Permanent magnet synchronous motor eccentric fault modeling method, device, equipment and medium

Abstract

The invention discloses a permanent magnet synchronous motor eccentric fault modeling method, device and equipment and a medium, and relates to the technical field of motor fault modeling, and the method comprises the following steps: inputting a mechanical angle of a permanent magnet synchronous motor into an improved air gap distribution function under an eccentric fault; obtaining an improved air gap distribution function and a reverse air gap distribution function under an eccentric fault; obtaining a self-inductance parameter, a mutual inductance parameter and an inductance matrix at the current moment according to the air gap distribution function and the reverse air gap distribution function under the eccentric fault; obtaining a stator current derivative based on the inductance matrix; and obtaining the stator current and the electromagnetic torque at the next moment, carrying out iteration on the obtaining process of the stator current based on the rotating speed and the mechanical angle of the motor at the next moment until the iteration is finished, and outputting a corresponding stator current waveform. The air gap distribution function and the inverse air gap distribution function at the permanent magnet are considered as functions related to the space angle, the space harmonic component is increased, and the accuracy of eccentricity fault judgment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of motor fault modeling, and in particular to a method, device, equipment and medium for modeling eccentricity faults of a permanent magnet synchronous motor. Background Art

[0002] Permanent magnet synchronous motors (PMSMs) offer advantages over conventional AC variable-frequency motors, such as high power density, high efficiency, high torque-to-inertia ratio, a wide range of constant power speed ratios, minimal vibration, and low noise. They have been widely used in various industrial and electric drive systems, often operating under variable speed and load conditions, such as in new energy vehicles, industrial robots, and high-speed rail power systems. Motors are crucial devices for converting electrical energy into mechanical energy in production and daily life. Therefore, faults must be detected and corrected promptly at the earliest possible stage to ensure reliable operation. However, due to factors such as production processes, manufacturing standards, and operating environments, permanent magnet synchronous motors can experience rotor eccentricity, leading to uneven air gaps, magnetic field distortion, vibration, noise, and motor heating, shortening the motor's service life. In severe cases, eccentricity can cause collisions between the stator and rotor, ultimately damaging the motor. Therefore, research on eccentricity fault diagnosis in permanent magnet synchronous motors is of great value and practical significance.

[0003] Eccentricity is a typical mechanical fault. It can be categorized into dynamic eccentricity, static eccentricity, and mixed eccentricity based on the eccentricity mechanism. Dynamic eccentricity occurs when the stator center coincides with the rotor's rotational center but not with the rotor's geometric center. Static eccentricity occurs when the stator center does not coincide with the rotor's rotational center, while the rotor's rotational center coincides with the rotor's geometric center. Mixed eccentricity occurs when the stator center does not coincide with either the rotor's rotational center or the rotor's geometric center.

[0004] Currently, diagnostic methods for eccentricity faults in permanent magnet synchronous motors fall into three main categories: vibration signal-based, magnetic induction intensity-based, and stator current-based. Vibration signal-based diagnostic methods are more sensitive to mechanical faults and, therefore, eccentricity faults. However, vibration sensors can be difficult to install, especially in compact environments. Furthermore, the vibration excitation source must travel a long path to reach the sensor, resulting in the inclusion of noise and coupled vibration information from other components in the vibration signal, further complicating the signal. These factors limit the wider industrial application of vibration signals. Magnetic induction intensity-based diagnostic methods can monitor magnetic field distortion and thus diagnose eccentricity faults. However, installing the magnetic induction sensor inside the motor requires disassembly, which is not only complex but also impacts motor performance. If installed externally, the motor housing often creates electrostatic shielding, affecting the accuracy of the magnetic field signal.

