Permanent magnet synchronous motor demagnetization fault modeling method and system

Abstract

The application relates to the technical field of permanent magnet synchronous motor modeling, and discloses a permanent magnet synchronous motor demagnetization fault modeling method and system. The method uses finite element simulation to assist in constructing a total parameter model of a permanent magnet synchronous motor under a demagnetization fault, and solves the problem that a demagnetization fault modeling method cannot simultaneously meet the requirements of high precision and short calculation time. By using the method, the real-time performance of a demagnetization fault model under a permanent magnet synchronous motor control system can be improved, and the problem of a motor traction system under a simulated and simulated real demagnetization fault is solved.

Description

Technical Field

[0001] This invention relates to the field of permanent magnet synchronous motor modeling technology, and in particular to a method and system for modeling demagnetization faults in permanent magnet synchronous motors. Background Technology

[0002] The core component of a permanent magnet traction system is the permanent magnet synchronous motor, which is the actuator of the traction system. Due to its long-term operation in a confined space with poor heat dissipation and continuous vibration, it is one of the most frequent sources of failure in rail vehicles. In particular, compared with the asynchronous traction motors used in previous generations of rail vehicles, permanent magnet motors have a unique risk of demagnetization, which poses a potential threat to the operational safety of the entire vehicle. For permanent magnet materials, their stability is challenged by a combination of factors such as temperature, external magnetic fields, acid and alkali corrosion, manufacturing defects, and natural lifespan. The magnetic induction intensity is prone to amplitude reduction or distortion, resulting in uniform or non-uniform demagnetization failures. Specifically, when the motor is overloaded or the heat dissipation system cannot meet requirements, the operating temperature of the permanent magnet will increase significantly, thereby increasing the activity of internal magnetic domains and affecting its magnetization ability. On the other hand, rare earth permanent magnet materials contain a large number of metallic elements. The metallic structure of these elements is easily affected by the external environment, leading to corrosion or oxidation and resulting in localized demagnetization. When a permanent magnet traction motor experiences a demagnetization fault, the motor's operating current increases to meet the torque requirements of the traction drive system. However, the increased current will increase motor losses and cause the internal temperature of the motor to rise. In addition, local demagnetization faults can not only cause this problem, but also disrupt the symmetry of the motor, increasing unbalanced magnetic pull and vibration. Therefore, if it is not diagnosed and treated in time, the permanent magnet demagnetization fault will continue to worsen, increasing the risk of stator-rotor contact. In severe cases, it can lead to the forced shutdown of the permanent magnet motor during traction, causing traffic accidents.

[0003] Currently, demagnetization fault modeling methods for permanent magnet synchronous motors are mainly divided into finite numerical simulation methods and analytical methods. However, existing modeling methods cannot simultaneously meet the requirements of high accuracy and short computation time. In addition, existing composite methods based on lumped parameter models usually ignore the magnetic saturation effect of the motor, while the equivalent inductance of the winding is affected by magnetic saturation. Therefore, the motor model established by ignoring the magnetic saturation effect has relatively low accuracy, which will affect the accuracy of fault diagnosis and optimized control algorithms. Summary of the Invention

[0004] This invention provides a method and system for modeling demagnetization faults in permanent magnet synchronous motors, in order to solve the problem of low accuracy in existing fault diagnosis.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] In a first aspect, the present invention provides a method for modeling demagnetization faults in a permanent magnet synchronous motor, comprising: S1: Construct a finite element model of a permanent magnet synchronous motor under demagnetization fault; S2: Based on the calculation results of the finite element model, establish a dataset of key inductance parameters and key flux linkage parameters for permanent magnet synchronous motors under different operating conditions. S3: Construct the lumped parameter function of the permanent magnet synchronous motor under demagnetization fault based on the inductance key parameter dataset and the flux linkage key parameter dataset; S4: Construct a total parameter model for the permanent magnet synchronous motor under demagnetization fault based on the lumped parameter function of the motor.

[0007] Secondly, this application provides a demagnetization fault modeling system for permanent magnet synchronous motors, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method described in the first aspect above.

