized: a reasonable upper limit threshold R for the rate of change was set. max The reasonable upper limit threshold R max Based on extensive experimental data, it was determined that this represents the extreme degree of drastic change in the temperature field; if R0 > R max Then R0 will be modified to R max If R0≤R max The original calculated values ​​are retained. After standardization, the final rate of change R of the envelope surface area between adjacent calculation time steps is obtained. This rate of change directly reflects the degree of change in the spatial distribution of the temperature field between adjacent time steps: the larger the R value, the more obvious the change in the spatial morphology of the temperature field and the more drastic the change in the non-uniformity of the temperature distribution; the smaller the R value, the more stable the spatial distribution of the temperature field. After the calculation is completed, R is associated with the corresponding time step number, S0, and ΔS and stored to provide data support for the mapping of the distortion correction factor.

[0064] Step 3.5 maps the obtained rate of change of the envelope surface area between adjacent calculation time steps to a temperature field distortion correction factor. Specifically, this involves: first, retrieving the previously constructed correlation system between the rate of change of the envelope surface area and the temperature field distortion correction factor. The establishment process of this system is as follows: designing multiple sets of motor operating conditions with different speeds and loads, synchronously collecting the rate of change of the envelope surface area and the actual degree of temperature field distortion under each condition, quantifying the deviation between the measured temperature and the ideal uniform temperature field, and based on the collected massive amounts of data, using a data fitting method to establish the mapping relationship between the two, ultimately forming a system containing the rate of change interval, ... A correlation table of correction factor benchmark values ​​and deviation adjustment coefficients is generated. Then, the mapping process is initiated: first, the calculated final rate of change R is compared one by one with the rate of change intervals in the correlation table to determine the interval to which R belongs, such as [0, 0.05) as a stable interval, [0.05, 0.2) as a mildly changing interval, and ≥0.2 as a drasticly changing interval; based on the interval, the corresponding correction factor benchmark value k0 is extracted; to improve mapping accuracy, k0 needs to be fine-tuned based on the actual characteristics of the current temperature field: retrieve the monitoring point temperature data from step 3.1 and calculate the maximum temperature gradient G of the current temperature field. max If G max Greater than the material's critical heat resistance gradient G n If G is positive, then k0 will be increased by a preset ratio to enhance the correction strength; if G is negative... max Less than G n If the value is 50%, then k0 will be adjusted downwards proportionally to reduce the correction force. The fine-tuning formula can be expressed as k = k0 × (1 + α × (G)). max -G n ) / G n ), where k is the final correction factor, α is the gradient influence coefficient, determined by experimental data, and its value ranges from 0.1 to 0.3, G n This represents the critical temperature gradient for heat resistance of the rotor core material (permanent magnet).

[0065] After fine-tuning, the final correction factor k is validated for rationality: check whether k is within the preset effective range (0.8, 1.5), and compare it with the correction factor values ​​under the same historical conditions to ensure that k meets the actual temperature field distortion correction requirements; if the validation passes, k is determined as the temperature field distortion correction factor for the current time step; if it fails, the correlation table is retrieved again, and more historical data is used for secondary fine-tuning until a correction factor that accurately adapts to the current temperature field change state is obtained. This factor will be used for parameter correction of the subsequent temperature field calculation model to improve the accuracy of temperature field calculation.

[0066] In a preferred embodiment of the present invention, step 4 above may include:

[0067] Step 4.1 involves coupling the temperature field distortion correction factor with the initial non-uniform temperature field to perform real-time correction of the initial temperature field distribution, thereby obtaining the accurate non-uniform temperature field at the current time step. This includes: retrieving the obtained temperature field distortion correction factor and the initial non-uniform temperature field data; initiating a basic data consistency verification process: firstly, confirming that the calculation time step stamps of the two types of data are completely matched to avoid cross-time step data confusion; secondly, unifying the spatial coordinates of the two types of data to the global coordinate system of the rotor's equivalent geometric structure model, eliminating coordinate deviations through feature point coordinate comparison, and ensuring accurate alignment of the basic data for the coupled calculation; subsequently, initiating a partitioned coupled calculation process, first dividing the coupled units according to the rotor's structural segments and material layers, so that each unit corresponds to a region with a single material and a single temperature gradient trend; then, assigning weights to the distortion correction factor according to the units. First, higher weights are assigned to high-gradient regions to ensure that the correction more closely matches the actual situation of regions with drastic temperature field changes. Then, the correction factors of each unit are coupled with the temperature data of the corresponding region of the initial temperature field. The slope of the temperature gradient and the magnitude of the temperature extrema in the corresponding region are adjusted by the correction factors to weaken the calculation deviation of the initial temperature field. After the coupling calculation is completed, the temperature data of the instantaneous envelope surface of the current time step is retrieved, and key monitoring points of each coupled unit, such as gradient extrema points and component interface points, are selected. The temperature values ​​of the corrected temperature field and the instantaneous envelope surface at these points are compared. If the deviation exceeds the preset allowable range, the weight allocation of the correction factors of the corresponding units is readjusted, and the coupling calculation and deviation verification process is repeated until the temperature deviation of all key monitoring points meets the requirements. Finally, an accurate non-uniform temperature field that can accurately reflect the actual temperature distribution of the current time step is obtained.