[0005] Stator current-based diagnostic methods eliminate the need for additional sensors inside or outside the motor. Motor eccentricity faults can be diagnosed by relying on the stator current characteristic frequency. However, the relationship between the characteristic frequency and the motor eccentricity pattern and degree remains to be determined, necessitating modeling and analysis of the motor system. Currently, eccentricity fault modeling methods for permanent magnet synchronous motors primarily include the finite element method (FEM), the equivalent magnetic circuit method (EMC), and the improved winding function method (IMF). The FEM is computationally intensive and affected by meshing accuracy; the EMC utilizes lumped parameter modeling, which is still computationally intensive; and the improved winding function method (IMF) offers a lower computational cost and provides an analytical expression for the motor inductance.

[0006] In practice, the air gap length at the permanent magnets of a permanent magnet synchronous motor is related to the rotor's spatial angle, which introduces harmonic components into the inductance calculation. However, the existing improved winding function method simplifies the air gap length at the permanent magnets to a constant value during modeling, ignoring the spatial harmonic components. This results in the stator current characteristic frequency missing some fault characteristic frequencies, making it impossible to accurately determine various types of eccentricity faults. Summary of the Invention

[0007] Based on the defects of the above-mentioned prior art, the present invention provides a method, device, equipment and medium for modeling the eccentricity fault of a permanent magnet synchronous motor, which solves the problem that the existing improved winding function method simplifies the air gap length at the permanent magnet to a constant value in modeling, ignores the spatial harmonic components, causes some fault characteristic frequencies to be missing in the stator current characteristic frequency, and cannot accurately judge various types of eccentricity faults.

[0008] The present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for modeling an eccentricity fault of a permanent magnet synchronous motor, comprising the following steps: The mechanical angle of the permanent magnet synchronous motor at the current moment is input into the improved air gap distribution function under the eccentricity fault, thereby obtaining the improved air gap distribution function and the inverse air gap distribution function under the eccentricity fault at the current moment; wherein, the spatial angle and the mechanical angle are introduced into the original air gap distribution function to obtain the improved air gap distribution function; Based on the improved winding function method, the current self-inductance and mutual inductance parameters are obtained according to the improved air gap distribution function and the inverted air gap distribution function under the eccentric fault at the current moment. The current self-inductance and mutual inductance parameters are combined to obtain the inductance matrix at the current moment. The inductance matrix and motor speed at the current moment are input into the voltage equation and the flux equation to obtain the stator current derivative at the current moment; the stator current and electromagnetic torque of the permanent magnet synchronous motor at the next moment are obtained based on the stator current derivative at the current moment, and the stator current and electromagnetic torque at the next moment are input into the dynamic equation to obtain the mechanical angle and motor speed at the next moment; The stator current acquisition process is iterated based on the mechanical angle and motor speed at the next moment until the iteration is completed, and the stator current waveform corresponding to the permanent magnet synchronous motor is output.

[0009] Preferably, the improved air gap distribution function is specifically as follows: ; Where, To improve the air gap distribution function, is the spatial angle, is the polar angle, is the shortest distance from the rotor center to the inner side of the permanent magnet, is the length of the permanent magnet, is the air gap length in normal state, It is the mechanical angle.

[0010] Preferably, the static eccentricity and the dynamic eccentricity are set, and the static eccentricity and the dynamic eccentricity are input into the improved air gap distribution function to obtain the improved air gap distribution function under the eccentricity fault, which is specifically shown as follows: ; ; in, ; ; Where, and are the improved air gap distribution function and the inverted air gap distribution function under eccentric fault, is the static eccentricity, is the dynamic eccentricity, To improve the inverse air gap distribution function, is the mechanical position angle at the minimum air gap, is the mechanical position angle that rotates with the rotor, is the eccentricity.

[0011] Preferably, the self-inductance parameter and the mutual inductance parameter are specifically as follows: Where, is the self-inductance parameter of phase A, is the self-inductance parameter of phase B, is the self-inductance parameter of phase C, and is the mutual inductance parameter of phase A and phase B, and is the mutual inductance parameter of phase C and phase A, and is the mutual inductance parameter of phase B and phase C, is the A-phase winding function, is the B-phase winding function, is the C-phase winding function, is an intermediate variable.

[0012] Preferably, the inductance matrix is ​​specifically as follows: ; Where, is the inductance matrix.

