A method and system for electromagnetic-thermal bidirectional coupling analysis of a high torque density permanent magnet vernier motor.

Abstract

This invention discloses a method and system for electromagnetic-thermal bidirectional coupling analysis of high torque density permanent magnet vernier motors, belonging to the field of multiphysics coupling analysis technology for motors. This invention constructs a hybrid electromagnetic model based on the scalar magnetic potential method and the equivalent magnetic circuit method, introduces magnetic grid density parameters in the stator core region, and achieves a fine characterization of leakage flux paths and local magnetic saturation effects by determining the spatial discrete resolution of the magnetic grid density. A heat source is established based on the calculated motor losses, and the temperature distribution is solved by inputting a lumped parameter thermal network model. Then, the winding resistance, permanent magnet characteristics, and iron loss parameters are updated based on the temperature field to iteratively complete the bidirectional coupling calculation of the electromagnetic and temperature fields. This invention significantly improves computational efficiency while maintaining the modeling accuracy for complex leakage flux and strong saturation effects, and can be used for the rapid design, performance evaluation, and temperature rise prediction of high torque density permanent magnet vernier motors.

Description

Technical Field

[0001] This invention relates to an electromagnetic-thermal bidirectional coupling analysis method for high torque density permanent magnet vernier motors based on magnetic grid density, belonging to the field of multiphysics coupling analysis technology for permanent magnet motors. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) are widely used in servo drives, electric vehicles, and aerospace due to their high efficiency, high power density, and compact structure. With the increasing demand for high torque density and lightweight designs, PMSMs have gained attention for their ability to achieve high torque output through magnetic field modulation. These motors typically employ high pole pair counts, complex magnetic circuit designs, and auxiliary permanent magnets or stators. During operation, they are prone to inter-pole leakage flux, tooth tip leakage flux, and localized strong magnetic saturation. This not only increases the difficulty of electromagnetic performance analysis but also causes additional losses and increased temperature rise, thereby affecting winding resistance, permanent magnet magnetic properties, and iron loss characteristics, resulting in a significant coupling relationship between the motor's electromagnetic field and temperature field.

[0003] In existing technologies, electromagnetic-thermal coupling analysis of motors typically employs the finite element method (FEM) or a combination of analytical models, equivalent magnetic circuit models, and lumped-parameter thermal network models. While the FEM offers high analytical accuracy, it suffers from high computational complexity and time consumption in the bidirectional coupling iterative analysis of complex motor structures. Although analytical models and equivalent networks improve computational efficiency, their accuracy in high-torque-density permanent magnet vernier motors, which exhibit complex leakage flux paths and strong magnetic saturation effects, heavily relies on the magnetic network partitioning method. Insufficient partitioning accuracy makes it difficult to accurately characterize leakage flux and saturation, while excessively high partitioning accuracy significantly increases the computational burden. Therefore, providing a method for electromagnetic-thermal bidirectional coupling analysis of high-torque-density permanent magnet vernier motors that balances computational accuracy and efficiency is a pressing technical problem in this field. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an electromagnetic-thermal bidirectional coupling analysis method and system for high torque density permanent magnet vernier motors based on magnetic grid density, so as to solve the problems of insufficient leakage flux and saturation modeling accuracy and low computational efficiency in the existing technology when performing bidirectional coupling analysis on high torque density permanent magnet vernier motors with complex topologies.

[0005] To solve the above technical problems, the present invention adopts the following technical solution:

[0006] First, this invention proposes an electromagnetic-thermal bidirectional coupling analysis method for high torque density permanent magnet vernier motors based on magnetic grid density, comprising the following steps:

[0007] S1: Obtain the structural parameters, material parameters, and operating condition parameters of the motor to be analyzed, and establish a hybrid electromagnetic analysis model;

[0008] S2: Introduce magnetic grid density parameters into the equivalent magnetic circuit model of the stator core, spatially discretize the stator teeth and yoke, and construct a magnetoresistive network;

[0009] S3: Based on the hybrid electromagnetic analysis model, solve for the magnetic field distribution and electromagnetic performance of the motor, and calculate the losses;

[0010] S4: Construct a lumped parameter thermal network model, take the loss as the heat source input, and solve for the temperature distribution of each component;

[0011] S5: Update temperature-related parameters based on temperature distribution;

[0012] S6: Repeat the electromagnetic and thermal analysis until the convergence condition is met to obtain the electromagnetic-thermal bidirectional coupling results.