[0068] Step 4.2: Based on the precise non-uniform temperature field at the current time step, determine the real-time temperature distribution of each component, including the permanent magnet, the magnetic shielding block, and the carbon fiber sheath. Specifically, based on the obtained precise non-uniform temperature field at the current time step, first extract the three-dimensional spatial boundary coordinates of the permanent magnet, the magnetic shielding block, and the carbon fiber braided sheath from the rotor's equivalent geometric model. Define the axial start and end ranges, radial inner and outer boundaries, and circumferential distribution range of each component. Based on this, construct a unique binary region mask for each component: coordinates marked as 1 in the mask represent points belonging to that component, and coordinates marked as 0 represent points not belonging to that component, ensuring accurate and non-overlapping spatial division of each component. Then, initiate the component temperature data extraction process, matching the global coordinates-temperature data of the precise non-uniform temperature field with the region masks of each component point by point. The temperature data corresponding to the coordinate points marked with a mask of 1 are filtered out and stored according to the format of component type, coordinates, and temperature. During the extraction process, abnormal data is removed simultaneously. The specific judgment criteria are: if the temperature value of a coordinate point deviates significantly from the temperature trend of the surrounding coordinate points of the same component, or exceeds the normal operating temperature range of the component material, it is judged as abnormal data and removed. At the same time, the weighted average of the surrounding valid data is used to fill the gaps. Finally, the extracted temperature data of each component is spatially distributed and organized. A data index is established according to the rules of axial segmentation and radial layering. The highest temperature, lowest temperature, and average temperature of each segment and layer are marked, clearly showing the spatial variation law of the internal temperature of each component along the axial and radial directions. Finally, the real-time temperature distribution corresponding to the permanent magnet, the magnetic shielding block, and the carbon fiber woven sheath are formed respectively.

[0069] Step 4.3: Based on the determined real-time temperature distribution of each component (permanent magnet, magnetic shielding block, and carbon fiber sheath), and combined with the pre-stored nonlinear mapping relationship between material property parameters and temperature, determine the real-time elastic modulus and real-time Poisson's ratio of each component at the current temperature. Specifically, this includes: first, retrieving the pre-stored nonlinear mapping relationship between material property parameters and temperature for each component from the material property database. This mapping relationship is constructed based on high-temperature test data of multiple batches of the same type of material and stored in a segmented table format. The table contains characteristic temperature nodes for different temperature ranges, as well as the standard values ​​of elastic modulus and Poisson's ratio corresponding to each node, and also marks the parameter change trend within each range; then, extracting the determined real-time temperature distribution of each component, and organizing the real-time temperature values ​​of each region according to the axial segmentation and radial layering of the component, clarifying the temperature range of each region; for each region of each component, initiating the parameter matching process: first, the real-time temperature distribution of the region is... The temperature value is compared with the corresponding nonlinear mapping table of the material to locate the temperature range to which it belongs. If the real-time temperature is exactly equal to the characteristic temperature node in the table, the elastic modulus and Poisson's ratio corresponding to that node are directly extracted as real-time parameters. If the real-time temperature is between two characteristic temperature nodes, linear interpolation is used to determine the accurate real-time elastic modulus and real-time Poisson's ratio. During the interpolation process, the parameter change trend of the temperature range is fully considered to ensure that the interpolation result conforms to the nonlinear change law of the material properties. After the parameter matching of all regions is completed, the consistency of the real-time elastic modulus and Poisson's ratio of each component is checked. It is checked whether the parameter change of different regions of the same component is continuous and whether it matches the change trend of the temperature distribution. If there are discontinuous abnormal parameters, the matching process of temperature data and mapping relationship is rechecked. After correcting the deviation, the real-time elastic modulus and real-time Poisson's ratio of each component under the current temperature state are finally determined.

[0070] Step 4.4: Calculate the relative change between the real-time elastic modulus of each component at the current temperature and the elastic modulus at the initial room temperature. Define this relative change as the nonlinear fluctuation value of the material's elastic parameters. Specifically, this includes: first, retrieving the standard value of the elastic modulus of each component at the initial room temperature. During retrieval, strictly verify the matching conditions of the standard value to ensure complete consistency with the material batch and testing standards corresponding to the real-time elastic modulus in Step 4.3, and that the ambient temperature of the initial room temperature is uniform, typically 25°C (standard room temperature), to avoid calculation deviations due to mismatched basic data. Then, initiate the relative change calculation process. For each region of each component, first calculate the difference between the real-time elastic modulus at the current temperature and the initial room temperature elastic modulus of that region, and then compare this difference with the initial room temperature elastic modulus. The relative change in elastic modulus of the region is obtained by calculating the ratio of the quantities, retaining the positive and negative signs of the change, where a positive value represents an increase in elastic modulus and a negative value represents a decrease in elastic modulus. After the calculation, the validity of the relative change in each region is judged: combined with the real-time temperature value of the corresponding region and referring to the basic law of material thermal deformation, if the magnitude of the relative change does not match the temperature change range, or exceeds the range of elastic modulus change of the same type of material under the same temperature change, it is judged as an abnormal change. The values ​​and calculation process of the real-time elastic modulus and the initial room temperature elastic modulus are rechecked, and the abnormal data is corrected. Finally, the verified relative change is formally defined as the nonlinear fluctuation value of the material elastic parameter, and stored in association with the format of component type, region location, real-time temperature, and nonlinear fluctuation value.

[0071] In a preferred embodiment of the present invention, step 5 above may include:

[0072] Step 5.1: Based on the precise non-uniform temperature field and its corresponding nonlinear fluctuation values ​​of material elastic parameters, update the material constitutive relations of each component in the rotor equivalent geometric structure model to obtain the updated material constitutive relation parameters. Specifically, this includes: retrieving the precise non-uniform temperature field global data and the nonlinear fluctuation values ​​of material elastic parameters; simultaneously extracting the original material constitutive relation parameters of each component from the parameter library of the rotor equivalent geometric structure model, including core mechanical parameters such as elastic modulus, Poisson's ratio, and coefficient of thermal expansion; and initiating the three-dimensional data correlation verification process. By establishing a mapping table of component regions, temperature values, and nonlinear fluctuation values, it is ensured that different axial segments and radial layered regions of each component can accurately match the corresponding temperature data and fluctuation values, and that the material grade and test standards of the original constitutive relation parameters are completely consistent with the current component, avoiding cross-regional data confusion or material property mismatch.

