Permanent magnet motor overall magnetizing transient analysis method and magnetizing machine

Abstract

The application discloses a permanent magnet motor overall magnetizing transient analysis method and a magnetizing machine. A two-dimensional model of a rotor permanent magnet is obtained, the two-dimensional model is divided into multiple magnetic domain units, and an energy change amount model of each magnetic domain unit is determined. The rotor of the permanent magnet motor is rotated multiple times at a preset angle. For each rotation, the following operations are performed: the permanent magnet in the rotor is magnetized by the magnetizing machine; during the magnetization process, the magnetic domain flip state of each magnetic domain unit is determined based on the energy change amount model of each magnetic domain unit, and the residual magnetism of the permanent magnet after the magnetization is determined according to the magnetic domain flip state of each magnetic domain unit, the residual magnetism of the permanent magnet after the magnetization is taken as the initial state of the next magnetization; and the final residual magnetism of the permanent magnet is determined according to the residual magnetism of the permanent magnet after the last magnetization. The application can obtain the residual magnetism of the permanent magnet at each transient in the magnetization process of the permanent magnet, and can obtain the cumulative magnetization effect of multiple magnetizations on the magnetic domain.

Description

Technical Field

[0001] This application relates to the field of permanent magnet magnetization technology, and in particular to a transient analysis method and magnetizer for overall magnetization of a permanent magnet motor. Background Technology

[0002] The magnetization process of permanent magnets has a significant impact on the performance, manufacturing quality, and production safety of motors. In the manufacturing process of permanent magnet motors, post-magnetization technology is widely used, which involves magnetizing the permanent magnets using a magnetizer after rotor assembly. To ensure that the permanent magnets achieve the required magnetization intensity, the magnetization process requires precise analysis and design.

[0003] In related technologies, the analysis of the post-magnetization process typically employs a static electromagnetic field simulation method. This method generally applies a fixed current to the magnetizing winding under static field conditions, observes the magnetic field distribution of the permanent magnet poles, and combines this with the hysteresis loop of the permanent magnet material to determine whether the permanent magnet has reached a saturation magnetization state. This method has the following problems: The magnetization of permanent magnet materials is a typical relaxation process. The magnetic induction intensity B of the material lags behind the change in magnetic field H. It takes time for the permanent magnet material to establish a new magnetization state. In actual magnetization, the magnetic field is a rapidly changing pulse. Judging the remanence of the permanent magnet solely based on the magnetic field intensity at a single moment cannot accurately reflect the dynamic process of magnetization and makes it difficult to truly evaluate the magnetization effect. In multiple magnetization applications, each magnetization changes the remanence distribution of the permanent magnet, and the magnetic field distribution changes accordingly, potentially interfering with adjacent magnetic pole regions. This results in a significant coupling characteristic in the magnetization process. Static simulation methods cannot incorporate the cumulative effect of multiple magnetizations into the analysis, nor can they adequately reflect the mutual influence between different pulses. Although the magnetization process is short-lived, it is a typical transient electromagnetic phenomenon. The magnetic field will initially increase and then decrease within a short period, causing the magnetic field intensity to change dynamically over time. Different amplitudes of magnetic field changes will affect the final remanence. Static methods ignore the time dimension of the pulse current and cannot accurately describe the actual magnetization process. Therefore, electromagnetic field simulation methods cannot simulate actual magnetization in real time, and cannot simultaneously consider the combined effects of magnetic field strength, pulse time characteristics, and magnetic field spatial distribution on the magnetization process, making it difficult to provide accurate basis for magnetization strategy optimization and equipment design. Summary of the Invention

[0004] The purpose of this application is to provide a transient analysis method for the overall magnetization of a permanent magnet motor, which can obtain the remanence of the permanent magnet at each transient state during the magnetization process and reflect the cumulative magnetization effect of multiple magnetizations on the magnetic domains.

[0005] Firstly, this application provides a method for overall magnetization transient analysis of a permanent magnet motor, the method comprising: A two-dimensional model of the permanent magnet of the rotor is obtained, the two-dimensional model is divided into multiple magnetic domain units, and the energy change model of each magnetic domain unit is determined. The energy change model is determined based on the energy model and energy barrier of the Ising model. The rotor of the permanent magnet motor is rotated multiple times at a preset angle, and the following operation is performed after each rotation: The permanent magnets in the rotor are magnetized using a magnetizer; During this magnetization process, the domain flipping state of each domain unit is determined based on the energy change model of each domain unit, and the remanence of the permanent magnet after this magnetization is determined according to the domain flipping state of each domain unit. The remanence of the permanent magnet after this magnetization is used as the initial state for the next magnetization. The final remanence of the permanent magnet is determined by the remanence of the permanent magnet after the last magnetization.

