A method and system for optimizing the air gap structure of a permanent magnet vernier motor

Abstract

The present invention discloses a method and system for optimizing the air gap structure of a permanent magnet vernier motor, and relates to the technical field of permanent magnet motors. The method comprises the following steps: constructing a material grid for the air gap structure of the motor; setting the material of the material grid for the air gap structure to obtain a material matrix; optimizing the material matrix using a genetic algorithm to obtain an optimized material combination. The present invention optimizes the air gap structure of the motor by setting a material grid on the stator and rotor sides to construct a material matrix, and searching for the best material combination in combination with an optimization algorithm. Different from the existing optimization methods, the present optimization method can simultaneously consider uniform air gaps, unequal air gaps, and various complex air gap structures in one optimization process, thereby further improving the optimization effect.

Description

Technical Field

[0001] The present invention relates to the technical field of permanent magnet motors, and in particular to a method and system for optimizing the air gap structure of a permanent magnet vernier motor. Background Art

[0002] The permanent magnet vernier motor is a high-performance motor with a simple structure and high torque density. It has received widespread attention in the field of motors at home and abroad. However, it may have a large torque fluctuation problem during operation. Large torque fluctuations will cause the motor's operating characteristics to deteriorate, increase noise and vibration, and in severe cases may cause motor failure and shorten the motor's service life. For permanent magnet vernier motors, the Maxwell stress tensor method can be used to establish the relationship between output torque and air gap flux density. The output torque can be expressed as:

[0003] ;

[0004] Among them, r g is the air gap radius, μ0 is the vacuum permeability, l a is the motor axial length, B rk ,θ rk , B tk ,θ tk are the amplitude and phase of the kth harmonic of the radial air gap flux and the tangential air gap flux, respectively. It can be seen from the above formula that the harmonic of the air gap flux is the key factor affecting the torque fluctuation of the permanent magnet vernier motor. Therefore, it is necessary to optimize the air gap structure of the motor, increase the amplitude of the working harmonic, and reduce the content of the non-working harmonic.

[0005] In order to solve this problem, researchers have proposed a method to optimize the air gap structure. By optimizing the air gap structure, the magnetic field distribution of the motor can be improved and torque fluctuations can be reduced. Most permanent magnet vernier motors are optimized by using optimization algorithms (such as genetic algorithms, particle swarm optimization algorithms, etc.) to optimize the structural parameters of the motor as a whole, and there are fewer methods for optimizing the air gap structure. Due to its special structure and working principle, the stator teeth of the permanent magnet vernier motor participate in the magnetic field modulation, especially the bilateral permanent magnet vernier motor, which has bidirectional magnetic field modulation. The magnetic permeance on the stator and rotor sides will have a greater impact on the air gap magnetic density harmonics, and the air gap structure optimization is more complicated. Summary of the invention

[0006] The purpose of the present invention is to solve the problems in the prior art.

[0007] The technical solution adopted by the present invention to solve the technical problem is: to provide a method for optimizing the air gap structure of a permanent magnet vernier motor, comprising the following steps:

[0008] Construct the air gap structural material grid of the motor;

[0009] Setting the material of the air gap structure material grid to obtain a material matrix;

[0010] Genetic algorithm is used to optimize the material matrix and obtain the optimized material combination.

[0011] Preferably, the motor is an inner rotor double-sided permanent magnet motor with hybrid stator teeth, and the air gap structure of the motor includes an outer side of the rotor and an inner side of the stator;

[0012] The method of constructing the material grid of the air gap structure of the motor is specifically to construct a plurality of material grids distributed on the outer side of the rotor and the inner side of the stator, and the thickness of the material grid is set to be variable.

[0013] Preferably, the distribution and construction of a plurality of material grids for the outer side of the rotor and the inner side of the stator includes:

[0014] For the rotor, six grids are evenly arranged on the surface of each pair of poles of the rotor permanent magnet, including three N poles and three S poles.