[0073] Subsequently, targeted updates to the constitutive relation parameters were carried out. For each sub-region of each component, the original elastic modulus and Poisson's ratio were used as a benchmark, and the parameters were corrected in conjunction with the corresponding nonlinear fluctuation values. If the fluctuation value was positive, it indicated that the material's elastic modulus had increased at the current temperature, and the benchmark parameters were adjusted upwards proportionally to the fluctuation value. If the value was negative, the parameters were adjusted downwards accordingly. During the correction process, the temperature data of the current region was simultaneously incorporated to ensure that the parameter adjustment range matched the temperature change trend and truly reflected the nonlinear influence of temperature on the material's mechanical properties. After the initial update was completed, a two-dimensional verification was initiated: on the one hand, it was checked whether the parameter changes in different regions within the same component were continuous and smooth, without abrupt changes; on the other hand, combined with the fundamental mechanical properties of the material, it was determined whether the corrected parameters conformed to the mechanical performance laws of this type of material in the corresponding temperature range. If there were parameter anomalies or mismatches, the entire process of fluctuation value calculation and temperature data matching was re-tracked, and after correcting the deviations, the updated material constitutive relation parameters were finally formed. These parameters were then updated in batches to the parameter library of the rotor equivalent geometric structure model according to the index format of component, region, temperature, and constitutive parameters, achieving accurate matching between the model's material properties and the current temperature state.

[0074] Step 5.2: Based on the real-time acquired current operating speed, calculate the centrifugal load acting on the rotor equivalent geometric model. Simultaneously, determine the assembly interference through assembly parameters. Specifically, this includes: first, acquiring the rotor's current operating speed in real time; performing time-series filtering on the collected speed data to remove peak anomalies caused by instantaneous impacts; selecting the average speed over 10 consecutive sampling periods as the current effective operating speed to ensure stable and reliable speed data; based on this effective speed, combined with the mass distribution characteristics of each component in the rotor equivalent geometric model, extracting the three-dimensional mass unit distribution data of each component from the model, clarifying the mass concentration location and rotation radius in different regions, and calculating the centrifugal load generated by high-speed rotation of each component. During the calculation, it is important to distinguish the differences in rotation radius between different axial segments and different radial levels to ensure the accuracy of the centrifugal load in spatial distribution.

[0075] Simultaneously, temperature correction of the assembly interference was carried out. The design values ​​of the interference between the permanent magnet and the shaft, the permanent magnet and the carbon fiber braided sheath, and the magnetic shielding block and the permanent magnet at room temperature were retrieved from the rotor assembly technical file. Combined with accurate non-uniform temperature field data, the influence of temperature changes on the thermal expansion of the dimensions of each component was analyzed. The dimensional expansion and contraction trend of each component at the current temperature was judged by the thermal expansion characteristics of the materials, and the design value of the interference at room temperature was dynamically corrected. If the component expands due to the increase in temperature, the interference correction value is appropriately reduced; if it contracts, it is increased accordingly. Finally, the actual effective assembly interference of each mating interface under the current temperature condition was obtained. Finally, the centrifugal load and interference were checked separately. The centrifugal load must conform to the basic law that the square of the rotational speed is positively correlated with the load, and the interference must be within the allowable elastic deformation range of the material to ensure that both data meet the accuracy requirements of subsequent structural analysis.

[0076] Step 5.3: In the rotor equivalent geometric model, for the mating interfaces between the permanent magnet, the magnetic shielding block, and the carbon fiber sheath, define contact pairs and set nonlinear contact criteria based on contact pressure and gap. Specifically, this includes: comprehensively reviewing the mating interface types of each component in the rotor equivalent geometric model, confirming that the core mating interfaces are the mating interface between the permanent magnet and the magnetic shielding block, the interference fit interface between the permanent magnet and the carbon fiber braided sheath, and the gap interface between the magnetic shielding block and the sheath, and defining contact pairs for each interface one by one; the selection of the master and slave surfaces of the contact pairs follows the principle of stiffness priority, with the surface of the component with greater stiffness as the master surface, such as the surface of the carbon fiber braided sheath as the master surface and the surface of the permanent magnet as the slave surface, to avoid difficulties in contact calculation convergence due to improper selection of master and slave surfaces; at the same time, confirm the effective range of the contact pairs to ensure complete coverage of the entire axial length and circumferential range of the interface, with no omissions in the contact definition; then configure the basic properties of the contact pairs, including selecting a suitable detection method for flexible contact, such as the penalty function method, setting reasonable contact stiffness coefficient and friction coefficient, and determining them based on the conventional value range of material friction tests to ensure accurate simulation of the contact state.

[0077] Based on this, a nonlinear contact criterion is formulated, specifically including three core logics: When the interface gap is negative, i.e., interference contact, the relationship between contact pressure and interference is confirmed to be nonlinearly increasing, while limiting the maximum contact pressure to not exceed the material's contact fatigue limit; When the interface gap is positive, i.e., a small gap exists, a gap threshold is set. If the gap is less than the threshold, it is judged as potential contact, retaining the possibility of contact under subsequent loads; if it is greater than the threshold, it is judged as no contact, and no contact force is transmitted; When the interface shows a relative sliding trend, the nonlinear law of friction force changing with normal pressure is clarified to avoid misjudgment of sliding state; After the criterion is formulated, it is associated and bound with the corresponding contact pair, and the rationality of the criterion is verified to ensure that the contact state judgment logic matches the actual assembly conditions and material properties.

[0078] Step 5.4 uses the updated material constitutive parameters, centrifugal load, assembly interference, and nonlinear contact criterion as coupled boundary conditions to solve the rotor equivalent geometric model, outputting a multi-field coupled stress field containing stress and strain distributions. Specifically, this includes: first, integrating all coupled boundary conditions, the updated material constitutive parameters, centrifugal load, and corrected assembly interference and nonlinear contact criterion, and initiating multi-dimensional compatibility verification; focusing on checking three core logics: first, whether the direction of the applied centrifugal load is consistent with the rotor rotation direction, and whether there is a conflict with the contact constraint direction; second, whether the magnitude of the assembly interference is compatible with the stiffness setting of the contact pair, avoiding calculation divergence due to excessive interference; and third, whether the temperature correlation of the material constitutive parameters is completely matched with the temperature field data, ensuring the synergy between mechanical properties and temperature state. If conflicts or incompatibilities are found, the corresponding steps are promptly backtracked to correct the data.

