Magnetic network modeling method and system for stator partitioned electric excitation flux switching motor

Abstract

The present invention proposes a magnetic network modeling method and system for a stator partitioned electric excitation flux switching motor, the method comprising: defining geometric parameters and material parameters of motor components; partitioning and modeling the stator based on the flux tube model of the traditional magnetic circuit method; dividing the nodes of the motor rotor and air gap based on the grid according to the required magnetic network accuracy; calculating the magnetomotive force of each branch according to the winding parameters and the current source excitation; considering the magnetic leakage in the stator slot, the slot and the non-magnetic material leakage of the rotor based on the magnetic network model; defining the connection mode between the motor units, and obtaining the complete magnetic network model under different rotor positions according to different rotor positions corresponding to different times; based on the complete magnetic network model, performing nonlinear iterative calculation on the magnetic permeability of the stator and rotor cores to obtain the final convergence result of the magnetic network model. The present invention can efficiently establish the magnetic network model of this type of motor.

Description

Technical Field

[0001] The present invention belongs to the field of motor optimization design, and in particular relates to a magnetic network modeling method and system for a stator partitioned electric excitation flux switching motor. Background Art

[0002] In the past 20 years, permanent magnet motors have been greatly studied and developed due to their advantages of high torque density and high efficiency. However, permanent magnet motors have the problems of high cost and limited operating temperature. In recent years, a stator-partitioned electric excitation flux switching motor has been proposed. Although the efficiency of the stator-partitioned electric excitation flux switching motor is usually slightly lower than that of the permanent magnet motor, the above two problems have been solved. The two stators of the stator-partitioned electric excitation flux switching motor are wound by armature windings and excitation windings respectively, and the intermediate rotor is composed of a modulating block core. Because the rotor does not have any coils and permanent magnets, this stator-partitioned electric excitation flux switching motor can operate at high speeds. In addition, the internal space of the stator-partitioned electric excitation flux switching motor is well utilized, which can further improve the torque density compared with the traditional electric excitation flux switching motor with a single stator.

[0003] Accurate performance calculation is always an essential part of motor design. There are several main methods for calculating the magnetic field of stator partitioned electromagnetic flux switching motors: finite element analysis is the most commonly used numerical analysis method for calculating mechanical electromagnetic performance. Although the finite element analysis method has the highest calculation accuracy, its main disadvantage is that it takes a longer calculation time; the MMF magnetic permeability model usually has a faster calculation speed, but usually cannot consider the magnetic saturation of the core; the equivalent magnetic circuit method and the equivalent magnetic network are the most commonly used methods for quickly calculating the electromagnetic performance of machines, and magnetic saturation can be considered. The main difference between these two methods lies in the accuracy of magnetic resistance division. Compared with the magnetic circuit method, the equivalent magnetic network generally has more nodes, so it has a relatively higher accuracy.

[0004] The equivalent magnetic network can accurately and quickly predict the performance of the motor in the early stage of motor design and achieve preliminary optimization of the motor. However, at present, there is only the traditional equivalent magnetic circuit method for stator partitioned electric excitation flux switching motor. Therefore, the magnetic network modeling for stator partitioned electric excitation flux switching motor still has high research value. Summary of the invention

[0005] The purpose of the present invention is to provide a magnetic network modeling method and system for a stator partitioned electric excitation flux switching motor, which can efficiently model the motor. To achieve the above purpose, the technical solution adopted is as follows:

[0006] A magnetic network modeling method for a stator partitioned electric excitation flux switching motor comprises the following steps:

[0007] Step S1, modeling motor components;

[0008] Step S2, calculating magnetic resistance, leakage magnetic resistance, and magnetomotive force, wherein:

[0009] The reluctance includes the reluctance of the inner stator, the outer stator, and the reluctance of the magnetic grid elements in two directions;

[0010] The leakage reluctance includes the leakage reluctance of the inner stator slots, the outer stator slots, the slots and the non-magnetic materials of the rotor;