[0015] For the stator, build the material mesh according to the type of stator teeth.

[0016] Preferably, the stator teeth include slotted teeth and straight teeth, and the material grid for the stator is constructed according to the type of stator teeth, including:

[0017] Nine grids are arranged on the surface of the slotted teeth; wherein the center line of one grid coincides with the center line axis of the stator permanent magnet, and the remaining eight grids are arranged symmetrically along the center line axis of the stator permanent magnet;

[0018] Set three grids on the surface of the spur teeth.

[0019] Preferably, the initial thickness of the grid is set to 0.1 mm.

[0020] Preferably, the material of the air gap structure material grid is set, and the set materials include: permanent magnet material for radially outward or radially inward excitation, iron core material and air; in the material matrix, 0 represents air, 1 represents permanent magnet material, and 2 represents iron core material.

[0021] Preferably, the material of the grid on the surface of the permanent magnet is set to 0 and 1; the material of the grid on the surface of the stator and rotor core is set to 0 and 2;

[0022] The initial material matrix of the rotor surface mesh for each pair of poles is [111222].

[0023] Preferably, the initial material matrix of the stator slotted tooth surface grid is [222111222]; the initial material matrix of the stator spur tooth surface grid is

[222] .

[0024] Preferably, the optimization of the material matrix using a genetic algorithm comprises the following steps:

[0025] The objective function is constructed and the global minimum of the objective function is solved. The optimization variables of the objective function include the material variables of 6 grids of each pair of poles on the rotor side, the material variables of 8 grids of the two tooth surfaces on the stator side, and the grid thickness variables on both sides of the stator and rotor. The optimization goal is to maximize the output torque and minimize the torque fluctuation. The objective function F is expressed as:

[0026] ;

[0027] in, , and They are the maximum output torque, minimum output torque and average torque respectively; and is the torque fluctuation weight and the average torque derivative weight;

[0028] For the material combination numbers of the grid of a pair of poles on the rotor side, the grid of the slotted teeth on the stator side, and the grid of the straight teeth on the stator side, a genetic algorithm is used to analyze the data and determine whether the minimum value of the objective function is obtained. If so, the current material combination is used as the optimal material combination; otherwise, a new set of material combinations is provided to perform the next iteration until the global minimum is found.

[0029] The present invention also provides a permanent magnet vernier motor air gap structure optimization system, comprising:

[0030] A mesh construction module is used to construct the mesh of the air gap structure material of the motor;

[0031] A matrix construction module sets the material of the air gap structure material grid to obtain a material matrix;

[0032] The material optimization module uses genetic algorithms to optimize the material matrix and obtain the optimized material combination.

[0033] The present invention has the following beneficial effects: the present invention proposes a method for optimizing the air gap structure by constructing a material grid, which can divide the air gap into multiple small areas, and set optimization parameters from the perspective of material composition, so that the optimization of the air gap is more targeted, which helps to improve the accuracy of the optimization results and obtain a better air gap structure; in addition, the material grid method can flexibly divide the air gap area, which is suitable for air gaps of various complex shapes. This method can be used for motors with uneven magnetic field distribution or uneven air gap width.

[0034] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments, but the present invention is not limited to the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A method step diagram of an embodiment of the present invention;

[0036] Figure 2 A schematic diagram of grid division according to an embodiment of the present invention;

[0037] Figure 3 Convergence curve for optimizing mesh material on the rotor side surface;

[0038] Figure 4 The torque waveform before and after the mesh material on the rotor side surface is optimized;

[0039] Figure 5 Convergence curve for optimizing the mesh material on the stator side surface;

[0040] Figure 6 The torque waveform before and after the optimization of the mesh material on the stator side surface;

[0041] Figure 7 Convergence curve for optimizing the mesh material on both sides of the stator and rotor surfaces;

[0042] Figure 8 The torque waveform before and after the optimization of the mesh material on both sides of the stator and rotor;

[0043] Fig. 9 Schematic diagram of doubling the number of material grids;

[0044] Fig.10 4 is a system structure diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0045] See also Figure 1 FIG. 1 is a diagram showing steps of a method according to an embodiment of the present invention, comprising the following steps:

[0046] S101, constructing an air gap structural material grid of the motor;

[0047] S102, setting the material of the air gap structure material grid to obtain a material matrix;

[0048] S103, optimizing the material matrix using a genetic algorithm to obtain an optimized material combination.