[0013] Furthermore, the structural parameters include at least the stator outer diameter, stator inner diameter, rotor outer diameter, rotor tooth width, stator tooth width, air gap length, main permanent magnet size, and auxiliary permanent magnet size; the material parameters include at least the core magnetization curve, winding resistivity, and permanent magnet remanent characteristics; and the operating condition parameters include at least the rotational speed, load torque, current, voltage, and ambient temperature.

[0014] Furthermore, the hybrid electromagnetic analysis model includes scalar magnetic potential models for permanent magnets and air gaps, as well as an equivalent magnetic circuit model for the stator core. The scalar magnetic potential model for permanent magnets establishes corresponding scalar magnetic potential control equations by considering the magnetization methods, remanent magnetization distribution, and magnetomotive force excitation of the main and auxiliary permanent magnets. The scalar magnetic potential model for air gaps solves for the air gap magnetic flux density distribution by establishing an analytical magnetic field model coupled to the permanent magnet region. The equivalent magnetic circuit model for the stator core establishes an equivalent magnetic circuit model based on nodal magnetomotive force to characterize the leakage magnetic flux and magnetic saturation effects of the stator teeth and stator yoke.

[0015] The spoke-type permanent magnet vernier motor adopts a magnetic circuit structure in which a main permanent magnet and an auxiliary permanent magnet cooperate. The main permanent magnet is preferably tangentially magnetized, and the auxiliary permanent magnet is preferably radially magnetized to enhance the main magnetic flux and improve the air gap magnetic density distribution.

[0016] Furthermore, the stator teeth are modeled using rectangular discrete elements, and the stator yoke is modeled using sector-shaped discrete elements. The rectangular or sector-shaped discrete elements are divided into multiple reluctance branches along the radial or circumferential direction. The magnetic grid density is characterized by the number of layers, rows, and columns of the discrete elements. By introducing the magnetic grid density parameter, the electromagnetic model has adjustable spatial discretization accuracy, thereby balancing computational accuracy and computational efficiency.

[0017] Furthermore, the equivalent magnetic circuit model iteratively updates the magnetic permeability matrix based on the magnetization curve of the core material to characterize the magnetic saturation effect. The solution process employs a numerical iterative method, introducing a relaxation factor during iteration to improve the stability and convergence speed of the nonlinear equations. The electromagnetic field solution is considered converged when the difference in magnetopotential distribution between two adjacent electromagnetic iterations is less than a preset threshold.

[0018] Furthermore, the losses include at least winding copper losses, core losses, and mechanical losses; the copper losses are calculated based on the winding current and the winding resistance at the corresponding temperature; the core losses are calculated based on the current air gap magnetic flux density, core magnetic flux density distribution, and frequency parameters, taking into account the influence of magnetic saturation on the losses; the mechanical losses include friction losses and wind resistance losses; the various types of losses are calculated and applied to their corresponding thermal node positions to form the distributed heat sources required for solving the lumped parameter thermal network.

[0019] Furthermore, the lumped parameter thermal network model treats the stator teeth, stator yoke, slot windings, end windings, rotor core, permanent magnets, and housing as equivalent thermal nodes, and describes the heat transfer relationships between each thermal node and between the thermal nodes and the external environment through thermal conductivity and convective thermal resistance. In the lumped parameter thermal network analysis, each thermal resistance branch is established based on the motor structural dimensions, material thermal conductivity, insulation layer filling rate, varnish filling rate, air convection heat transfer coefficient, and contact area parameters, and the transient or steady-state temperature of each node is solved in conjunction with the heat source input.

[0020] Furthermore, the convergence condition is that the temperature difference of the key thermal node or the change in the key electromagnetic parameter in two adjacent coupling iterations is less than a preset threshold.

[0021] Meanwhile, the present invention also proposes an electromagnetic-thermal bidirectional coupling analysis system, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores program instructions executable by the at least one processor, and when the program instructions are executed, the at least one processor is able to perform the steps of the method proposed in the present invention.