[0006] In one embodiment, a two-dimensional model of the permanent magnet of the rotor is obtained, and the two-dimensional model is divided into multiple magnetic domain units, including: A two-dimensional model of the permanent magnet is constructed using the permanent magnet portion of one-quarter of the rotor structure model. The two-dimensional model is divided into multiple magnetic domain units, each of which includes multiple magnetic domains. Each magnetic domain unit is configured such that the magnetic field strength is uniformly distributed and has the same magnitude and direction, and the remanence after magnetization is the statistical result of the average magnetization degree of all magnetic domains in the magnetic domain unit. The magnetization direction is set to be consistent with the parallel magnetization direction of the rotor; The magnetic moment direction of each domain is either 1 or -1. 1 indicates that the magnetic moment direction of the domain is consistent with the magnetization direction, and -1 indicates that the magnetic moment direction of the domain is opposite to the magnetization direction.

[0007] In one embodiment, determining the energy change model for each magnetic domain unit includes: For each magnetic domain, The energy model of the Ising model of the magnetic domain is described by the Hamiltonian energy function, which is determined based on the magnetic moment direction of the domain itself, the magnetic moment direction of each adjacent domain, the coupling coefficient between adjacent domains, the effective magnetic moment of the domain spin, and the magnetizing current. The energy difference between two adjacent time steps is determined based on the Hamiltonian energy function. The energy change model between two adjacent time steps of the magnetic domain is determined based on the energy difference and the energy barrier of the magnetic domain. The energy barrier characterizes the energy threshold that the magnetic domain needs to overcome to flip. The energy barrier follows a normal distribution.

[0008] In one embodiment, the Hamiltonian energy function is expressed as: ; Among them, S i S represents the direction of the magnetic moment of the i-th domain. j J represents the direction of the magnetic moment of the j-th magnetic domain adjacent to the i-th magnetic domain. ij This represents the coupling coefficient between the i-th and j-th magnetic domains.<i,j> The combination of magnetic domains adjacent to the i-th magnetic domain is represented by μ, where μ represents the effective magnetic moment of the domain spin, and h is the effective magnetic moment of the domain spin. j This indicates the input magnetizing current; The energy change model is expressed as: ; Where H(t) represents the energy of the magnetic domain at time t, H(t+Δt) represents the energy of the magnetic domain at time t+Δt, ΔE represents the energy change of the magnetic domain between time t+Δt and time t, and E barrier It represents an energy barrier.

[0009] In one embodiment, the magnetization process includes a process with magnetizing current input and a process without magnetizing current input. The domain reversal state of each domain unit is determined based on an energy change model, and the remanence of the permanent magnet after magnetization is determined based on the domain reversal state of each domain unit. During the process of receiving a magnetizing current, the magnetizing current is input to the rotor through a magnetizer to magnetize the permanent magnets in the rotor. Within the pulse duration of the magnetizing current, the pulse duration is divided into multiple time steps, wherein, within each time step, For each magnetic domain unit, the Monte Carlo algorithm and energy change model are used to determine the domain flipping state of each domain in the magnetic domain unit, and the mean value of the magnetic moment direction of the magnetic domain unit is determined based on the domain flipping state of each domain. Based on the average value of the magnetic moment direction of each magnetic domain unit, the remanence of the permanent magnet within this time step is determined, and the remanence of the permanent magnet is used as the initial state of the permanent magnet in the next time step. Once the residual magnetism of the permanent magnet is obtained within the last time step, magnetization of the permanent magnet is stopped.

[0010] In one embodiment, the Monte Carlo algorithm and energy change model are used to determine the domain flipping state of each domain in the domain unit, and the mean value of the magnetic moment direction of the domain unit is determined based on the domain flipping state of each domain, including: Divide the time step into M Monte Carlo steps; Perform the following operation within the Lth Monte Carlo step: Based on the pulse waveform of the magnetizing current, obtain the current value corresponding to the Monte Carlo step size; A domain is randomly selected from the domain unit. Assuming that the domain flips, the energy of the domain in the Lth Monte Carlo step is calculated using the Hamiltonian energy function based on the magnetic moment direction of the flipped domain and the magnetic moment directions of each adjacent domain. According to the energy and energy change model in the (L-1)th Monte Carlo step, the energy change of the domain in the Lth Monte Carlo step is calculated. Based on the energy change and the Metropolis decision criterion, it is determined whether the domain accepts flipping. The magnetic moment direction of the domain is determined based on the result of the determination. Repeat the above steps until the number of randomly flipped magnetic domains reaches M. Based on the average value of the magnetic moment direction of each magnetic domain of the acquired magnetic domain unit, determine the average value of the magnetic moment direction of the magnetic domain unit within the time step.