[0008] Beneficial effects: The demagnetization fault modeling method for permanent magnet synchronous motors provided by this invention utilizes finite element simulation to assist in constructing a total parameter model of the permanent magnet synchronous motor under demagnetization faults. This solves the problem of simultaneously meeting the requirements of high accuracy and short computation time in demagnetization fault modeling methods. Using this method, the real-time performance of the demagnetization fault model under the permanent magnet synchronous motor control system can be improved, breaking through the problem of simulating the motor traction system under real demagnetization faults. Attached Figure Description

[0009] Figure 1 This is a structural diagram of the permanent magnet synchronous motor body according to an embodiment of the present invention; Figure 2 This is a flowchart of a method for modeling demagnetization faults in a permanent magnet synchronous motor according to an embodiment of the present invention; Figure 3 This is a schematic diagram of key parameter data of a motor with local demagnetization fault under different operating conditions according to an embodiment of the present invention; Figure 4 This invention relates to a permanent magnet synchronous motor under a local demagnetization fault. dq Block diagram of axis lumped parameter model; Figure 5 The permanent magnet synchronous motor in this embodiment of the invention is based on i d The rated operating condition under the model predictive control strategy with =0 ( i e = Simulation results for 32A). Detailed Implementation

[0010] The technical solution of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0011] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms "an" or "a" and similar terms do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms "connected" or "linked" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," "right," etc., are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship also changes accordingly.

[0012] Specifically, this application refers to the structure of a certain type of embedded permanent magnet synchronous motor, and the schematic diagram of the permanent magnet synchronous motor body structure is shown below. Figure 1 As shown, its control uses a method based on i d The predictive control strategy is based on a model with a value of 0. This embodiment will use finite element simulation-assisted modeling of demagnetization faults in a permanent magnet synchronous motor as an example for illustration.

[0013] In this embodiment, the calibration parameters of a certain type of permanent magnet synchronous motor are shown in Table 1.

[0014] Table 1 Parameters of Permanent Magnet Synchronous Motor

[0015] Please see Figure 2 This application provides a method for modeling demagnetization faults in permanent magnet synchronous motors, comprising: S1: Construct a finite element model of a permanent magnet synchronous motor under demagnetization fault; S2: Based on the calculation results of the finite element model, establish datasets of key inductance parameters and key flux linkage parameters of permanent magnet synchronous motors under different working conditions; S3: Construct the lumped parameter function of the permanent magnet synchronous motor under demagnetization fault based on the inductance key parameter dataset and the flux linkage key parameter dataset; S4: Construct a total parameter model for a permanent magnet synchronous motor under demagnetization fault based on the lumped parameter function of the motor.

[0016] It should be understood that the permanent magnet synchronous motor demagnetization fault modeling method provided in this application can be applied to permanent magnet synchronous motor demagnetization fault detection scenarios to realize the detection of permanent magnet synchronous motor demagnetization faults. In other words, it can determine whether a fault exists and the specific fault type based on the total parameter model.

[0017] The aforementioned modeling method for demagnetization faults in permanent magnet synchronous motors utilizes finite element simulation to assist in constructing a total parameter model of the permanent magnet synchronous motor under demagnetization faults. This method solves the problem of simultaneously meeting the requirements of high accuracy and short computation time in demagnetization fault modeling methods. By using this method, the real-time performance of the demagnetization fault model under the permanent magnet synchronous motor control system can be improved, overcoming the challenge of simulating the motor traction system under real demagnetization faults.

[0018] In this embodiment, as Figure 1 As shown, the demagnetization fault of the permanent magnet synchronous motor is a localized demagnetization fault of 50% in a single permanent magnet (mag0). The following steps are all discussions under this localized demagnetization fault. In addition, the method provided in this application can also be applied to other types of demagnetization fault modeling methods for permanent magnet synchronous motors. This is only an example and is not intended to limit the application.

[0019] Based on the structural parameters of the permanent magnet synchronous motor body, as well as the degree and location of local demagnetization faults, the original geometric model of the permanent magnet synchronous motor body is constructed using finite element software (Maxwell 16.0 in this example). The motor geometric model is then simplified according to the electromagnetic simulation requirements to determine the initial angle of the motor rotor.

[0020] In this example, the permanent magnet synchronous motor body is as follows: Figure 1 As shown, the motor rotor d The angle between the axis direction and the axis direction of the stator A-phase winding is 5 degrees, and the initial angle of the motor rotor is set to 5 degrees.