[0011] The magnetomotive force includes the magnetomotive force of the field winding and the armature winding;

[0012] Step S3, defining the connection modes between the rotor and the inner air gap and the outer air gap respectively according to the rotor positions corresponding to different moments;

[0013] Based on the magnetic resistance and leakage magnetic resistance calculated in step S2 and the connection modes corresponding to different rotor positions, a magnetic network model under different rotor positions is obtained;

[0014] Step S4: Based on the complete magnetic network model obtained in S3, a nonlinear iterative calculation is performed on the relative magnetic permeability u to obtain a final convergence result of the magnetic network model.

[0015] Preferably, step S1 specifically includes:

[0016] Step S11, defining the geometric parameters and material parameters of the inner stator, the outer stator and the rotor; and providing the electromagnetic characteristic curve of the material;

[0017] Step S12, dividing and modeling the inner stator and the outer stator based on the flux tube model of the traditional magnetic circuit method;

[0018] Step S13, dividing the magnetic grid elements of the rotor, air gap and slot according to the required magnetic network accuracy.

[0019] Preferably, in step S2, the excitation winding magnetomotive force F f And the three-phase armature winding magnetomotive force F a , F b , F c It can be expressed as:

[0020]

[0021] Among them, N f Indicates the number of turns of the excitation winding, I f Indicates the magnitude of the excitation current; N c Indicates the number of turns of the three-phase armature winding coil, i a 、i b 、i c Respectively represent the instantaneous values ​​of the three-phase current.

[0022] Preferably, in step S2, the equivalent magnetic resistance R1 of the stator teeth along the radial direction can be expressed as:

[0023]

[0024] Where L represents the magnetic path length of the motor stator tooth in the direction of the magnetic flux, μ0 represents the vacuum magnetic permeability, and μ t represents the relative magnetic permeability of the stator teeth of the motor, W represents the width of the stator teeth, and D represents the axial length of the motor;

[0025] The equivalent magnetic resistance R2 of the stator yoke along the tangential direction can be expressed as:

[0026]

[0027] Among them, μ y Represents the relative magnetic permeability of the motor stator yoke, R i , R o Respectively represent the inner and outer diameters of the ring, and θ represents the arc swept by the ring;

[0028] The trapezoidal magnetic resistance R3 of the stator pole shoes along the magnetic flux direction can be expressed as:

[0029]

[0030] Among them, μ sh It represents the relative magnetic permeability of the motor stator pole shoe, W1 and W2 represent the length of the short base and long base of the trapezoid, and H represents the height of the trapezoid.

[0031] Preferably, in step S2, the radial magnetic resistance R of the magnetic network grid element r and tangential magnetic resistance R t It can be expressed as:

[0032]

[0033] For a motor component, m and n represent the number of grids in the radial and tangential directions, respectively, and ri and r o They represent the inner and outer diameters of the ring respectively, and α represents the angle swept by a motor component in the circumferential direction.

[0034] Preferably, step S4 specifically includes:

[0035] S41. Calculate the complete magnetic network to obtain the magnetic flux Φ of each branch, calculate the magnetic flux density B of each branch, and obtain a new relative magnetic permeability by looking up the μ-B curve of common materials.

[0036] S42. Calculate the relative error between the current magnetic permeability and the magnetic permeability of the previous iteration. If the relative error is greater than the given error δ, update the relative magnetic permeability and continue iterating until the relative error is less than δ, that is, the calculation result converges. At this time, record the current magnetic flux and magnetic flux density, and the calculation of the motor magnetic network iteration model is completed.