[0049] Specifically, take the inner rotor double-sided permanent magnet motor with hybrid stator teeth as an example. The rotor is composed of rotor permanent magnets and rotor core, and the stator is composed of stator permanent magnets, stator core and armature winding. Several material grids of the same thickness are constructed on both sides of the air gap of the motor, that is, on the outer side of the rotor and the inner side of the stator, such as Figure 2As shown. Each permanent magnet on the rotor side and its adjacent rotor tooth form a pair of poles, and 6 grids are evenly set on the surface of each pair of poles, that is, 3 on the permanent magnet surface and 3 on the rotor tooth surface. Then copy and expand it to all pairs of rotor poles. For the stator, the stator teeth are divided into two types: split teeth and straight teeth. Among them, the split teeth are equipped with permanent magnets, and 9 grids are set on the tooth surface. The middle grid on the permanent magnet surface is the symmetry axis, and the grids on both sides are symmetrical. Therefore, when setting variables, only the grid materials on one side of the symmetry axis and the grid materials of the middle permanent magnet are set, which reduces the amount of calculation; 3 grids are set on the straight tooth surface. The grids of the two tooth surfaces on the stator side are copied and extended to the remaining corresponding tooth surfaces. Due to the limitation of accuracy, the initial thickness of all grids is set to 0.1mm. The optimization range of the rotor side grid thickness is set to 0.1mm-Hrpm (rotor permanent magnet thickness); the stator side grid thickness is set to 0.1mm-Hspm (stator permanent magnet thickness).

[0050] Specifically, in the embodiment of the present invention, the initial thickness of the grid is set to 0.1 mm.

[0051] Specifically, in this embodiment, a material matrix is ​​set for the iron core and permanent magnet: GridArray1 [DW315-50, air]; GridArray2 [NdFe35, air] (DW315-50 represents the iron core material, NdFe35 represents the permanent magnet material, and air represents air). For the grids distributed on the surface of the iron core, a material pointer is assigned to it, pointing to GridArray1, 1 represents DW315-50, and 0 represents air; for the grids distributed on the surface of the permanent magnet, a material pointer is assigned to it, pointing to GridArray2, 2 represents NdFe35, and 0 represents air. The materials of all grids can be expressed in the form of a matrix. For example: the grid material of a pair of poles on the rotor side can be expressed as [111222], which means the material composition: iron core-iron core-iron core-permanent magnet-permanent magnet-permanent magnet; it can also be expressed as [011022], which means the material composition: air-iron core-iron core-air-permanent magnet-permanent magnet. The mesh material of the stator side split teeth can be expressed as [111222111], which means the material composition is: iron core-iron core-iron core-permanent magnet-permanent magnet-permanent magnet-iron core-iron core; it can also be expressed as [110020011], which means the material composition is: iron core-iron core-air-air-permanent magnet-air-air-iron core-iron core. The mesh material of the stator side straight teeth can be expressed as

[111] , which means the material is: iron core-iron core-iron core; it can also be expressed as

[010] , which means the material is: air-iron core-air.