[0021] Define the materials involved in the design of permanent magnet synchronous motor components and allocate them according to actual conditions. Modify the material of the faulty permanent magnet according to the fault type to be simulated, and set and add simulation boundary conditions.

[0022] To reduce modeling complexity, the effect of temperature on the electromagnetic properties of permanent magnets is ignored. Therefore, the magnetic flux density of the permanent magnet is... B for:

[0023] In the formula, μ 0 represents the permeability in vacuum, with a value of 4π × 10⁻⁶. -7 H / m, μ r The relative permeability of a permanent magnet. H c For the coercivity of permanent magnets, Br The remanent magnetic flux density of the permanent magnet is expressed in tons (T). This example demonstrates how to change the coercivity. H c and residual magnetic induction B r The size of the magnet is used to simulate the demagnetization fault of the permanent magnet, a motor fault model is established, and finite element analysis is performed.

[0024] Furthermore, a corresponding motor model simulation mesh was designed, and a finite element model of the permanent magnet synchronous motor under demagnetization fault was constructed. Execute the Maxwell 2D / Mesh Operations / Assign / On selection command to configure the meshing settings: Set Length_Mag=3.50mm to be assigned to the permanent magnet area; Set Length_Coil=2.85mm to be allocated to the stator winding area; Set Length_Core=5.00mm to be assigned to the stator and rotor core area; Set Length_In=5.00mm and assign it to the inner layer area; It should be noted that in this embodiment, the simulation time is 0.01s, and the simulation step size is 1e-5s; in this example, the permanent magnet material is neodymium iron boron, specifically NdFe33. μ r It is 1.24. B r It is 1.1258T. H c It is 721601A / m.

[0025] Furthermore, such as Figure 3 As shown, 9 (Z=8) motor operating conditions (stator current amplitude) were set, and the key parameters of inductance and flux linkage of the permanent magnet synchronous motor under each operating condition were calculated by simulation using the established finite element model.

[0026] exist i d Under the =0 control algorithm, the operating condition set of the permanent magnet synchronous motor Z=0,1,... is collected. z ,..., Z Effective value of stator phase current of lower motor i e Construct a dataset of effective values ​​of stator phase currents I Z : ; In the formula, i ez For the first z The effective value of the stator phase current of the motor under each operating condition.

[0027] In the finite element simulation software, the operating condition set Z is set for the three-phase current excitation source set I of the permanent magnet synchronous motor stator A, B, and C under the finite element simulation model of the motor. aZ I bZ I cZ The expression is as follows: ; ; In the formula, i az , i bz , i cz The first z The three-phase current values ​​of motor stator A, B, and C under each operating condition. For the mechanical angle of the motor rotor, p This represents the number of pole pairs of the motor. By setting the simulation time and step size, and using Maxwell finite element simulation software, the motor inductance under the permanent magnet synchronous motor operating condition set Z is obtained. and magnetic chain Dataset: ; ; ; ; In the formula, L ABCz For the first z Three-phase inductor matrix of motor under various operating conditions L AAz ( ), L BBz ( ), L CCz ( ) are respectively the first z The self-inductance of the motor's three-phase windings A, B, and C under various operating conditions M ABz ( ), M BAz ( ), M ACz ( ), M CAz ( ), M BCz ( ), MBCz ( ) represent the mutual inductance between the phase windings of the motor, Ψ ABCz For the first z Three-phase flux linkage matrix of motor under various operating conditions ( ), ( ), The first z The three-phase flux linkages of the motor (A, B, and C) under various operating conditions.

[0028] Based on the dataset of key parameters such as inductance and flux linkage of permanent magnet synchronous motors under different operating conditions, a polynomial function fitting method is used to construct the key parameter function F of the permanent magnet synchronous motor under local demagnetization fault of the permanent magnet. Z : The motor inductance parameter L under demagnetization fault Z ( The data is obtained through motor coordinate transformation. dq The motor inductance parameters under the shaft are expressed as follows: ; ; ; ; In the formula, L dZ ( L qZ ( (This refers to the common operating condition set Z) d , q Shaft motor inductor set, This is the motor coordinate transformation matrix. This is the matrix transpose.