[0079] Subsequently, following the sequence of attribute update, load application, and constraint binding, boundary conditions are applied one by one to the rotor equivalent geometric model to synchronously replace the constitutive relation parameters of each component's subdivided region. A partitioned loading method is used to precisely apply centrifugal loads to the mass concentration areas of each component according to the calculation results. Assembly interference is applied to the corresponding mating interfaces through displacement constraints. The nonlinear contact criterion is activated and associated with each contact pair. After the boundary conditions are applied, a step-by-step iterative solution process is initiated. The first step solves for the thermal stress distribution under the coupling of the temperature field and material constitutive model to obtain the basic stress field. The second step superimposes the centrifugal load to solve for the coupled stress of centrifugal force and thermal stress. The third step, based on the nonlinear contact criterion, iteratively corrects the contact pressure and stress distribution of each mating interface until the calculation results converge. The convergence criterion is that the stress change in adjacent iteration steps is less than a preset allowable value.

[0080] After the solution is completed, the output includes complete multi-field coupled stress field data containing the three-dimensional spatial stress distribution of each rotor component, such as normal stress and shear stress, and strain distribution, such as linear strain and shear strain. Simultaneously, the validity of the results is verified. The model is compared to the expected locations of stress concentration areas, such as interface edges and structural abrupt changes, to ensure they match the theoretical analysis. The maximum stress value is checked to ensure it is within the allowable stress range of the material. Trend comparisons are performed using stress field data from similar historical operating conditions to ensure the accuracy and reliability of the output results.

[0081] In a preferred embodiment of the present invention, step 6 above may include:

[0082] Step 6.1: Extract the normal and tangential contact stresses at the interfaces between adjacent permanent magnet segments from the multi-field coupled stress field. Specifically, this includes: retrieving the complete parameters of the rotor equivalent geometric model from the output multi-field coupled stress field global data; accurately locating the three-dimensional spatial coordinate range of the interfaces between all adjacent permanent magnet segments; clarifying the axial start and end coordinates, circumferential full-angle distribution range, and radial coverage depth from the inside to the outside of each interface; organizing this coordinate information into an index table of interface numbers and spatial coordinate ranges as precise screening conditions for stress extraction; subsequently, initiating a regional stress extraction process; using the spatial coordinate range of each interface as the screening basis, extracting stress data for all discrete coordinate points within the corresponding interface from the multi-field coupled stress field; simultaneously establishing stress direction determination rules; using the tangential direction of the interface as a reference; and... Stress perpendicular to the interface tangent is defined as normal contact stress, and stress parallel to the interface tangent is defined as tangential contact stress, thus completing the initial classification and labeling of the two types of stress. Next, a dual-stage validity screening of the stress data is conducted. The first screening removes abnormal discrete data exceeding the allowable contact stress range of the corresponding permanent magnet material. The second screening analyzes the stress change trends of adjacent coordinate points, removing abrupt data that disrupts the continuous stress distribution, retaining continuous and smooth effective stress values. Finally, the screened effective stress data is grouped and integrated according to the interface number, and the distribution characteristic values ​​of normal and tangential contact stress within each interface are calculated, including maximum, minimum, and average values, forming a structured dataset of interface number, normal contact stress distribution, and tangential contact stress distribution, ensuring that the extracted stress data is accurately correlated with each target interface.

[0083] Step 6.2 involves inputting the extracted normal and tangential contact stresses of each interface into the pre-built dynamic correlation model. Specifically, this includes determining the source of the core architecture of the pre-built dynamic correlation model. The dynamic correlation model is optimized based on an improved BP neural network architecture. To address the problem of slow convergence and easy getting trapped in local optima in multi-factor coupled calculations of traditional BP neural networks, the activation function of the hidden layer and the weight iteration strategy have been optimized. A spatial-temporal correlation verification module with multiple input parameters has been added to adapt to the nonlinear mapping requirements of stress, rotational speed, temperature gradient, and axial strain compensation coefficient in this invention.

[0084] The specific construction process is as follows: First, the network topology is designed. The input layer has 6 nodes, corresponding to the maximum normal contact stress, average normal contact stress, maximum tangential contact stress, average tangential contact stress, current operating speed, and axial temperature gradient at the interface, covering the core factors affecting axial strain. Two hidden layers are set, with the number of nodes in each layer determined through trial and error to ensure a balance between model fitting and generalization capabilities. The output layer has 1 node, corresponding to the rotor's real-time axial strain compensation coefficient. Next, the core network parameters are configured. The activation function of the hidden layer is replaced with an improved Sigmoid function to improve calculation accuracy under multi-factor coupling. An adaptive momentum gradient descent algorithm is selected as the weight iterative optimization algorithm, with a reasonable learning rate and iteration termination condition set: the iteration error is less than a preset threshold or the number of iterations reaches the upper limit. Finally, a spatial-temporal correlation module is embedded. This module establishes spatial location correlations for the input parameters, ensuring that the stress parameters match and are correlated with the corresponding interface's temperature gradient parameters, and ensuring that the speed and stress data correspond to the same calculation time step, avoiding data mismatches across interfaces and time steps.