[0037] A magnetic network modeling system for a stator partitioned electric excitation flux switching motor, comprising:

[0038] Parameter definition module: initialize the parameters of the equivalent magnetic network, give the initial magnetic permeability, calculate the initial magnetic resistance of the stator and rotor cores; calculate the magnetic motive force of each branch according to the excitation and winding parameters; give the grid accuracy and calculate the grid magnetic resistance of each component of the motor;

[0039] Magnetic network model construction module: Based on the magnetic network model, the magnetic flux leakage in the stator slot and slot opening as well as the magnetic flux leakage of the rotor non-magnetic material are considered; the connection mode between the motor units is defined, and the complete magnetic network model under different rotor positions is obtained according to the different rotor positions corresponding to different times;

[0040] And iterative calculation module: based on the complete magnetic network model, the magnetic permeability of the stator and rotor cores is calculated nonlinearly to obtain the final convergence result of the magnetic network.

[0041] Compared with the prior art, the advantages of the present invention are:

[0042] 1. The magnetic network modeling method of the stator partitioned electric excitation flux switching motor provided by the present invention can be used to establish a magnetic network model of this type of motor in MATLAB / Simulink, which is more accurate than the equivalent magnetic circuit method;

[0043] 2. Using the magnetic network modeling method of the stator partitioned electric excitation flux switching motor provided by the present invention, a magnetic network model of this type of motor can be established in the early stage of motor design to accurately and quickly obtain the main performance of the motor, which is convenient for the optimal design of the motor and has the characteristics of being intuitive and easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A flow chart of a magnetic network modeling method for a stator partitioned electrically excited flux switching motor;

[0045] Figure 2 It is a topological structure diagram of a stator partitioned electric excitation flux switching motor;

[0046] Figure 3 (a) is a schematic diagram of the stator pole shoe magnetic circuit. Figure 3 (b) is a schematic diagram of the modeling of the stator pole shoe of the present invention;

[0047] Figure 4 Schematic diagram for modeling the inner stator slots;

[0048] Figure 5 Schematic diagram for modeling the outer stator slots;

[0049] Figure 6 This is a model diagram of a ring grid element;

[0050] Figure 7 This is a complete magnetic network model diagram;

[0051] Figure 8 This is a comparison diagram of the no-load air gap flux density predicted by the present invention and the result predicted by the finite element method at the d-axis position, wherein the excitation current is 3.6 amperes;

[0052] Fig. 9 This is a comparison chart of the no-load flux linkage of phase A predicted by the present invention and the result predicted by the finite element method, wherein the excitation current is 3.6 amperes;

[0053] Fig.10 This is a comparison diagram of the load air gap flux density predicted by the present invention and the result predicted by the finite element at the d-axis position; wherein the excitation current is 3.6 amperes, the q-axis current is 20 amperes, the d-axis current is 0, and the d-axis and q-axis currents are the currents in the two-phase stationary coordinate system obtained by Park transformation of the currents in the abc three-phase rotating coordinate system;

[0054] Fig.11 This is a comparison chart of the A-phase load flux predicted by the present invention and the results predicted by the finite element method, wherein the excitation current is 3.6 amperes, the q-axis currents are 5, 10, 15, and 20 amperes respectively, and the d-axis current is 0;

[0055] Fig.12 This is a comparison chart of the average electromagnetic torque predicted by the present invention and the result predicted by the finite element method, wherein the excitation current is 3.6 amperes, the q-axis currents are 5, 10, 15, and 20 amperes respectively, and the d-axis current is 0; DETAILED DESCRIPTION

[0056] The magnetic network modeling method and system of the stator partitioned electric excitation flux switching motor of the present invention will be described in more detail below in conjunction with the schematic diagram, wherein the preferred embodiment of the present invention is shown, and it should be understood that those skilled in the art can modify the present invention described herein and still achieve the advantageous effects of the present invention. Therefore, the following description should be understood as being widely known to those skilled in the art and not as a limitation of the present invention.

[0057] like Figure 1 As shown, a magnetic network modeling method of a stator partitioned electric excitation flux switching motor based on MATLAB / Simulink includes the following steps:

[0058] Step S1, modeling the motor components, specifically including the following steps:

[0059] Step S11, defining the geometric parameters and material parameters of the motor components (stator, rotor), including size parameters, geometric position, number of coil turns, etc.; defining the electromagnetic characteristics of the stator and rotor.