[0013] Preferably, the step of obtaining the stator current and electromagnetic torque of the permanent magnet synchronous motor at the next moment based on the stator current derivative at the current moment comprises the following steps: The implicit Euler method is used to update the stator current at the next moment, as shown below: ; Where, for The stator current at time for The stator current at time is the stator current derivative, is the time step; The stator current at the next moment is input into the electromagnetic torque equation to obtain the electromagnetic torque.

[0014] Preferably, the dynamic equation is specifically as follows: ; Where, for The mechanical angular velocity at the moment, that is, the motor speed, for The mechanical angle of the moment, for The mechanical angular velocity at the moment, for The mechanical angle of the moment, is the damping coefficient, is the moment of inertia, is the electromagnetic torque, is the load torque.

[0015] In a second aspect, the present invention provides a permanent magnet synchronous motor eccentricity fault modeling device, comprising: An input module is used to input the mechanical angle of the permanent magnet synchronous motor at the current moment into the improved air gap distribution function under the eccentricity fault, thereby obtaining the improved air gap distribution function and the inverse air gap distribution function under the eccentricity fault at the current moment; wherein the spatial angle and the mechanical angle are introduced into the original air gap distribution function to obtain the improved air gap distribution function; A first calculation module is configured to obtain the current self-inductance parameter and mutual inductance parameter based on the improved winding function method and the improved air gap distribution function and the inverted air gap distribution function under the eccentric fault at the current moment; and combine the current self-inductance parameter and the mutual inductance parameter to obtain the current inductance matrix; The second calculation module is used to input the inductance matrix and motor speed at the current moment into the voltage equation and the flux equation to obtain the stator current derivative at the current moment; based on the stator current derivative at the current moment, the stator current and electromagnetic torque of the permanent magnet synchronous motor at the next moment are obtained, and the stator current and electromagnetic torque at the next moment are input into the dynamic equation to obtain the mechanical angle and motor speed at the next moment; The iteration module is used to iterate the stator current acquisition process based on the mechanical angle and motor speed at the next moment until the iteration is completed, and output the stator current waveform corresponding to the permanent magnet synchronous motor.

[0016] In a third aspect, the present invention provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned permanent magnet synchronous motor eccentricity fault modeling method when executing the program.

[0017] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned permanent magnet synchronous motor eccentricity fault modeling method is implemented.

[0018] Compared with the prior art, the at least one technical solution adopted by the present invention can achieve the following beneficial effects: The present invention first introduces the spatial angle and mechanical angle into the original air gap distribution function, resulting in an improved air gap distribution function that considers the true distribution of the air gap. The air gap distribution function and the inverse air gap distribution function at the permanent magnet are considered as functions related to the spatial angle, thereby increasing the spatial harmonic component. The current mechanical angle of the permanent magnet synchronous motor is then input into the improved air gap distribution function under an eccentricity fault, resulting in an improved air gap distribution function and an inverse air gap distribution function under the current eccentricity fault. An inductance matrix is ​​then obtained using an improved winding function method. State parameters such as current, speed, electromagnetic torque, and mechanical angle are updated at different times using motor voltage, flux linkage, electromagnetic torque, and dynamic equations, ultimately resulting in a stator current waveform that considers the spatial harmonic component. The present invention considers the air gap distribution function and the inverse air gap distribution function at the permanent magnet as functions related to the spatial angle, thereby increasing the spatial harmonic component, improving the output stator current waveform, and enhancing the accuracy of eccentricity fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 This is a flow chart of a method for modeling eccentricity faults of a permanent magnet synchronous motor according to the present invention; Figure 2 This is a current spectrum diagram of the motor at a speed of 605 rpm under experimental conditions of an embodiment of the present invention; Figure 3 This is a current spectrum diagram of the motor at a speed of 605 rpm under simulation conditions of an embodiment of the present invention without considering the actual internal shape of the motor; Figure 4 This is a current spectrum diagram of the motor at a speed of 605 rpm under the simulation conditions of an embodiment of the present invention, taking into account the actual internal shape of the motor; Figure 5 This is a current spectrum diagram of the motor at a speed of 908 rpm under experimental conditions of an embodiment of the present invention; Figure 6 This is a current spectrum diagram of the motor at a speed of 908 rpm under simulation conditions of an embodiment of the present invention without considering the actual internal shape of the motor; Figure 7 This is a current spectrum diagram of the motor at a speed of 908 rpm considering the actual internal shape of the motor under the simulation conditions of an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0022] To overcome the shortcomings of the prior art, the present invention aims to provide a method for simulating eccentricity faults in permanent magnet synchronous motors that considers the actual air gap distribution. This method utilizes the actual internal geometry of the motor, considers the air gap distribution function and the inverse air gap distribution function at the permanent magnet as functions of spatial angle, and then calculates the inductance matrix using an improved winding function method. This inductance matrix is ​​then incorporated into the four fundamental motor equations. By constructing a simulation model, the stator current waveform is obtained.