[0085] The model training process is conducted in conjunction with the actual operating scenarios of the rotor: The first step involves constructing a training dataset, designing multiple typical operating conditions covering three speed levels (low, medium, and high) and three temperature gradient scenarios (low, normal, and high). Real-time rotor data is collected experimentally under each condition, including the normal and tangential contact stresses at the interfaces of adjacent permanent magnets, the current operating speed, the axial temperature gradient at the interface, and the actual axial strain compensation coefficient measured by a high-precision strain sensor. This data is organized into a training dataset in the format of input parameter set - actual output value, and divided into training and validation sets according to a preset ratio. The second step involves data preprocessing. The input parameters in the training set are standardized to the same numerical range to eliminate the impact of differences in parameter magnitudes on the training effect. For any missing data, interpolation from adjacent operating conditions is used to supplement the missing data. The third step is to start model training. The preprocessed training set is input into the model, and the network weights and thresholds are iteratively updated using the backpropagation algorithm. Every 100 iterations, the model's prediction error is evaluated using the validation set. If the prediction error increases continuously for multiple iterations, an early stopping mechanism is triggered to avoid overfitting. The fourth step is model optimization and calibration. For the working conditions with large errors in the validation set, such as high-speed and high-temperature extreme working conditions, the corresponding experimental data is supplemented and retrained. The number of hidden layer nodes and the learning rate are adjusted until the prediction error of the model under all typical working conditions is less than the preset allowable range. Finally, the construction and training of the dynamic association model are completed.

[0086] After the model is built and trained, a readiness check of the dynamic association model is initiated first to confirm that the core parameters of the model have been fully loaded and that all calculation modules are in normal operating condition. At the same time, the data format requirements of the model input interface are verified to ensure compatibility with the format of the data to be input. Then, the extracted structured stress dataset is preprocessed, and the normal and tangential contact stress characteristic values ​​of each interface are standardized and converted to the preset input range of the model. Simultaneously, the effective data of the current operating speed, the stable speed value after time-series filtering, and the axial gradient values ​​of the corresponding positions of each adjacent permanent magnet interface in the precise non-uniform temperature field are retrieved and organized into an interface parameter set that matches the stress data. Finally, the preprocessed stress characteristic values, the current operating speed, and the temperature axial gradient values ​​of the corresponding interfaces are organized into structured input data according to the order of the model input layer nodes and completely transmitted to the dynamic association model through the model input interface. During the transmission process, data verification is initiated to ensure that the input data is complete and without mismatch, and that the spatial position and time sequence of each parameter are completely consistent.

[0087] Step 6.3: Using a pre-built dynamic correlation model, based on the input interface normal and tangential contact stresses, the current operating speed, and the axial gradient characteristics of the precise non-uniform temperature field, the real-time axial strain compensation coefficient of the rotor is calculated. Specifically, after receiving the input data, the dynamic correlation model first initiates the built-in multi-parameter correlation verification process. Through the spatial-temporal correlation verification module, it checks one by one whether the normal and tangential contact stresses and the corresponding interface temperature axial gradient values ​​in each set of input data match the same interface position, and whether all input parameters correspond to the operating speed of the current calculation time step. If data mismatch or cross-time step problems are found, feedback is immediately provided and the calculation is terminated until the data is corrected and re-entered.

[0088] After successful verification, the multi-factor coupling calculation process is initiated: First, the standardized parameters are input into the first hidden layer via the input layer. Feature extraction and preliminary processing are performed on the input parameters to extract the basic correlation features between each parameter and the axial strain compensation coefficient, such as the basic influence trend of stress magnitude on axial strain compensation and the effect of rotational speed on centrifugal strain. Second, the preliminarily extracted features are input into the second hidden layer to further analyze the synergistic coupling effect of multiple factors, such as the superposition effect of stress and temperature gradient on axial strain under high-speed scenarios. Third, the coupling analysis results are integrated and transformed through the output layer to obtain the preliminary real-time rotor axial strain compensation coefficient. During the calculation process, based on the operating conditions learned during the training phase, the weight ratio of each input parameter is dynamically adjusted. For example, under high-speed conditions, the weight of the rotational speed parameter is increased to match its dominant influence on axial strain; under high-temperature gradient conditions, the weight of the temperature axial gradient parameter is increased to adapt to the significant effect of temperature deformation, ensuring that the weight allocation is compatible with the actual influence of each parameter on axial strain under the current operating conditions.

[0089] After the calculation is completed, the preliminary axial strain compensation coefficient is output, and then the coefficient rationality verification process is initiated: First, historical test data under the corresponding working condition is retrieved and compared with the axial strain compensation coefficient under similar historical working conditions to determine whether the current output coefficient's trend is consistent; Second, the theoretical reasonable range of the axial strain compensation coefficient under the current working condition is calculated by combining the elastic properties of the rotor material and the structural design parameters, and the preliminary output coefficient is checked to see if it is within this range; If the preliminary coefficient exceeds the reasonable range or does not conform to the historical trend, the model will automatically backtrack the coupling calculation process, adjust the feature extraction weights of each hidden layer, and recalculate the corrected compensation coefficient; If the preliminary coefficient meets the verification requirements, it is directly used as the candidate coefficient; Finally, the candidate coefficient is combined with the axial strain data in the output multi-field coupled stress field to verify whether the axial strain distribution after the compensation coefficient correction is more consistent with the actual working state of the rotor; After the final verification is completed, the accurate real-time axial strain compensation coefficient of the rotor is determined.

[0090] In a preferred embodiment of the present invention, step 7 above may include:

[0091] Step 7.1: Based on the real-time axial strain compensation coefficient, the rotor axial stress components extracted from the multi-field coupled stress field are corrected to obtain the corrected axial stress distribution. Specifically, this includes: retrieving the real-time axial strain compensation coefficient and the global data of the multi-field coupled stress field, initiating a data consistency deep verification to ensure that the calculation time steps of the two types of data are completely matched, and that the spatial coordinates are all unified to the global coordinate system of the rotor equivalent geometric structure model, avoiding correction deviations caused by cross-time steps or coordinate mismatches; subsequently, the rotor axial stress components are accurately extracted from the multi-field coupled stress field, with the extraction range covering all core components of the rotor, including each segment of the permanent magnet, the magnetic shielding block, and the carbon fiber braided sheath, segmented axially. The radially layered rules are organized into structured axial stress data to confirm the axial stress distribution characteristics of each region. Based on the real-time axial strain compensation coefficient, a region-by-region correction is carried out. The axial stress value of the corresponding region is adjusted according to the compensation coefficient. The correction logic is to weaken or strengthen the distribution amplitude of axial stress through the compensation coefficient, so that the corrected axial stress is more in line with the actual axial strain state of the rotor. After the correction is completed, the stress rationality verification is initiated. Combining the elastic characteristics of the rotor material and the mechanical parameters at the current temperature, it is determined whether the corrected axial stress is within a reasonable range. If there is an abnormal deviation, the matching process between the compensation coefficient and the axial stress is traced back. Finally, a complete corrected axial stress distribution is formed.