[0052] Specifically, S103 optimizes the material matrix obtained in step 2 using the MOGA algorithm. The optimization goal is to maximize the output torque and minimize the torque ripple. The optimization variables are the material variables of the 6 grids of each pair of poles on the rotor side, the material variables of the 8 grids of the two tooth surfaces on the stator side, and the grid thickness variables on both sides of the stator and rotor, a total of 16 variables. The objective function is as follows:

[0053] ;

[0054] in, , and They are the maximum output torque, minimum output torque and average torque respectively; and is the torque fluctuation weight and the average torque derivative weight. For the material matrix of the three regions (a pair of poles on the rotor side, split teeth on the stator side, and the mesh of the spur tooth surface), the genetic algorithm analyzes the data and determines whether the desired minimum value is obtained. If so, the simulation is terminated to obtain the target minimum value and the optimal material combination; otherwise, the genetic algorithm provides a new set of material combinations and executes the next iteration to find the global minimum.

[0055] When the algorithm converges, the optimized material combination is obtained, and finite element simulation is performed on this material combination to verify the results of the optimization algorithm.

[0056] Taking the hybrid stator tooth double-sided permanent magnet motor as an example, after constructing the material mesh on both sides of the air gap, the material matrix is ​​optimized. You can choose to optimize only the rotor side mesh, only the stator side mesh, or both the stator and rotor meshes at the same time.

[0057] The mesh materials of the two tooth surfaces on the stator side are set to be the initial materials and remain unchanged. Only the mesh material on the rotor side surface is optimized by genetic algorithm. The data of the optimization process are as follows: Figure 3 As shown, the torque waveforms before and after optimization are as follows Figure 4 shown.

[0058] The mesh materials of the rotor side surface are set to be the initial materials and remain unchanged. Only the mesh materials of the stator side surface are optimized by genetic algorithm. The data of the optimization process are as follows: Figure 5 As shown, the torque waveforms before and after optimization are as follows Figure 6 shown.

[0059] At the same time, the mesh materials on both sides of the stator and rotor are optimized by genetic algorithm. The data of the optimization process are as follows: Figure 7 As shown, the torque waveforms before and after optimization are as follows Figure 8 shown.

[0060] The comparison of motor output torque characteristics before and after optimization is shown in the following table:

[0061]

[0062] Judging from the optimization results, when the genetic algorithm is used to optimize the rotor side grid alone, the output torque is increased by 11.3%, and the torque pulsation is reduced by 32.1% compared with the initial 5.6%; when the genetic algorithm is used to optimize the stator side grid alone, the output torque is increased by 14%, while the torque pulsation increases by 8.9%; when the genetic algorithm is used to optimize the entire grid, the torque pulsation is reduced by 39.3% while the output torque is reduced by 0.23%.

[0063] When the genetic algorithm is used to optimize the rotor side grid, the output torque is increased by 11.4% and the torque pulsation is reduced by 0.4%; when the genetic algorithm is used to optimize the stator side grid, the output torque is increased by 5% and the torque pulsation is reduced by 0.7%; when the genetic algorithm is used to optimize the entire grid, the torque pulsation is reduced by 1.3% and the output torque is only reduced by 0.2%. In addition, the eddy current loss and core loss of the three cases are reduced.

[0064] For this example, the optimization targets are output torque and torque pulsation, and good results can be achieved in all three cases. The torque improvement after optimization on the single rotor side is the most obvious, the torque pulsation reduction after overall optimization is the most obvious, and the effect after optimization on the single stator side is the most balanced. This optimization method can be used for other types of permanent magnet vernier motors.

[0065] During specific implementation, the number of material grids can also be increased. For finite element analysis software, this can increase the optimization accuracy to a certain extent and improve the final optimization effect and accuracy. Fig. 9 This is a schematic diagram of doubling the number of material grids in the above method to obtain a smaller air gap area. In addition, if the computer configuration is good, the thickness of each grid can be set as a separate variable. When optimizing, the performance of the motor when each grid has different thicknesses is considered, so that the structure on both sides of the air gap forms a shape similar to the coding teeth, which can better utilize the magnetic field and improve the motor optimization effect.