[0023] Reference Figure 1 The present invention provides a method for modeling eccentricity fault of a permanent magnet synchronous motor, comprising the following steps: S1: Set simulation time , thereby determining the start and end time of the simulation and initializing the static eccentricity and dynamic eccentricity ; Get the inner diameter of the motor stator , permanent magnet pole pairs and stator resistance and other parameters.

[0024] S2: Introducing the spatial angle and mechanical angle into the original air gap distribution function to obtain an improved air gap distribution function.

[0025] The air gap distribution function is a function that describes the distribution law of the air gap length between the stator and rotor of the motor along the spatial angle of the rotor.

[0026] The original air gap distribution function and the inverse air gap distribution function without considering the true internal shape are as follows: ; ; Where, is the spatial angle, is the polar angle, is the shortest distance from the rotor center to the inner side of the permanent magnet, is the length of the permanent magnet, is the air gap length in normal state, From the above formula, we can see that the air gap length at the permanent magnet is a constant, and the space harmonic components are ignored.

[0027] The present invention considers the actual shape of the rotor inside the motor and considers the air gap distribution function and the inverse air gap distribution function at the permanent magnet as functions related to the spatial angle, thereby obtaining the improved air gap distribution function and the inverse air gap distribution function. Taking into account the spatial harmonic components, the air gap distribution function of the normal motor is calculated. g and the inverse air gap distribution function , as shown below:

[0028] S3: Setting the static eccentricity and the dynamic eccentricity, inputting the static eccentricity and the dynamic eccentricity into the improved air gap distribution function, and obtaining the improved air gap distribution function under the eccentricity fault.

[0029] Calculation of the improved air gap distribution function between the stator and rotor under eccentric fault and improved inverse air gap distribution function , as follows: Where, is the static eccentricity in S1, is the dynamic eccentricity in S1, is the inverse air gap distribution function of a normal motor, is the mechanical angle, is the mechanical position angle at the minimum air gap, is the mechanical position angle that rotates with the rotor, is the eccentricity.

[0030] The mechanical angle of the permanent magnet synchronous motor at the current moment is obtained, and the mechanical angle of the permanent magnet synchronous motor at the current moment is input into the improved air gap distribution function under the eccentricity fault, so as to obtain the improved air gap distribution function and the inverse air gap distribution function under the eccentricity fault at the current moment.

[0031] Based on the actual internal geometric structure of the permanent magnet synchronous motor, the air gap distribution function and inverse air gap distribution function waveforms of the normal motor and the eccentricity fault motor are calculated. This can improve the accuracy of modeling, more realistically reflect the air gap changes caused by the eccentricity fault, and more accurately calculate the self-inductance and mutual inductance.

[0032] S4: Calculate winding function ,for For the pole-distributed winding, the winding function expression is as follows: Where, y for a or b or c , a, b and c are phase A, phase B and phase C respectively, is the A-phase winding function, is the B-phase winding function, is the C-phase winding function, is the equivalent number of turns of the stator phase winding, is the angle corresponding to the stator slot.