[0029] The synthetic flux linkage parameter Ψ of the motor under demagnetization fault Z ( The data is obtained through motor coordinate transformation. dq The motor flux linkage parameter under the shaft is expressed as follows: ; ; ; ; In the formula, Ψ fdZ ( ), Ψ fqZ ( (This refers to the common operating conditions of motors under condition Z) d , q Axial permanent magnet flux linkage; It should be noted that in this embodiment... , .

[0030] Further obtain the motor parameter set The parameter set was fitted with a second-order Fourier function with respect to the mechanical angle of the motor rotor. function set G Z Its expression is: ; ; In the formula, A 0z A 1z B 1z A 2z B 2z These are the fitting coefficient matrices of the constant term in the Fourier function, respectively. The fitting coefficient matrix of the term, The fitting coefficient matrix of the term, The fitting coefficient matrix of the term, The fitting coefficient matrix of the term, It is a positive integer.

[0031] Extract the constant term A from it. 0Z =[A 00 A 01 ... A 0z ... A 08 [P] is the key parameter set of the motor under operating condition Z. Z ,Right now: ; Data set I of effective values ​​of motor stator phase current Z With key parameter set P Z Fitting the polynomial function set F Z Constructing the operating conditions (effective value of phase current) of a permanent magnet synchronous motor under partial demagnetization fault of the permanent magnet. i e Key parameter functions: ; ; In the formula, C0, C1, and C2 are the fitting coefficient matrices of the constant term in the quadratic polynomial function, respectively. The fitting coefficient matrix of the term, The fitting coefficient matrix of the term, , They are respectively d , q Inductance function of shaft motor , They are respectively d , q The flux linkage function of the permanent magnet in the shaft motor.

[0032] Then, a permanent magnet synchronous motor under demagnetization fault conditions is constructed. dq Axis lumped parameter model, such as Figure 4 As shown.

[0033] First, the flux linkage equation of the permanent magnet synchronous motor under demagnetization fault is constructed, and its expression is as follows: ; In the formula, Ψ d Ψ q For motor d, q Axial composite magnetic flux, i d , i q For motor d, q shaft current value, L d , L q For motor d, q Shaft inductance value, fd , fq For the permanent magnet of the motor d, q Axial magnetic flux.

[0034] Constructing a permanent magnet synchronous motor dq The mathematical model under the axis is expressed as follows: ; In the formula, u d , u q For motor d, q shaft voltage, R s This is the resistance of the motor stator winding. p This represents the number of pole pairs of the motor. ω m This represents the motor speed.

[0035] Furthermore, it is possible to construct a permanent magnet synchronous motor under partial demagnetization fault conditions. dq The lumped-parameter model of the axes is expressed as follows: ; Permanent magnet synchronous motor under partial demagnetization fault dq Simulation results of the A-phase current under the motor control system using the shaft lumped parameter model, such as... Figure 5 As shown.

[0036] The modeling method proposed in this application can improve the real-time performance of the demagnetization fault model under the permanent magnet synchronous motor control system, and simulate the permanent magnet synchronous motor control system under real demagnetization faults. It has important theoretical research value and engineering application potential.

[0037] Corresponding to the above method embodiments, this embodiment also provides a permanent magnet synchronous motor demagnetization fault modeling system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the above method. The above-described permanent magnet synchronous motor demagnetization fault modeling system can implement various embodiments of the above-described permanent magnet synchronous motor demagnetization fault modeling method and achieve the same beneficial effects; therefore, further details are omitted here.