[0022] The present invention adopts the above technical solution, and compared with the prior art, the present invention has the following technical effects:

[0023] (1) This invention introduces a magnetic grid density parameter into the hybrid electromagnetic analysis model, which makes the discretization accuracy of the stator magnetoresistive network adjustable, so as to more accurately characterize the inter-pole leakage flux, tooth tip leakage flux and local strong magnetic saturation phenomenon in the permanent magnet vernier motor, thereby improving the prediction accuracy of air gap magnetic flux density, back EMF, torque and loss.

[0024] (2) The present invention adopts a coupled analysis framework of scalar magnetic potential method, equivalent magnetic circuit method and lumped parameter thermal network method, which significantly reduces the time required for bidirectional coupled analysis while maintaining the analysis accuracy of complex motor structure and improves the analysis efficiency in the design stage.

[0025] (3) By iteratively updating the temperature-related parameters, this invention realizes the bidirectional coupling analysis between the electromagnetic field and the temperature field, which can more realistically reflect the actual operating status of the high torque density permanent magnet vernier motor under rated and overload conditions, and provides an effective technical means for the rapid design, performance evaluation and temperature rise prediction of high torque density motors. Attached Figure Description

[0026] Figure 1 The flowchart shows the electromagnetic-thermal bidirectional coupling analysis method based on magnetic grid density.

[0027] Figure 2 This is a schematic diagram of the high torque density permanent magnet vernier motor involved in this invention.

[0028] Figure 3 This is a magnetic circuit diagram of the motor involved in this invention.

[0029] Figure 4 This is a schematic diagram of the electromagnetic analysis iterative process described in this invention.

[0030] Figure 5 This is a schematic diagram of the stator equivalent magnetic circuit model described in this invention.

[0031] Figure 6 This is a schematic diagram of the rectangular discrete unit of the magnetoresistive network described in this invention.

[0032] Figure 7 This is a schematic diagram of the sector-shaped discrete unit of the magnetoresistive network described in this invention.

[0033] Figure 8 This is the lumped parameter thermal network model of the high torque density permanent magnet vernier motor described in this invention.

[0034] Reference numerals in the attached diagram: 1. Stator; 2. Winding; 3. Auxiliary permanent magnet; 4. Main permanent magnet; 5. Magnetic barrier; 6. Rotor core; 7. Magnetic bridge; 8. Armature current; 9. Saturation current. Detailed Implementation

[0035] To better understand the technical content of the present invention, specific embodiments are described below in conjunction with the accompanying drawings.

[0036] In this invention, various aspects of the invention are described with reference to the accompanying drawings, in which numerous illustrative embodiments are shown. Embodiments of the invention are not limited to those depicted in the drawings. It should be understood that the invention is implemented through any of the various concepts and embodiments described above, as well as the concepts and embodiments described in detail below, because the concepts and embodiments disclosed herein are not limited to any particular implementation. Furthermore, some aspects of the invention disclosed may be used alone or in any suitable combination with other aspects of the invention disclosed.

[0037] First refer to Figure 1 As shown, this embodiment provides an electromagnetic-thermal bidirectional coupling analysis method for high torque density permanent magnet vernier motors based on magnetic grid density, which consists of the following steps:

[0038] S1. Input motor structural parameters, material parameters, and operating conditions;

[0039] The structural parameters include stator outer diameter, stator inner diameter, rotor outer diameter, rotor tooth width, stator tooth width, air gap length, main permanent magnet size, and auxiliary permanent magnet size; the material parameters include at least the core magnetization curve, winding resistivity, and permanent magnet remanent characteristics; and the operating condition parameters include at least the speed, load torque, current, voltage, and ambient temperature.

[0040] S2. Establish a hybrid electromagnetic model based on magnetic grid density, in which magnetic grid density is introduced into the stator tooth / yoke discrete element, and the permanent magnet, air gap and stator core are modeled by scalar magnetic potential method and equivalent magnetic circuit method respectively, forming a scalar magnetic potential model including permanent magnet and air gap, and an equivalent magnetic circuit model of stator core.

[0041] The permanent magnet scalar magnetic potential model establishes corresponding scalar magnetic potential control equations by considering the magnetization mode, remanent magnetization distribution and magnetomotive force excitation of the main permanent magnet and the auxiliary permanent magnet.

[0042] The air gap scalar magnetic potential model solves for the air gap magnetic flux density distribution by establishing an analytical magnetic field model coupled with the permanent magnet region.