[0033] S5: Calculate self-inductance parameters based on the improved winding function method and mutual inductance parameters , we get the inductance matrix , as follows: Where, is the self-inductance parameter of phase A, is the self-inductance parameter of phase B, is the self-inductance parameter of phase C, and is the mutual inductance parameter of phase A and phase B, and is the mutual inductance parameter of phase C and phase A, and is the mutual inductance parameter of phase B and phase C.

[0034] The self-inductance part is: The mutual inductance part is: Where, is an intermediate variable, , is the magnetic permeability of air, is the average air gap length, is the effective length of the core.

[0035] By improving the winding function method, the self-inductance and mutual inductance at each moment can be calculated as the mechanical angle The changing relationship between the air gap distribution function and the inverse air gap distribution function between the stator and rotor further refines the inductance parameters and provides support for the inductance parameters in the four basic equations of the subsequent motor.

[0036] S6: Calculate the stator current derivative based on the motor voltage equation and flux equation.

[0037] ; ; Where, is the three-phase voltage, , is the resistance input in step S1, is the stator current, is the stator three-phase winding flux, Permanent magnet flux matrix, is the permanent magnet flux amplitude, T is the transposition character.

[0038] Get the current motor speed, input the current inductance matrix and motor speed into the voltage equation and flux equation, and get the current stator current derivative, as shown below: Where, , is the resistance input in step S1, is the stator current, is the three-phase voltage, is the permanent magnet flux, is the mechanical angular velocity (rotational speed).

[0039] According to the voltage equation and magnetic flux equation of the motor, the derivative of the current can be obtained, which provides support for the subsequent calculation of the stator current at the next moment.

[0040] S6: Use implicit Euler method to update the stator current at the next moment The electromagnetic torque is calculated by the electromagnetic torque equation Size, as follows: Where, is the current at the next moment, is the current at the current moment, is the time step.

[0041] The implicit Euler method is used to update the current according to the current derivative calculated in step S5, and then the electromagnetic torque is calculated to provide support for the subsequent calculation of the mechanical speed and mechanical angle.

[0042] S7: Use implicit Euler method to update the motor mechanical angular velocity at the next moment Mechanical angle at the next moment , until the simulation time in step 1 is reached , as follows: Where, is the damping coefficient, is the moment of inertia, is the electromagnetic torque in step 6, is the load torque.

[0043] Step 8: Output the stator current waveform.

[0044] Example The effectiveness of the present invention is verified by taking the eccentricity experimental data of the MDMF152L1H6M permanent magnet synchronous motor as an example. The simulation scheme uses Simulink software to establish a dual closed-loop control permanent magnet synchronous motor simulation model. Among them, the motor module is based on the four basic equations of the motor, and adopts an inductance calculation method derived based on the real internal structure of the motor to replace the inductance term in the motor equation. Two groups of experiments were conducted, respectively, collecting current signals at speeds of 605rpm and 908rpm, and performing Fourier transform to verify the effectiveness of the simulation model; four groups of simulations were conducted, respectively, comparing the consideration of the real internal shape of the motor and the non-consideration of the real internal shape of the motor at speeds of 605rpm and 908rpm, and performing Fourier transform to verify the superiority of the simulation model in considering the real internal shape of the motor.

[0045] according to Figure 2-Figure 4 It can be seen that when the speed is 605rpm, the fault characteristic frequency in the current spectrum when the internal shape of the motor is considered is significantly higher than when it is not considered, and is more consistent with the experimental current fault characteristic spectrum. Figure 5-Figure 7 It can be seen that when the speed is 908 rpm, the fault characteristic frequency in the current spectrum when the internal shape of the motor is considered is significantly higher than when it is not considered, and is more consistent with the experimental current fault characteristic spectrum. Figure 2-Figure 7 In the figure, X is the horizontal coordinate and Y is the vertical coordinate.

[0046] Based on the same concept, the present invention also provides a permanent magnet synchronous motor eccentricity fault modeling device, which includes an input module, a first calculation module, a second calculation module and an iteration module.