[0060] Specifically: the size parameters, geometric position, winding position and number of turns of the inner stator, outer stator and rotor; the material of the stator and the magnetic conductive part of the rotor are all iron core, and the BH curve of the iron core is given. H is the magnetic field intensity of the iron core; B is the magnetic flux density of the iron core. B = uH, which can be converted into μ-B curve.

[0061] From the above-mentioned size parameters, the cross-sectional areas S of the inner stator, the outer stator and the rotor can be obtained, so as to be used for obtaining the magnetic flux density B of each branch in the subsequent step S4.

[0062] Initialize the relative permeability to μ k-1 =a.

[0063] Step S12, dividing and modeling the inner stator and the outer stator based on the flux tube model of the traditional magnetic circuit method;

[0064] Step S13, dividing the magnetic grid elements of the rotor, air gap and slot according to the required magnetic network accuracy.

[0065] The results are as follows Figure 2 The motor structure shown in the figure has 12 inner and outer stator slots, and the intermediate rotor has 10 modulated iron blocks (rotor core) embedded in non-magnetic materials, and there is an air gap between the stator and the rotor. The three-phase symmetrical AC armature winding is wound on the outer stator, and the excitation winding with direct current is wound on the inner stator. In addition, the technology involved in the present invention is not only applicable to this type of winding, but also to single-phase, multi-phase, and asymmetric motor windings.

[0066] S2. Calculate the magnetic resistance, leakage magnetic resistance, and magnetomotive force.

[0067] The reluctance includes the reluctance of the inner stator, the outer stator, and the reluctance of the magnetic grid elements in two directions;

[0068] The leakage reluctance includes the leakage reluctance of the inner stator slots, the outer stator slots, the slots and the non-magnetic materials of the rotor;

[0069] The magnetomotive force includes the magnetomotive force of the excitation winding and the armature winding.

[0070] Excitation winding magnetomotive force F f And the three-phase armature winding magnetomotive force F a , F b , F c It can be expressed as:

[0071]

[0072] Among them, N f Indicates the number of turns of the excitation winding, I f Indicates the magnitude of the excitation current; N c Indicates the number of turns of the three-phase armature winding coil, i a 、i b 、i c Respectively represent the instantaneous values ​​of the three-phase current.

[0073] The magnetic resistance of the inner and outer stators of the motor are divided into rectangular magnetic resistance, annular magnetic resistance and trapezoidal magnetic resistance.

[0074] The stator teeth are regarded as rectangular magnetic resistance, and the equivalent magnetic resistance R1 along the radial direction (radial direction of the stator) can be expressed as

[0075]

[0076] Where L represents the magnetic path length of the motor stator tooth in the direction of the magnetic flux, μ0 represents the vacuum magnetic permeability, and μ t represents the relative magnetic permeability of the stator teeth of the motor, W represents the width of the stator teeth, and D represents the axial length of the motor.

[0077] Initially, μ t =a; in subsequent iterations, μ t =μ k .

[0078] The stator yoke is regarded as an annular magnetic resistance, and the equivalent magnetic resistance R2 along the tangential direction can be expressed as:

[0079]

[0080] Among them, μ y Represents the relative magnetic permeability of the motor stator yoke, R i , R o represent the inner and outer diameters of the ring, respectively, and θ represents the arc swept by the ring. Initially, μ y =a; in subsequent iterations, μ y =μ k x is the integral variable, which is x from R i Integrate to R o .