[0092] Step 7.2 involves simultaneously extracting the rotor radial and tangential stress distributions corresponding to the corrected axial stress distribution from the multi-field coupled stress field. Specifically, this includes: using the obtained corrected axial stress distribution as a benchmark, first determining the rotor spatial range and partitioning method it covers to ensure consistency between the subsequently extracted radial and tangential stress distributions; then, from the full-domain data of the multi-field coupled stress field, simultaneously extracting the radial and tangential stress components within the corresponding regions according to the same spatial filtering conditions. During the extraction process, strictly associating the spatial indexes of each coordinate point ensures that the radial and tangential stresses at each coordinate point can accurately match the corrected axial stress; performing validity filtering on the extracted radial and tangential stress data, removing abnormal discrete data exceeding the allowable stress range of the corresponding material, and abrupt data that disrupts the continuous stress distribution pattern, retaining continuous and smooth effective stress values; then, according to the partitioning rules of the corrected axial stress distribution, grouping and organizing the radial and tangential stress data to establish an axial segmentation, radial layering, and stress value indexing system consistent with the axial stress, ensuring a clear spatial correlation between the three types of stress distributions.

[0093] Step 7.3 involves synthesizing the corrected axial, radial, and tangential stress distributions to determine the maximum combined stress and its spatial location under operating conditions. This includes: constructing a unified spatial index framework for the three stress distributions; associating the corrected axial, radial, and tangential stress distributions point-by-point according to three-dimensional spatial coordinates to ensure accurate correspondence of the three stress components at the same spatial coordinate point and avoid stress mismatch across coordinate points; and integrating the axial, radial, and tangential stress data at corresponding coordinate points based on the core logic of stress synthesis to complete the stress synthesis calculation. During the synthesis process, the influence of stress direction on the synthesis result is carefully considered to ensure the synthesis logic is consistent. The actual stress state of the rotor is determined. After the stress synthesis is completed, the combined stress values ​​of all spatial coordinate points are traversed, and the combined stress with the largest value is selected. At the same time, the three-dimensional spatial coordinates corresponding to the maximum combined stress are recorded to confirm the rotor component (such as a certain segment of the permanent magnet, a certain area of ​​the sheath) and its specific location (axial segment, radial layer). Finally, the rationality of the maximum combined stress and its location is verified. It is checked whether the location of the maximum combined stress is a theoretical stress concentration area, such as the interface between adjacent permanent magnets, the interface between the sheath and the permanent magnet, etc. If the location deviates from the reasonable range, the stress synthesis process is re-verified. After correction, the maximum combined stress of the rotor under the current operating conditions and its precise spatial location are finally determined.

[0094] Step 7.4: Based on the maximum combined stress and combined with the allowable stresses of the permanent magnet and the sheath material, complete the strength verification of the permanent magnet rotor under the current operating conditions. Specifically, this includes: retrieving the allowable stress data of the permanent magnet and the carbon fiber woven sheath from the material property database, strictly matching the material grade, batch, and allowable stress value corresponding to the current operating temperature, as temperature significantly affects the mechanical load-bearing capacity of the material; ensuring that the allowable stress data is completely compatible with the current operating conditions; subsequently, comparing the determined maximum combined stress with the allowable stresses of the permanent magnet and the carbon fiber woven sheath, respectively. The process involves determining whether the maximum combined stress is less than the allowable stress of the corresponding material, calculating the difference between the maximum combined stress and the allowable stress, and assessing the stress redundancy. If the maximum combined stress is less than the allowable stress of the corresponding material, and the stress redundancy meets the preset safety requirements, the permanent magnet rotor is deemed to have qualified strength under the current operating conditions. If the maximum combined stress is close to or exceeds the allowable stress, or the stress redundancy is insufficient, the strength is deemed to be unqualified. The cause of the overstress is analyzed, and the spatial location of the maximum combined stress is considered to determine whether it is due to local structural design defects or unreasonable operating parameters. Finally, a complete strength verification result is output, clearly indicating whether it is qualified or not, the maximum combined stress value, the allowable stress of the corresponding material, and the stress redundancy.

[0095] like Figure 2 As shown, embodiments of the present invention also provide a high-speed motor permanent magnet rotor strength analytical calculation system, including:

[0096] The temperature field acquisition module is used to acquire the initial non-uniform temperature field with specific gradient characteristics formed axially by the rotor of a high-speed motor under operating conditions.

[0097] The monitoring point layout module is used to dynamically arrange field feature monitoring points at key parts of the rotor according to the gradient characteristics of the initial non-uniform temperature field; the key parts include at least the axial ends and middle sections of each segment of permanent magnet, the interface area between the permanent magnet and the carbon fiber sheath, and the interface transition area between adjacent permanent magnet segments.

[0098] The construction and calculation module is used to acquire temperature data of the field feature monitoring points in real time. Based on the acquired temperature data, a dynamic envelope surface is constructed to characterize the spatial evolution of the overall temperature field of the rotor. The surface area change rate of the dynamic envelope surface between adjacent calculation time steps is calculated to generate a temperature field distortion correction factor.

[0099] The correction and determination module is used to correct the initial non-uniform temperature field in real time through the temperature field distortion correction factor to obtain the accurate non-uniform temperature field, and at the same time determine the nonlinear fluctuation of the material elastic parameters caused by the accurate non-uniform temperature field.