[0047] The input module is used to input the mechanical angle of the permanent magnet synchronous motor at the current moment into the improved air gap distribution function under the eccentricity fault, and obtain the improved air gap distribution function and the inverse air gap distribution function under the eccentricity fault at the current moment; wherein, the spatial angle and the mechanical angle are introduced into the original air gap distribution function to obtain the improved air gap distribution function.

[0048] The first calculation module is used to obtain the self-inductance parameter and mutual inductance parameter at the current moment based on the improved winding function method and the improved air gap distribution function and the inverted air gap distribution function under the eccentric fault at the current moment; the self-inductance parameter and the mutual inductance parameter at the current moment are combined to obtain the inductance matrix at the current moment.

[0049] The second calculation module is used to input the inductance matrix and motor speed at the current moment into the voltage equation and magnetic flux equation to obtain the stator current derivative at the current moment; based on the stator current derivative at the current moment, the stator current and electromagnetic torque of the permanent magnet synchronous motor at the next moment are obtained, and the stator current and electromagnetic torque at the next moment are input into the dynamic equation to obtain the mechanical angle and motor speed at the next moment.

[0050] The iteration module is used to iterate the stator current acquisition process based on the mechanical angle and motor speed at the next moment until the iteration is completed, and output the stator current waveform corresponding to the permanent magnet synchronous motor.

[0051] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned permanent magnet synchronous motor eccentricity fault modeling method is implemented.

[0052] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned permanent magnet synchronous motor eccentricity fault modeling method is implemented.

[0053] This paper proposes a permanent magnet synchronous motor eccentricity fault simulation model that considers the actual air gap distribution. First, basic parameters such as motor geometry and resistance are input, and dynamic and static eccentricity are set as initial conditions. Secondly, the actual motor shape is considered, and the air gap distribution function and the inverse air gap distribution function at the permanent magnet are considered as functions related to the spatial angle. By introducing the eccentricity factor, the air gap distribution function and the inverse air gap distribution function under eccentricity are solved. The winding function is then derived based on the three-phase winding distribution. Then, the inductance matrix is ​​obtained using an improved winding function method. State parameters such as current, speed, torque, and mechanical angle are updated using the motor voltage, flux linkage, electromagnetic torque, and dynamic equations. The output stator current is then Fourier transformed. This method provides theoretical support for modeling motors under eccentricity, enabling subsequent eccentricity fault analysis.

[0054] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0055] Obviously, those skilled in the art may make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if such modifications and variations fall within the scope of the claims and their equivalents, the present invention is intended to include such modifications and variations.

Claims

1. A method for modeling eccentricity fault of a permanent magnet synchronous motor, characterized in that: The following steps are involved: The mechanical angle of the permanent magnet synchronous motor at the current moment is input into the improved air gap distribution function under the eccentricity fault, thereby obtaining the improved air gap distribution function and the inverse air gap distribution function under the eccentricity fault at the current moment; wherein, the spatial angle and the mechanical angle are introduced into the original air gap distribution function to obtain the improved air gap distribution function; Based on the improved winding function method, the current self-inductance and mutual inductance parameters are obtained according to the improved air gap distribution function and the inverted air gap distribution function under the eccentric fault at the current moment. The current self-inductance and mutual inductance parameters are combined to obtain the inductance matrix at the current moment. The inductance matrix and motor speed at the current moment are input into the voltage equation and the flux equation to obtain the stator current derivative at the current moment; the stator current and electromagnetic torque of the permanent magnet synchronous motor at the next moment are obtained based on the stator current derivative at the current moment, and the stator current and electromagnetic torque at the next moment are input into the dynamic equation to obtain the mechanical angle and motor speed at the next moment; The stator current acquisition process is iterated based on the mechanical angle and motor speed at the next moment until the iteration is completed, and the stator current waveform corresponding to the permanent magnet synchronous motor is output.