[0011] In one embodiment, determining whether the magnetic domain has received a flip, based on energy changes and the Metropolis decision criterion, includes: If the energy change is less than or equal to 0, the magnetic domain is determined to be subject to flipping. If the energy change is greater than 0, the domain is determined to accept the flip with a domain flip probability P, where the domain flip probability P is calculated using the following formula: ; Where, ΔE l k represents the energy change of a magnetic domain within the Lth Monte Carlo step. B denoted as Boltzmann constant, and T represents absolute temperature.

[0012] In one embodiment, determining the domain reversal state of each domain unit based on an energy change model, and determining the remanence of the permanent magnet after magnetization based on the domain reversal state of each domain unit, further includes: During the process without magnetizing current input, the magnetizing current is set to zero within a preset time period, and the residual magnetism of the permanent magnet in the last time step is taken as the initial state. The preset time period is divided into multiple calculation steps, where, within each calculation step, For each magnetic domain unit, the domain flipping state of each domain in the magnetic domain unit is determined based on the energy change model, and the mean value of the magnetic moment direction of the magnetic domain unit is determined based on the domain flipping state of each domain. Based on the average value of the magnetic moment direction of each magnetic domain unit, the remanence of the permanent magnet within the calculation step is determined, and the remanence of the permanent magnet is used as the initial state of the next calculation step. The remanence of the permanent magnet after this magnetization is determined by the remanence of the permanent magnet obtained from the last calculation step.

[0013] In one embodiment, the domain flipping state of each domain in the domain unit is determined based on an energy change model, and the mean value of the magnetic moment direction of the domain unit is determined based on the domain flipping state of each domain, including: The preset time period is divided into Q calculation steps. Within the Kth calculation step, A domain is randomly selected from the domain unit. Assuming that the domain flips, the energy corresponding to the domain at the Kth calculation step is calculated using the Hamiltonian energy function based on the magnetic moment direction of the flipped domain and the magnetic moment directions of each domain adjacent to the flipped domain. According to the energy and energy change model corresponding to the (K-1)th calculation step, the energy change of the domain at the Kth calculation step is calculated. Based on the energy change and the Metropolis decision criterion, it is determined whether the domain accepts flipping. Based on the result of the determination, the magnetic moment direction of the domain is determined. Based on the average magnetic moment direction of each domain in the domain unit, the average magnetic moment direction of the domain unit in the Kth calculation step is determined. Then, the mean value of the magnetic moment direction of each magnetic domain unit in the Kth calculation step is obtained, the remanence of the permanent magnet in the Kth calculation step is determined, and the remanence of the permanent magnet in the Kth calculation step is used as the initial state of the permanent magnet in the K+1th calculation step.

[0014] Secondly, this application provides a magnetizer, comprising: The magnetization circuit is used to magnetize the permanent magnets in the rotor; The controller includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the transient analysis method for overall magnetization of the permanent magnet motor as described above.

[0015] This application constructs an energy change model for magnetic domains using the energy model and energy barrier of the Ising model. Based on the energy change model, it analyzes the flipping of each magnetic domain to determine the remanence of the permanent magnet after each magnetization. The energy change model considers the external magnetic field, the interaction between magnetic domains, and the differences between magnetic domains. It can simulate the physical process of actual magnetization of permanent magnets from the perspective of microscopic magnetic domains and obtain the magnetic field distribution and remanence of permanent magnets at each transient state during the magnetization process. By performing multiple rotations and multiple magnetizations, the magnetic domains of the permanent magnet continuously accumulate and flip during multiple magnetizations, which can reflect the cumulative magnetization effect of multiple magnetizations on the magnetic domains and obtain the final remanence distribution that conforms to the actual magnetization process. This can provide an important basis for formulating the optimal magnetization strategy for permanent magnets. Attached Figure Description