[0081] like Figure 3 (a) shown in which H sh2 With H sh1 are the heights of the inner and outer sides of the outer stator pole shoes, W sh is the length of the bevel of the outer stator pole shoe. Its equivalent magnetic resistance model is as follows: Figure 3As shown in (b), the inner and outer stator pole shoes can be regarded as a combination of trapezoidal reluctance and rectangular reluctance (pole shoe reluctance R sh ), where the trapezoidal magnetic resistance R3 along the magnetic flux direction can be expressed as:

[0082]

[0083] Among them, μ sh It represents the relative magnetic permeability of the motor stator pole shoe, W1 and W2 represent the length of the short base and long base of the trapezoid, and H represents the height of the trapezoid.

[0084] Therefore, the pole shoe reluctance R sh It can be expressed as:

[0085] R sh = rectangular reluctance + trapezoidal reluctance;

[0086]

[0087] Initially, μ sh =a; in subsequent iterations, μ sh =μ k .

[0088] The schematic diagram of the inner stator slot is as follows Figure 4 As shown, the inner stator slot is regarded as a trapezoidal magnetic resistance (the outer magnetic resistance of the inner stator slot R is1 、Inner layer magnetic resistance R is2 ), W iss1 , W iss2 , W iss are the short side, long side and average length of the trapezoid, H iss It is 1 / 2 of the height of the trapezoid. The magnetic resistance of the outer layer of the inner stator slot is R is1 The inner layer magnetic resistance R is2 Can be expressed as:

[0089]

[0090] The schematic diagram of the outer stator slot is as follows Figure 5 As shown, the outer stator slot is regarded as a rectangular magnetic resistance (the radial magnetic resistance of the outer stator slot R osv , tangential magnetic resistance R ost ), W oss Represents the length of the rectangle, H ot Indicates the width of the rectangle, H osh2 Indicates the inner height of the outer stator pole shoe, W oso Indicates the width of the outer stator slot. The radial magnetic resistance of the outer stator slot R osv and tangential magnetic resistance R ost Can be expressed as:

[0091]

[0092] The rotor modules, air gaps and stator slots of the motor are divided into a certain number of magnetic network mesh elements according to the required accuracy. Figure 6 As shown in the figure, the equivalent magnetic reluctance of the mesh element is regarded as a circular magnetic reluctance in the radial motor, and the radial magnetic reluctance R r and tangential magnetic resistance R t It can be expressed as:

[0093] The slot is the gap between adjacent stator pole shoes.

[0094]

[0095] For a motor component, m and n represent the number of grids in the radial and tangential directions, respectively, and r i , r o They represent the inner and outer diameters of the ring respectively, and α represents the angle swept by a motor component in the circumferential direction.

[0096] According to formula (5), Figure 7 As shown, the rotor, air gap and slot are divided into 360 nodes in the tangential direction and 1 node in the radial direction, and the non-magnetic material between adjacent rotors is divided into 2 nodes in the radial direction.

[0097] S3. According to the rotor positions corresponding to different moments, define the connection modes between the rotor and the inner air gap and the outer air gap respectively;

[0098] Based on the magnetic resistance and leakage magnetic resistance calculated by S2 and the connection methods corresponding to different rotor positions, the magnetic network model under different rotor positions is obtained. In this example, the schematic diagram of the complete magnetic network model is as follows: Figure 7 shown.

[0099] Among them, R ot With R it They are the outer stator tooth reluctance and the inner stator tooth reluctance respectively.

[0100] R ott With R itt They are the reluctance at the bottom of the outer stator teeth and the reluctance at the bottom of the inner stator teeth respectively.

[0101] R osv With R ost are the radial and tangential magnetic reluctances of the outer stator slots, respectively, which can be calculated according to formula (7). osv The equivalent magnetic resistance can be calculated according to formula (2).

[0102] R osy With R isy are the reluctance of the outer stator yoke and the inner stator yoke respectively. The equivalent reluctance of the reluctance circuit can be calculated according to formula (3).

[0103] R osh With R ish They are the magnetic resistance of the outer stator pole shoe and the inner stator pole shoe, and the equivalent magnetic resistance R of the magnetic resistance circuit sh It can be calculated according to formula (5).