[0038] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method of modeling demagnetization fault of permanent magnet synchronous motor, characterized in that, include: S1: Construct a finite element model of a permanent magnet synchronous motor under demagnetization fault; S2: Based on the calculation results of the finite element model, establish a dataset of key inductance parameters and key flux linkage parameters for permanent magnet synchronous motors under different operating conditions. S3: Construct the lumped parameter function of the permanent magnet synchronous motor under demagnetization fault based on the inductance key parameter dataset and the flux linkage key parameter dataset; S4: Construct a total parameter model of the permanent magnet synchronous motor under demagnetization fault based on the motor lumped parameter function; S3 includes: S31: The motor inductance parameter L under demagnetization fault Z ( Obtained through motor coordinate transformation dq The motor inductance parameters under the shaft are expressed as follows: ； ； ； ； In the formula, L dZ ( ), For the commonly used operating condition set Z d , q Shaft motor inductor set, This is the motor coordinate transformation matrix. For matrix transpose, L ABCz For the first z Three-phase inductor matrix of motor under various operating conditions For the mechanical angle of the motor rotor; S32: Combine the motor flux linkage parameter Ψ Z ( Obtained through motor coordinate transformation dq The motor flux linkage parameter under the shaft is expressed as follows: ； ； ； ； In the formula, Ψ fdZ ( ), Ψ fqZ ( (This refers to the common operating conditions of motors under condition Z) d , q Axial permanent magnet flux linkage, , , For the first z Three-phase flux linkage matrix of motor under various operating conditions i d , i q Motors d, q Shaft current value; S33: Establish motor parameter set The parameter set was fitted with a second-order Fourier function with respect to the mechanical angle of the motor rotor. function set G Z Its expression is: ； ； In the formula, A 0z A 1z B 1z A 2z B 2z These are the fitting coefficient matrices of the constant term in the Fourier function, respectively. The fitting coefficient matrix of the term, The fitting coefficient matrix of the term, The fitting coefficient matrix of the term, The fitting coefficient matrix of the term, It is a positive integer; Extracting constant terms As the key parameter set of the motor under operating condition Z ,Right now: S34: Data set I of effective values ​​of motor stator phase current Z With key parameter set P Z Fitting the polynomial function set F Z The effective value of the phase current of a permanent magnet synchronous motor under the condition of partial demagnetization of the permanent magnet is constructed. i e Key parameter functions: ； ； In the formula, C0, C1, and C2 are the fitting coefficient matrices of the constant term in the quadratic polynomial function, respectively. The fitting coefficient matrix of the term, The fitting coefficient matrix of the term, , They are respectively d , q Inductance function of shaft motor , They are respectively d , q The flux linkage function of the permanent magnet in the shaft motor. For the first z The effective value of the stator phase current of the motor under each operating condition.

2. The method for modeling demagnetization faults of permanent magnet synchronous motors according to claim 1, characterized in that, The total parameter model is as follows: dq Axis lumped parameter model.

3. The method for modeling demagnetization faults of permanent magnet synchronous motors according to claim 1, characterized in that, S2 includes: S21: Collect data on the permanent magnet synchronous motor operating condition set Z=0,1,... z ,..., Z Effective value of stator phase current of lower motor i e Construct a dataset of effective values ​​of stator phase currents I Z : ； In the formula, i ez For the first z The effective value of the stator phase current of the motor under each operating condition; S22: Set the excitation source sets of the three-phase currents of the permanent magnet synchronous motor stator A, B, and C under operating condition set Z as follows: , , The expression is as follows: ； ； In the formula, i az , i bz , i cz The first z The three-phase current values ​​of motor stator A, B, and C under each operating condition. For the mechanical angle of the motor rotor, p This represents the number of pole pairs of the motor. S23: Obtain the motor inductance dataset of the permanent magnet synchronous motor with demagnetization fault under operating condition set Z. and magnet link dataset : ； ； ； ； In the formula, L ABCz For the first z Three-phase inductor matrix of motor under various operating conditions L AAz ( ), L BBz ( ), L CCz ( ) are respectively the first z The self-inductance of the motor's three-phase windings A, B, and C under various operating conditions M ABz ( ), M BAz ( ), M ACz ( ), M CAz ( ), M BCz ( ), M BCz ( ) represent the mutual inductance between the phase windings of the motor, Ψ ABCz For the first z Three-phase flux linkage matrix of motor under various operating conditions ( ), ( ), ( ) are respectively the first z The three-phase flux linkages of the motor (A, B, and C) under various operating conditions.

4. The method for modeling demagnetization faults of permanent magnet synchronous motors according to claim 1, characterized in that, The total parameter model in S4 satisfies the following relationship: ； In the formula, R s This is the resistance of the motor stator winding. i d , i q Motors d, q shaft current value, u d , u q Motors d, q Shaft voltage value, ω m This refers to the motor speed. , They are respectively d , q Inductance function of shaft motor p This represents the number of pole pairs of the motor.

5. A demagnetization fault modeling system for a permanent magnet synchronous motor, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1 to 4.

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