[0100] The stress field solving module is used to solve the multi-field coupled stress field of the rotor based on the accurate non-uniform temperature field and the nonlinear fluctuation of the elastic parameters of the material, while applying the centrifugal load determined by the rotational speed and the assembly interference, and considering the nonlinearity of the interface contact.

[0101] The final processing and verification module is used to extract the contact stress state at the interface of the segmented permanent magnet in the multi-field coupled stress field, calculate the axial strain compensation coefficient through a pre-built dynamic correlation model, correct the axial stress according to the axial strain compensation coefficient, and complete the strength verification of the permanent magnet rotor by combining radial and tangential stresses.

[0102] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for analytical calculation of the strength of a permanent magnet rotor in a high-speed motor, characterized in that, The method includes: To obtain the initial non-uniform temperature field with gradient characteristics formed in the axial direction of a high-speed motor rotor under operating conditions, the following steps are taken: determining the structural composition of the high-speed motor rotor, i.e., the high-speed motor rotor is assembled by a permanent magnet, a magnetic shielding block, and a carbon fiber sheath through an interference fit; constructing an equivalent geometric structure model of the rotor considering material anisotropy based on the actual assembly relationship between the permanent magnet, the magnetic shielding block, and the carbon fiber sheath; calculating the electromagnetic loss distribution in the permanent magnet and the carbon fiber sheath based on the equivalent geometric structure model of the rotor and combining it with the electromagnetic parameters at the current operating speed to generate a dynamic electromagnetic heat source; and using the dynamic electromagnetic heat source as input, analytically calculating the initial non-uniform temperature field with gradient characteristics formed in the axial direction of the high-speed motor rotor by combining it with the radial thermal conductivity of the carbon fiber sheath. Based on the gradient characteristics of the initial non-uniform temperature field, field characteristic monitoring points are dynamically arranged at key parts of the rotor; the key parts include at least the axial ends and middle sections of each segment of permanent magnet, the interface area between the permanent magnet and the carbon fiber sheath, and the interface transition area between adjacent permanent magnet segments. The temperature data of the field feature monitoring points are acquired in real time. Based on the acquired temperature data, a dynamic envelope surface is constructed to characterize the spatial evolution of the overall temperature field of the rotor. The surface area change rate of the dynamic envelope surface between adjacent calculation time steps is calculated to generate a temperature field distortion correction factor. The initial non-uniform temperature field is corrected in real time by temperature field distortion correction factor to obtain accurate non-uniform temperature field, and at the same time, the nonlinear fluctuation of material elastic parameters caused by accurate non-uniform temperature field is determined. Based on the precise non-uniform temperature field and the nonlinear fluctuation of the material's elastic parameters, and simultaneously applying a centrifugal load determined by the rotational speed and an assembly interference fit, the multi-field coupled stress field of the rotor is solved under the condition of considering the nonlinearity of the interface contact. In the multi-field coupled stress field, the contact stress state at the interface of the segmented permanent magnet is extracted, and the axial strain compensation coefficient is calculated through a pre-constructed dynamic correlation model. The axial stress is corrected based on the axial strain compensation coefficient, and the strength of the permanent magnet rotor is verified by combining radial and tangential stresses.

2. The analytical calculation method for the strength of a permanent magnet rotor in a high-speed motor according to claim 1, characterized in that, Based on the gradient characteristics of the initial non-uniform temperature field, field characteristic monitoring points are dynamically arranged at key locations on the rotor; these key locations include at least the axial ends and middle sections of each segmented permanent magnet, the interface region between the permanent magnet and the carbon fiber sheath, and the interface transition region between adjacent permanent magnet segments, including: Analyze the gradient distribution of the initial non-uniform temperature field along the axial and radial directions, and determine the extreme locations and rates of change of the gradient field; Based on the extreme locations and rate of change of the gradient field, a set of initial field characteristic monitoring points located in key parts of the rotor is initially selected. The key parts include the axial end sections of each segment of permanent magnet, the middle sections of each segment of permanent magnet, the interface region between the permanent magnet and the carbon fiber sheath, and the interface transition region between adjacent permanent magnet segments. Based on the temperature data fed back by the initial field feature monitoring point set within the first calculation time step, the completeness of the point set in capturing the spatial features of the temperature field is evaluated, and based on a preset gradient change rate threshold, insufficiently covered areas where the gradient change rate exceeds the threshold are identified. Based on the identified insufficiently covered areas, the position and density of field feature monitoring points are dynamically adjusted to increase the number of field feature monitoring points in the insufficiently covered areas and optimize the distribution of field feature monitoring points in areas where the gradient change rate is lower than the threshold, thus forming an optimized dynamic monitoring point layout scheme. Based on the optimized dynamic monitoring point layout scheme, the dynamic layout of field characteristic monitoring points is carried out starting from the second calculation step.

3. The analytical calculation method for the strength of a permanent magnet rotor in a high-speed motor according to claim 2, characterized in that, The temperature data of the field feature monitoring points is acquired in real time. Based on the acquired temperature data, a dynamic envelope surface characterizing the spatial evolution of the overall temperature field of the rotor is constructed. The surface area change rate of the dynamic envelope surface between adjacent calculation time steps is calculated, and a temperature field distortion correction factor is generated, including: Based on the dynamically arranged field characteristic monitoring points, the temperature data of each monitoring point at the current calculation time step is acquired in real time; Based on the temperature data at the current calculation time step, and combined with the spatial coordinates of each monitoring point, an instantaneous envelope surface is constructed to characterize the spatial distribution of the overall temperature field of the rotor at the current time step. By obtaining the instantaneous envelope surface of the previous calculation time step, the change in surface area between the instantaneous envelope surface of the current calculation time step and the instantaneous envelope surface of the previous calculation time step can be calculated. The rate of change of the surface area of ​​the envelope surface between adjacent calculation time steps is calculated based on the ratio of the change in surface area to the surface area of ​​the instantaneous envelope surface in the previous calculation time step. The rate of change of the envelope surface area between adjacent calculation time steps is mapped to a temperature field distortion correction factor.