[0104] R is1 With R is2 are the outer tangential magnetic resistance and inner tangential magnetic resistance of the inner stator slot respectively, which can be calculated according to formula (6).

[0105] R oso With R iso They represent the magnetic networks at the inner and outer stator slots, respectively, where the mesh elements are the same size as the inner and outer air gaps.

[0106] S4, based on the complete magnetic network model obtained in S3, the relative magnetic permeability μ k Perform nonlinear iterative calculations to obtain the final convergence result of the magnetic network model.

[0107] The steps of nonlinear iterative calculation include:

[0108] S41. Perform simulation calculations based on the complete magnetic network in MATLAB / Simulink to obtain the magnetic flux Φ of each branch (each excitation winding, each armature winding, the magnetic flux on the core, and the air gap / leakage magnetic resistance) (obtained by direct calculation by the software, the calculation method of the software is matrix solution), calculate the magnetic flux density B of each branch, and obtain the new relative permeability by looking up the μ-B curve table of common materials.

[0109] S42. Calculate the relative error between the current magnetic permeability and the magnetic permeability of the previous iteration. If the relative error is greater than the given error δ, update the relative magnetic permeability and continue to iterate (continue to execute steps S2-S4) until the relative error is less than δ, that is, the calculation result converges. At this time, record the current magnetic flux and magnetic flux density, and the calculation of the motor magnetic network iterative model is completed.

[0110] Among them, the iterative expression of relative magnetic permeability is:

[0111] μ k =k1μ k +k2μ k-1 (6)

[0112] In the formula, μ k and μ k-1 are the current relative magnetic permeability and the relative magnetic permeability of the previous iteration, respectively; k1 and k2 are the current relative magnetic permeability coefficient and the relative magnetic permeability coefficient after the previous iteration, k1=0.1, k2=0.9.

[0113] The relative error convergence judgment expression is:

[0114]

[0115] According to the established magnetic network model of the stator partitioned electro-excitation flux switching motor, the air gap flux density, phase winding flux linkage and the corresponding average electromagnetic torque of the motor under no-load and load conditions are calculated and compared with the finite element results.

[0116] like Figure 8 As shown in FIG. 1 , the radial and tangential magnetic flux density of the no-load inner and outer air gaps predicted by the present invention have high accuracy; Fig. 9 As shown, the no-load A-phase flux predicted by the present invention has a high accuracy; Fig.10 As shown, the radial and tangential magnetic flux density of the inner and outer air gaps of the load predicted by the present invention have high accuracy; Fig.11 As shown, the load A phase flux predicted by the present invention has a higher accuracy; Fig.12 As shown, the load average torque predicted by the present invention has higher accuracy.

[0117] The above is only a preferred embodiment of the present invention and does not limit the present invention in any way. Any technician in the relevant technical field, without departing from the scope of the technical solution of the present invention, makes any form of equivalent replacement or modification to the technical solution and technical content disclosed in the present invention, which does not depart from the content of the technical solution of the present invention and still falls within the protection scope of the present invention.