[0066] See also Fig.10 FIG. 1 is a system structure diagram of an embodiment of the present invention, including:

[0067] A grid construction module 1001 constructs a grid of air gap structure materials of the motor;

[0068] A matrix construction module 1002 is used to set the material of the air gap structure material grid to obtain a material matrix;

[0069] The material optimization module 1003 uses a genetic algorithm to optimize the material matrix to obtain an optimized material combination.

[0070] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing the air gap structure of a permanent magnet vernier motor, characterized in that: The following steps are involved: Construct the air gap structural material grid of the motor; Setting the material of the air gap structure material grid to obtain a material matrix; A genetic algorithm is used to optimize the material matrix to obtain an optimized material combination; the motor is an inner rotor double-sided permanent magnet motor with hybrid stator teeth, and the air gap structure of the motor includes an outer side of the rotor and an inner side of the stator; The air gap structure material grid of the motor is constructed, specifically, a plurality of material grids are constructed for the outer side of the rotor and the inner side of the stator respectively, and the thickness of the material grid is set to be variable; The material of the air gap structure material grid is set, and the set materials include: permanent magnet material for radial outward excitation, iron core material and air; in the material matrix, 0 represents air, 1 represents permanent magnet material, and 2 represents iron core material; The method of optimizing the material matrix by using a genetic algorithm comprises the following steps: The objective function is constructed and the global minimum of the objective function is solved. The optimization variables of the objective function include the material variables of 6 grids of each pair of poles on the rotor side, the material variables of 8 grids of the two tooth surfaces on the stator side, and the grid thickness variables on both sides of the stator and rotor. The optimization goal is to maximize the output torque and minimize the torque fluctuation. The objective function F is expressed as: Among them, T max , T min and T avg are the maximum output torque, minimum output torque and average torque respectively; K1 and K2 are the torque fluctuation weight and average torque derivative weight; For the material combination numbers of the grid of a pair of poles on the rotor side, the grid of the slotted teeth on the stator side, and the grid of the straight teeth on the stator side, a genetic algorithm is used to analyze the data and determine whether the minimum value of the objective function is obtained. If so, the current material combination is used as the optimal material combination; otherwise, a new set of material combinations is provided to perform the next iteration until the global minimum is found.

2. The method for optimizing the air gap structure of a permanent magnet vernier motor according to claim 1, characterized in that: The material grids are constructed for the outer side of the rotor and the inner side of the stator, including: For the rotor, six grids are evenly arranged on the surface of each pair of rotor permanent magnet poles, including three N poles and three S poles; For the stator, build the material mesh according to the type of stator teeth.

3. The method for optimizing the air gap structure of a permanent magnet vernier motor according to claim 2, characterized in that: The stator teeth include slotted teeth and straight teeth, and the material grid for the stator is constructed according to the type of the stator teeth, including: Nine grids are arranged on the surface of the slotted teeth; wherein the center line of one grid coincides with the center line axis of the stator permanent magnet, and the remaining eight grids are arranged symmetrically along the center line axis of the stator permanent magnet; Set three grids on the surface of the spur teeth.

4. The method for optimizing the air gap structure of a permanent magnet vernier motor according to claim 1, characterized in that: The material of the mesh on the surface of the permanent magnet is set to 0 and 1; the material of the mesh on the surface of the stator and rotor core is set to 0 and 2; The initial material matrix of the rotor surface mesh for each pair of poles is [111222].

5. The method for optimizing the air gap structure of a permanent magnet vernier motor according to claim 1, characterized in that: The initial material matrix of the stator slotted tooth surface mesh is [222111222]; the initial material matrix of the stator spur tooth surface mesh is [222].

6. The method for optimizing the air gap structure of a permanent magnet vernier motor according to claim 1, characterized in that: The genetic algorithm is used to optimize the material matrix, the thickness of each grid is set as a separate variable, the performance of the motor when each grid has different thickness is considered during optimization, and the structure on both sides of the air gap forms the shape of the coding teeth.

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