[0043] The equivalent magnetic circuit model of the stator core is established based on nodal magnetomotive force to characterize the leakage magnetic field and magnetic saturation effect of the stator teeth and stator yoke. The stator teeth are modeled using rectangular discrete elements, and the stator yoke is modeled using sector-shaped discrete elements; the rectangular or sector-shaped discrete elements are divided into multiple reluctance branches along the radial or circumferential direction.

[0044] The magnetic grid density is characterized by the number of layers, rows, and columns of discrete units. By introducing the magnetic grid density parameter, the electromagnetic model has adjustable spatial discretization accuracy, thereby balancing computational accuracy and computational efficiency.

[0045] S3. Perform electromagnetic field analysis: Solve for the electromagnetic performance and losses of the motor based on the current temperature-related parameters.

[0046] The equivalent magnetic circuit model iteratively updates the magnetic permeability matrix based on the magnetization curve of the core material to characterize the magnetic saturation effect. The solution process employs a numerical iterative method, introducing a relaxation factor during iteration to improve the stability and convergence speed of the nonlinear equations. The electromagnetic field solution is considered convergent when the difference in magnetopotential distribution between two adjacent electromagnetic iterations is less than a preset threshold.

[0047] The losses include at least winding copper loss, core loss, and mechanical loss; the copper loss is calculated based on the winding current and the winding resistance at the corresponding temperature; the core loss is calculated based on the current air gap magnetic flux density, core magnetic flux density distribution, and frequency parameters, and the influence of magnetic saturation on the loss is considered; the mechanical loss includes friction loss and wind resistance loss; the various types of losses are calculated and applied to their corresponding thermal node positions to form the distributed heat source required for solving the lumped parameter thermal network.

[0048] S4. Perform temperature field analysis: Input the loss as a heat source into the lumped parameter thermal network model of the motor, and solve for the transient temperature distribution and temperature rise of each component.

[0049] The lumped parameter thermal network model treats stator teeth, stator yoke, slot windings, end windings, rotor core, permanent magnets, and housing as equivalent thermal nodes, and describes the heat transfer relationships between each thermal node and between the thermal nodes and the external environment through thermal conductivity and convective thermal resistance. In the lumped parameter thermal network analysis, each thermal resistance branch is established based on the motor structural dimensions, material thermal conductivity, insulation layer filling rate, varnish filling rate, air convection heat transfer coefficient, and contact area parameters, and the transient or steady-state temperature of each node is solved in combination with the heat source input.

[0050] S5. Update temperature parameters: Update winding resistance, permanent magnet characteristics, iron loss parameters, etc., based on the temperature field to provide corrected input parameters for the next round of electromagnetic analysis.

[0051] S6. Determine whether the preset termination time has been reached. If yes, output the coupling analysis result; otherwise, return to step S3.

[0052] like Figure 2 As shown, the high torque density permanent magnet vernier motor includes a stator 1, a rotor core 6 and a magnetic bridge 7; the stator 1 is provided with a winding 2; a magnetic barrier 5 is provided between adjacent rotor cores 6; an auxiliary permanent magnet 3 is provided on the top of the rotor core 6; and a main permanent magnet 4 is provided on the side of the rotor core 6 near the magnetic barrier 5.

[0053] The high torque density permanent magnet vernier motor adopts a combination structure of main permanent magnet 4 and auxiliary permanent magnet 3, wherein the main permanent magnet 4 is tangentially magnetized and the auxiliary permanent magnet 3 is radially magnetized, and high torque density is achieved by utilizing the magnetic field modulation effect.

[0054] like Figure 3 As shown, due to the presence of inter-pole leakage magnetic field, tooth tip leakage magnetic field, and local strong magnetic saturation phenomena in this structure, it is necessary to establish a coupled analysis method that takes into account both accuracy and efficiency.

[0055] First, according to such Figure 4 The flowchart shown establishes a hybrid electromagnetic analysis model of the motor. This hybrid electromagnetic analysis model includes scalar magnetic potential models for the permanent magnet region and the air gap region, as well as an equivalent magnetic circuit model for the stator core region, such as... Figure 5 As shown in the figure. In the permanent magnet region, the remanent magnetization distribution of the permanent magnet is considered, and a corresponding analytical magnetic field model is established in the air gap region. In the stator core region, to characterize the nonlinear magnetic saturation effect in the stator teeth and stator yoke, an equivalent magnetic circuit model based on nodal magnetomotive force is adopted.