4. The analytical calculation method for the strength of a permanent magnet rotor in a high-speed motor according to claim 3, characterized in that, The initial non-uniform temperature field is corrected in real time by a temperature field distortion correction factor to obtain an accurate non-uniform temperature field. Simultaneously, the nonlinear fluctuations in material elastic parameters induced by the accurate non-uniform temperature field are determined, including: By coupling the temperature field distortion correction factor with the initial non-uniform temperature field, the initial temperature field distribution is corrected in real time, and the accurate non-uniform temperature field at the current time step is obtained. Based on the precise non-uniform temperature field at the current time step, the real-time temperature distribution of each component, including the permanent magnet, the magnetic shielding block, and the carbon fiber sheath, is determined. Based on the real-time temperature distribution of each component, including the permanent magnet, the magnetic shielding block, and the carbon fiber sheath, and combined with the pre-stored material property parameters and the nonlinear mapping relationship between temperature, the real-time elastic modulus and real-time Poisson's ratio of each component under the current temperature state are determined. Calculate the relative change between the real-time elastic modulus of each component under the current temperature condition and the elastic modulus under the initial normal temperature condition, and define the relative change as the nonlinear fluctuation value of the material elastic parameter.

5. The analytical calculation method for the strength of a permanent magnet rotor in a high-speed motor according to claim 4, characterized in that, Based on the precise non-uniform temperature field and the nonlinear fluctuations of the material's elastic parameters, and simultaneously applying a centrifugal load determined by the rotational speed and an assembly interference fit, the multi-field coupled stress field of the rotor is solved under the condition of considering the nonlinearity of interface contact, including: Based on the precise non-uniform temperature field and the corresponding nonlinear fluctuation values ​​of the material elastic parameters, the material constitutive relations of each component in the rotor equivalent geometric structure model are updated to obtain the updated material constitutive relation parameters. Based on the real-time acquisition of the current operating speed, the centrifugal load acting on the rotor equivalent geometric model is calculated, and the assembly interference is determined through assembly parameters. In the rotor equivalent geometric model, contact pairs are defined and nonlinear contact criteria based on contact pressure and gap are set for the mating interface between permanent magnets, magnetic shielding blocks and carbon fiber sheaths. The updated material constitutive parameters, centrifugal load, assembly interference, and nonlinear contact criterion are used as coupled boundary conditions to solve the rotor equivalent geometric model, outputting a multi-field coupled stress field containing stress and strain distributions.

6. The analytical calculation method for the strength of a permanent magnet rotor in a high-speed motor according to claim 5, characterized in that, In the multi-field coupled stress field, the contact stress state at the interface of the segmented permanent magnet is extracted, and the axial strain compensation coefficient is calculated through a pre-constructed dynamic correlation model, including: From the multi-field coupled stress field, extract the normal contact stress and tangential contact stress at the interface between adjacent permanent magnet segments; The extracted normal and tangential contact stresses of each interface are input into a pre-built dynamic correlation model; By using a pre-built dynamic correlation model, the real-time axial strain compensation coefficient of the rotor is calculated based on the input interface normal contact stress and tangential contact stress, current operating speed, and axial gradient characteristics of the precise non-uniform temperature field.

7. The analytical calculation method for the strength of a permanent magnet rotor in a high-speed motor according to claim 6, characterized in that, The axial stress is corrected based on the axial strain compensation coefficient, and the strength verification of the permanent magnet rotor is completed by combining radial and tangential stresses, including: Based on the real-time axial strain compensation coefficient, the rotor axial stress components extracted from the multi-field coupled stress field are corrected to obtain the corrected axial stress distribution. From the multi-field coupled stress field, the rotor radial stress distribution and tangential stress distribution corresponding to the axial stress distribution are extracted and corrected simultaneously; The corrected axial stress distribution, radial stress distribution and tangential stress distribution are combined to determine the maximum combined stress of the rotor under operating conditions and its spatial location. Based on the maximum combined stress and combined with the allowable stress of the permanent magnet and the sheath material, the strength verification of the permanent magnet rotor under the current operating conditions is completed.

8. A high-speed motor permanent magnet rotor strength analytical calculation system, wherein the system implements the method as described in any one of claims 1 to 7, characterized in that, include: The temperature field acquisition module is used to acquire the initial non-uniform temperature field with gradient characteristics formed axially by the rotor of a high-speed motor under operating conditions. The monitoring point layout module is used to dynamically arrange field feature monitoring points at key parts of the rotor according to the gradient characteristics of the initial non-uniform temperature field; the key parts include at least the axial ends and middle sections of each segment of permanent magnet, the interface area between the permanent magnet and the carbon fiber sheath, and the interface transition area between adjacent permanent magnet segments. The construction and calculation module is used to acquire temperature data of the field feature monitoring points in real time. Based on the acquired temperature data, a dynamic envelope surface is constructed to characterize the spatial evolution of the overall temperature field of the rotor. The surface area change rate of the dynamic envelope surface between adjacent calculation time steps is calculated to generate a temperature field distortion correction factor. The correction and determination module is used to correct the initial non-uniform temperature field in real time through the temperature field distortion correction factor to obtain the accurate non-uniform temperature field, and at the same time determine the nonlinear fluctuation of the material elastic parameters caused by the accurate non-uniform temperature field. The stress field solving module is used to solve the multi-field coupled stress field of the rotor based on the accurate non-uniform temperature field and the nonlinear fluctuation of the elastic parameters of the material, while applying the centrifugal load determined by the rotational speed and the assembly interference, and considering the nonlinearity of the interface contact. The final processing and verification module is used to extract the contact stress state at the interface of the segmented permanent magnet in the multi-field coupled stress field and calculate the axial strain compensation coefficient through a pre-built dynamic correlation model. The axial stress is corrected based on the axial strain compensation coefficient, and the strength of the permanent magnet rotor is verified by combining radial and tangential stresses.

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