2. A permanent magnet synchronous motor eccentricity fault modeling method according to claim 1, characterized in that: The improved air gap distribution function is specifically as follows: ； Where, To improve the air gap distribution function, is the spatial angle, is the polar angle, is the shortest distance from the rotor center to the inner side of the permanent magnet, is the length of the permanent magnet, is the air gap length in normal state, It is the mechanical angle.

3. A permanent magnet synchronous motor eccentricity fault modeling method according to claim 2, characterized in that: The static eccentricity and dynamic eccentricity are set, and the static eccentricity and dynamic eccentricity are input into the improved air gap distribution function to obtain the improved air gap distribution function under eccentricity fault, which is shown as follows: ； ； in, ； ； Where, and are the improved air gap distribution function and the inverted air gap distribution function under eccentric fault, is the static eccentricity, is the dynamic eccentricity, To improve the inverse air gap distribution function, is the mechanical position angle at the minimum air gap, is the mechanical position angle that rotates with the rotor, is the eccentricity.

4. A permanent magnet synchronous motor eccentricity fault modeling method according to claim 3, characterized in that: The self-inductance parameters and mutual inductance parameters are specifically as follows: Where, is the self-inductance parameter of phase A, is the self-inductance parameter of phase B, is the self-inductance parameter of phase C, and is the mutual inductance parameter of phase A and phase B, and is the mutual inductance parameter of phase C and phase A, and is the mutual inductance parameter of phase B and phase C, is the A-phase winding function, is the B-phase winding function, is the C-phase winding function, is an intermediate variable.

5. A permanent magnet synchronous motor eccentricity fault modeling method according to claim 4, characterized in that: The inductance matrix is ​​specifically shown as follows: ； Where, is the inductance matrix.

6. A permanent magnet synchronous motor eccentricity fault modeling method according to claim 5, characterized in that: The step of obtaining the stator current and electromagnetic torque of the permanent magnet synchronous motor at the next moment based on the stator current derivative at the current moment includes the following steps: The implicit Euler method is used to update the stator current at the next moment, as shown below: ； Where, for The stator current at time for The stator current at time is the stator current derivative, is the time step; The stator current at the next moment is input into the electromagnetic torque equation to obtain the electromagnetic torque.

7. A permanent magnet synchronous motor eccentricity fault modeling method according to claim 6, characterized in that: The dynamic equation is specifically as follows: ； Where, for The mechanical angular velocity at the moment, that is, the motor speed, for The mechanical angle of the moment, for The mechanical angular velocity at the moment, for The mechanical angle of the moment, is the damping coefficient, is the moment of inertia, is the electromagnetic torque, is the load torque.

8. A permanent magnet synchronous motor eccentricity fault modeling device, characterized in that: include: An input module is used to input the mechanical angle of the permanent magnet synchronous motor at the current moment into the improved air gap distribution function under the eccentricity fault, thereby obtaining the improved air gap distribution function and the inverse air gap distribution function under the eccentricity fault at the current moment; wherein the spatial angle and the mechanical angle are introduced into the original air gap distribution function to obtain the improved air gap distribution function; A first calculation module is configured to obtain the current self-inductance parameter and mutual inductance parameter based on the improved winding function method and the improved air gap distribution function and the inverted air gap distribution function under the eccentric fault at the current moment; and combine the current self-inductance parameter and the mutual inductance parameter to obtain the current inductance matrix; The second calculation module is used to input the inductance matrix and motor speed at the current moment into the voltage equation and the flux equation to obtain the stator current derivative at the current moment; based on the stator current derivative at the current moment, the stator current and electromagnetic torque of the permanent magnet synchronous motor at the next moment are obtained, and the stator current and electromagnetic torque at the next moment are input into the dynamic equation to obtain the mechanical angle and motor speed at the next moment; The iteration module is used to iterate the stator current acquisition process based on the mechanical angle and motor speed at the next moment until the iteration is completed, and output the stator current waveform corresponding to the permanent magnet synchronous motor.

9. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for modeling the eccentricity fault of a permanent magnet synchronous motor as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by the processor, the method for modeling the eccentricity fault of the permanent magnet synchronous motor according to any one of claims 1 to 7 is implemented.

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