[0056] The process of establishing the hybrid electromagnetic analysis model in step S2 is as follows:

[0057] S201. Using the scalar magnetic potential method, an analytical model of the permanent magnet and the air gap region is established, and the magnetomotive force of the permanent magnet and the distribution of the air gap magnetic field are calculated through the Poisson equation and the Laplace equation.

[0058] S202. Perform magnetic grid density modeling and establish an equivalent magnetic circuit model of the stator core;

[0059] S203. Initialize the magnetic permeability matrix Gm;

[0060] S204. Solve for the nodal magnetic potential distribution V, and update the magnetic permeability according to the BH curve to characterize magnetic saturation;

[0061] S205. Introduce a relaxation factor and perform nonlinear iteration until the solution converges; otherwise, return to S204.

[0062] In step S201 of this embodiment, in the permanent magnet region, considering the remanence of the permanent magnet, the scalar magnetopotential satisfies the Poisson equation, which is obtained by solving for:

[0063] ,

[0064] In the formula, A0, B0, A n B n is the undetermined coefficient; n is the harmonic order; r is the calculation radius.

[0065] Among them, the special solution P n (r) is calculated using the following method:

[0066] ,

[0067] In the formula, B rn It is the harmonic coefficient of the remanence of a permanent magnet.

[0068] The calculation method for the scalar magnetomotive force in the air gap region is the same as the process described above, and the result is:

[0069] ,

[0070] In the formula, Cn and Dn are undetermined coefficients; r pm_ry It is the radius at the junction of the permanent magnet and the rotor yoke; r st_g It is the radius at the junction of the stator teeth and the air gap; r pm_g It is the radius at the junction of the permanent magnet and the air gap.

[0071] In step S202 of this embodiment, a magnetic grid density parameter is introduced into the equivalent magnetic circuit model of the stator core. Specifically, as shown... Figure 6 As shown, the stator teeth are discretized into rectangular elements, such as... Figure 7 The stator yoke is discretized into sector-shaped elements, and the magnetic grid density is characterized by the number of layers, rows, and columns of these discrete elements. The equivalent magnetic reluctance of the rectangular discrete element is then:

[0072] ,

[0073] ,

[0074] In the formula, x0 is the width of the equivalent rectangular discrete element; y0 is the length of the equivalent rectangular discrete element; L is the axial length of the high torque density permanent magnet vernier motor; μ0 is the vacuum permeability; and μ r It is the relative permeability of the core material.

[0075] The equivalent magnetic reluctance of the sector-shaped discrete element is:

[0076] ,

[0077] In the formula, θ0 is the angle of the equivalent sector discrete element; r0 is the starting edge of the equivalent sector discrete element calculation; r i It is the equivalent sector discrete element used to calculate the terminal edge.

[0078] Higher magnetic mesh density results in higher spatial resolution of the magnetoresistive network, leading to more detailed characterization of leakage magnetic paths and local magnetic saturation; however, it also increases the computational scale. By setting different numbers of magnetic mesh layers, the balance between analytical accuracy and efficiency can be adjusted.

[0079] In step S203 of this embodiment, the initial value of Gm is given by calculation using the linear scalar magnetic potential method in S201.

[0080] In step S204 of this embodiment, the initial value of the magnetic permeability matrix is ​​first given according to the linear model, and then the magnetic permeability value of each branch in the magnetic permeability matrix is ​​iteratively updated according to the BH curve of the core material to establish a nonlinear magnetic circuit equation considering magnetic saturation.

[0081] ,

[0082] In the formula, V is the equivalent magnetic circuit node magnetomotive force, and G is... m It is the magnetic permeability matrix, Φ PM It is an equivalent magnetic flux source of a permanent magnet, L s It is the winding inductance matrix, I s Is it like this? Figure 5 The armature current 8, I shown sat Is it like this? Figure 5 The equivalent saturation current shown is 9.

[0083] In step S205 of this embodiment, a numerical iterative method is further used to solve for the nodal magnetic potential distribution, and a relaxation factor is introduced during the iteration process to improve the convergence speed of the solution:

[0084] ,

[0085] In the formula α r It is a relaxation factor.