Claims

1. A magnetic network modeling method for a stator partitioned electric excitation flux switching motor, characterized in that: The following steps are involved: Step S1, modeling the motor components; wherein step S1 specifically includes: Step S11, defining the geometric parameters and material parameters of the inner stator, the outer stator and the rotor; and providing the electromagnetic characteristic curve of the material; Step S12, dividing and modeling the inner stator and the outer stator based on the flux tube model of the traditional magnetic circuit method; Step S13, dividing the magnetic grid elements of the rotor, air gap and slot according to the required magnetic network accuracy; Step S2, calculating magnetic resistance, leakage magnetic resistance, and magnetomotive force, wherein: The reluctance includes the reluctance of the inner stator, the outer stator, and the reluctance of the magnetic grid elements in two directions; The leakage reluctance includes the leakage reluctance of the inner stator slots, the outer stator slots, the slots and the non-magnetic materials of the rotor; The magnetomotive force includes the magnetomotive force of the field winding and the armature winding; In step S2, the equivalent magnetic resistance R1 of the stator teeth along the radial direction is expressed as: Where L represents the magnetic path length of the motor stator tooth in the direction of magnetic flux, μ0 represents the vacuum magnetic permeability, and μ t represents the relative magnetic permeability of the stator teeth of the motor, W represents the width of the stator teeth, and D represents the axial length of the motor; The equivalent magnetic resistance R2 of the stator yoke along the tangential direction is expressed as: Among them, μ y Represents the relative magnetic permeability of the motor stator yoke, R i , R o denote the inner and outer diameters of the ring, respectively; θ denotes the arc swept by the ring; x is the integral variable, which is the integral of x from R i Integrate to R o ; The trapezoidal magnetic resistance R3 of the stator pole shoes along the magnetic flux direction is expressed as: Among them, μ sh It represents the relative magnetic permeability of the motor stator pole shoe, W1 and W2 represent the length of the short and long bases of the trapezoid, and H represents the height of the trapezoid; In step S2, the radial magnetic resistance R r and tangential magnetic resistance R t It is expressed as: For a motor component, m and n represent the number of grids in the radial and tangential directions, respectively, and r i , r o They represent the inner and outer diameters of the ring, respectively, and α represents the angle swept by a motor component in the circumferential direction; Step S3, defining the connection modes between the rotor and the inner air gap and the outer air gap respectively according to the rotor positions corresponding to different moments; Based on the magnetic resistance and leakage magnetic resistance calculated in step S2 and the connection modes corresponding to different rotor positions, a magnetic network model under different rotor positions is obtained; Step S4, based on the complete magnetic network model obtained in S3, performing nonlinear iterative calculation on the relative magnetic permeability u to obtain a final convergence result of the magnetic network model; Step S4 specifically includes: S41, calculate according to the complete magnetic network, obtain the magnetic flux Φ of each branch, calculate the magnetic flux density B of each branch, and obtain a new relative magnetic permeability by looking up the μ-B curve of the material; S42. Calculate the relative error between the current magnetic permeability and the magnetic permeability of the previous iteration. If the relative error is greater than the given error δ, update the relative magnetic permeability and continue iterating until the relative error is less than δ, that is, the calculation result converges. At this time, record the current magnetic flux and magnetic flux density, and the calculation of the motor magnetic network iteration model is completed.

2. The magnetic network modeling method of the stator partitioned electric excitation flux switching motor according to claim 1 is characterized in that: In step S2, the magnetomotive force F of the excitation winding f And the three-phase armature winding magnetomotive force F a , F b , F c It is expressed as: Among them, N f Indicates the number of turns of the excitation winding, I f Indicates the magnitude of the excitation current; N c Indicates the number of turns of the three-phase armature winding coil, i a 、i b 、i c Respectively represent the instantaneous values ​​of the three-phase current.

3. A magnetic network modeling system for a stator partitioned electric excitation flux switching motor, using the magnetic network modeling method for a stator partitioned electric excitation flux switching motor described in claims 1-2, characterized in that: include: Parameter definition module: initialize the parameters of the equivalent magnetic network, give the initial magnetic permeability, and calculate the initial magnetic resistance of the stator and rotor cores; Calculate the magnetomotive force of each branch according to the excitation and winding parameters; Given the grid accuracy, calculate the grid reluctance of each component of the motor; Magnetic network model construction module: Based on the magnetic network model, the magnetic flux leakage in the stator slot and slot opening as well as the magnetic flux leakage of the rotor non-magnetic material are considered; the connection mode between the motor units is defined, and the complete magnetic network model under different rotor positions is obtained according to the different rotor positions corresponding to different times; And iterative calculation module: based on the complete magnetic network model, the magnetic permeability of the stator and rotor cores is calculated nonlinearly to obtain the final convergence result of the magnetic network.

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