[0086] In step S3 of this embodiment, after the magnetomotive force solution in step S2 converges, the air gap magnetic flux density, phase flux linkage, and back electromotive force are obtained, and the electromagnetic torque is calculated within one electrical cycle:

[0087] ,

[0088] In the formula P em It is electromagnetic power, Ω is the rotor mechanical angle, and e is the electromagnetic power. i It is the equivalent branch back electromotive force, φ i It is the equivalent branch flux, i i It is the equivalent branch current.

[0089] Step S3, after calculating the electromagnetic performance, further calculates the losses. Copper losses are obtained based on the winding resistance and current, and the winding resistance is updated as temperature changes.

[0090] ,

[0091] In the formula, m is the number of phases of the motor, and R s It is T k Phase resistance at time t, R s0 It is the phase resistance at time T0, α Cu It is the temperature coefficient of copper resistivity.

[0092] Iron loss is calculated using a loss model that considers the effects of frequency and magnetic saturation.

[0093] ,

[0094] In the formula, f is the motor frequency, and C hys It is the simplified hysteresis mapping function, C eddy It is the simplified eddy current mapping function, I d It is the direct-axis current, I d It is a quadrature-axis current.

[0095] Mechanical losses include frictional losses and wind resistance losses, both of which are proportional to the rotational speed of the IPMSM, but are difficult to measure accurately. Therefore, they are usually extracted through unloaded testing of the prototype. These losses are collectively used as the heat source input to the thermal analysis model.

[0096] Furthermore, the thermal analysis section in step S4 employs, as follows: Figure 8 The lumped-parameter thermal network model is shown. Based on the motor geometry, components such as stator teeth, stator yoke, slot windings, end windings, rotor, permanent magnets, and housing are designated as thermal nodes. These thermal nodes are connected by thermal conductivity and convective thermal resistance to describe the internal heat transfer path of the motor. Copper losses, iron losses, and mechanical losses obtained from electromagnetic analysis are applied to the corresponding thermal nodes, and the temperature distribution of each key component is then solved.

[0097] After obtaining the temperature distribution, in step S5, the winding resistance, permanent magnet performance parameters, and iron loss model parameters are updated using the temperature distribution. Electromagnetic analysis is then performed again to recalculate the electromagnetic performance and losses. Subsequently, the updated losses are re-input into the lumped-parameter thermal network model to solve for the new temperature distribution. This process forms a bidirectional coupling iteration between the electromagnetic field and the temperature field.

[0098] When the temperature difference of key hot nodes in two adjacent iterations is less than a preset threshold, or when the change in loss and torque in two adjacent iterations is less than a preset threshold, the iteration stops and the final coupling analysis results are output, including air gap magnetic flux density, back EMF, torque, loss and temperature distribution.

[0099] To determine the target magnetic mesh density suitable for this type of high torque density permanent magnet vernier motor, the coupling analysis results under different magnetic mesh densities with different numbers of layers can be compared. By comparing the performance of each scheme in terms of air gap magnetic flux density, back EMF, loss error, and computation time, the optimal magnetic mesh density that balances computational accuracy and efficiency is selected as the target magnetic mesh density.

[0100] The method described in this invention can be used not only for electromagnetic-thermal coupling analysis of high torque density permanent magnet vernier motors under rated operating conditions, but also for torque and temperature rise prediction under overload conditions, making it suitable for scenarios such as rapid motor design, parameter optimization, and performance evaluation.

[0101] This embodiment also proposes an electromagnetic-thermal bidirectional coupling analysis system, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores program instructions executable by the at least one processor, and when the program instructions are executed, the at least one processor is able to perform the steps of the method proposed in this invention.

[0102] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0103] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0106] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for electromagnetic-thermal bidirectional coupling analysis of a high torque density permanent magnet vernier motor based on magnetic grid density, characterized in that, Includes the following steps: S1. Obtain the structural parameters, material parameters, and operating condition parameters of the high torque density permanent magnet vernier motor to be analyzed, and establish a hybrid electromagnetic analysis model, including: scalar magnetic potential model of the permanent magnet and air gap region, and equivalent magnetic circuit model of the stator core region; S2. Introduce a magnetic mesh density parameter into the equivalent magnetic circuit model, and perform layered and discrete division of the stator tooth and yoke parts to construct a magnetoresistive network for characterizing leakage magnetic path and magnetic saturation characteristics. S3. Solve the electromagnetic characteristics of the motor based on the hybrid electromagnetic analysis model, and calculate the motor losses; S4. Construct a lumped parameter thermal network model corresponding to each component of the motor, input the loss as a heat source into the lumped parameter thermal network model, and solve for the motor temperature distribution; S5. Update the temperature-related parameters of the motor according to the temperature distribution; S6. Based on the updated temperature-related parameters, repeat steps S3 and S4 until the temperature distribution or electromagnetic performance parameters of two adjacent iterations meet the preset convergence conditions, and obtain the electromagnetic-thermal bidirectional coupling analysis results of the motor.

2. The method according to claim 1, characterized in that, The high torque density permanent magnet vernier motor includes a tangentially magnetized main permanent magnet and a radially magnetized auxiliary permanent magnet. The auxiliary permanent magnet is used to provide a closed magnetic circuit for the main magnetic flux and the modulation magnetic flux, so as to improve the air gap magnetic density and reduce the leakage magnetic effect.

3. The method according to claim 1, characterized in that, The magnetic grid density parameter mentioned in step S2 is characterized by the number of rows and columns of the stator core discrete unit. The discrete unit includes rectangular units for representing the stator teeth and sector units for representing the stator yoke. Different magnetic grid densities correspond to magnetoresistive networks with different spatial resolutions.

4. The method according to claim 3, characterized in that, The equivalent magnetic circuit model establishes the nodal magnetomotive force equation based on Kirchhoff's laws, and iteratively updates the permeability of each reluctance branch according to the magnetization curve of the core material to characterize the nonlinear magnetic saturation effect of the stator teeth and yoke. The nodal magnetic potential distribution is solved by numerical iteration, and a relaxation factor is introduced during the iteration process to accelerate the convergence speed of the nonlinear solution.

5. The method according to claim 1, characterized in that, The electromagnetic characteristics mentioned in step S3 include magnetomotive force distribution, air gap magnetic flux density, winding flux linkage, and electromagnetic torque. The motor losses include copper loss, iron loss, and mechanical loss. Copper loss is calculated based on winding resistance considering the effect of temperature. Iron loss is calculated based on a loss model considering magnetic saturation and frequency effects. Mechanical loss includes friction loss and wind resistance loss.

6. The method according to claim 1, characterized in that, The lumped parameter thermal network model described in step S4 treats the stator teeth, stator yoke, slot windings, end windings, rotor core, permanent magnets, and casing as equivalent thermal nodes, and establishes the heat transfer relationship between each thermal node through thermal conductivity and convective thermal resistance.

7. The method according to claim 1, characterized in that, The temperature-related parameters mentioned in step S5 include at least the winding resistance, permanent magnet magnetic performance parameters, and iron loss-related parameters.

8. The method according to claim 1, characterized in that, The preset convergence condition in step S6 is that the temperature difference of any key hot node in two adjacent iterations is less than a preset threshold, or the change in motor loss value and torque value in two adjacent iterations is less than a preset threshold.

9. The method according to claim 1, characterized in that, After performing step S2, the analysis results under different magnetic grid densities are compared, and the target magnetic grid density is determined by taking into account the air gap magnetic flux density, back electromotive force, loss error and calculation time, so as to balance the calculation accuracy and calculation efficiency.

10. An electromagnetic-thermal bidirectional coupling analysis system, characterized in that, include: At least one processor; The system also includes a memory communicatively connected to the at least one processor; wherein the memory stores program instructions that, when executed by the at least one processor, enable the at least one processor to perform the following functions: acquire motor structural parameters, material parameters, and operating condition parameters; construct a hybrid electromagnetic analysis model including a scalar magnetic potential model of the permanent magnet and air gap region and an equivalent magnetic circuit model of the stator core region; and introduce a magnetic grid density parameter into the equivalent magnetic circuit model to construct a magnetoresistive network. The electromagnetic characteristics and loss distribution of the motor are calculated based on the hybrid electromagnetic analysis model; a heat source is constructed based on the loss distribution, and the temperature distribution is calculated through a lumped parameter thermal network model; the motor parameters are updated according to the temperature distribution, and bidirectional iterative calculations of the electromagnetic field and temperature field are performed.

Images