[0016] Figure 1 This is a first flowchart of the transient analysis method for overall magnetization of a permanent magnet motor provided in an embodiment of this application; Figure 2 This is a schematic diagram of a two-dimensional model of a permanent magnet provided in an embodiment of this application; Figure 3 This is a second flowchart of the transient analysis method for overall magnetization of a permanent magnet motor provided in an embodiment of this application; Figure 4 The third flowchart is provided for the transient analysis method of overall magnetization of permanent magnet motors in this application embodiment; Figure 5 A schematic diagram illustrating the variation of magnetic domain distribution with external magnetic field strength as provided in an embodiment of this application; Figure 6 The fourth flowchart of the transient analysis method for overall magnetization of permanent magnet motors provided in the embodiments of this application; Figure 7 This is a schematic diagram of the hysteresis loop waveform under different durations of magnetizing magnetic fields provided in the embodiments of this application; Figure 8 A schematic diagram of hysteresis loop waveforms under different temperature conditions provided in the embodiments of this application; Figure 9 This is a schematic diagram of the surface magnetic distribution of a permanent magnet rotor provided in this application embodiment under different magnetization voltage excitation in a simulation environment; Figure 10 The magnetization circuit provided in the embodiments of this application; Figure 11 This is a schematic diagram of a magnetizer and magnetization process provided in an embodiment of this application; Figure 12 This is a schematic diagram of the rotor structure to be magnetized provided in an embodiment of this application; Figure 13 This is a schematic diagram of the surface magnetic distribution of the permanent magnet rotor provided in the embodiments of this application under different magnetization voltage excitation in an experimental verification environment. Detailed Implementation

[0017] The present application will be described in detail below with reference to the specific embodiments shown in the accompanying drawings. However, these embodiments do not limit the present application. Any structural, methodological, or functional modifications made by those skilled in the art based on these embodiments are included within the protection scope of the present application.

[0018] Please refer to Figure 1 This application provides a method for transient analysis of the overall magnetization of a permanent magnet motor, the method comprising: S101, Obtain a two-dimensional model of the permanent magnet of the rotor, divide the two-dimensional model into multiple magnetic domain units, determine the energy change model of each magnetic domain unit, and determine the energy change model based on the energy model and energy barrier of the Ising model.

[0019] A two-dimensional model of the permanent magnet rotor is constructed, which describes the geometry of the permanent magnet. The two-dimensional model is divided into multiple domain units. Based on the energy model and energy barrier of the Ising model, an energy change model for each domain unit is constructed. The interaction between domain spins can be described using the Ising model. The energy model of the Ising model uses Hamiltonian functions. In a permanent magnet, due to crystal defects, domain wall pinning positions, local stress distribution, and differences in magnetocrystalline anisotropy, the energy thresholds required for domain flipping are not the same for different domains, and different domain flipping has its own inherent energy barrier.

[0020] The energy model of the Ising model includes the coupling energy between adjacent magnetic domains and the energy of the external magnetic field on the magnetic domains. By introducing an energy barrier into the energy change model, it not only reflects the magnetic domain flipping situation from an energy perspective, but also introduces the differences between different magnetic domains, making the magnetic domain flipping results closer to the magnetization behavior of actual permanent magnets.

[0021] S102, the rotor of the permanent magnet motor is rotated multiple times at a preset angle. After each rotation, the following operation is performed: the permanent magnet in the rotor is magnetized by a magnetizer. During the magnetization process, the domain reversal state of each domain unit is determined based on the energy change model of each domain unit, and the residual magnetism of the permanent magnet after the magnetization is determined according to the domain reversal state of each domain unit. The residual magnetism of the permanent magnet after the magnetization is used as the initial state for the next magnetization.

[0022] For example, the preset angle can be set to 22.5 degrees. The rotor of the permanent magnet motor rotates from 0 degrees, with a rotation angle of 22.5 degrees, and can rotate 4 times. After each rotation, the permanent magnets in the rotor are magnetized by a magnetizer to change the spatial position of the permanent magnets in the magnetizer, so that the permanent magnets are subjected to pulsed magnetic fields at different spatial positions. During each magnetization process, the domain reversal state of each domain unit is determined based on the energy change model of each domain unit, and the remanence of the permanent magnets after this magnetization is determined according to the domain reversal state of each domain unit. The remanence of the permanent magnets after this magnetization is used as the initial state for the next magnetization, thereby continuously updating the magnetic field distribution and remanence of the permanent magnets.

[0023] S103, the final remanence of the permanent magnet is determined by the remanence of the permanent magnet after the last magnetization.

[0024] In this embodiment, an energy change model of magnetic domains is constructed using the energy model and energy barrier of the Ising model. Based on the energy change model, the flipping of each magnetic domain is analyzed to determine the remanence of the permanent magnet after each magnetization. This energy change model considers the external magnetic field, the interaction between magnetic domains, and the differences between magnetic domains. It can simulate the physical process of the actual magnetization of the permanent magnet from the perspective of microscopic magnetic domains and obtain the magnetic field distribution and remanence of the permanent magnet at each transient state during the magnetization process. By performing multiple rotations and multiple magnetizations, the permanent magnet is subjected to external pulse magnetic fields at different spatial positions, which can reflect the influence of the remanence after the previous magnetization on the next magnetization. The magnetic domains of the permanent magnet continuously accumulate and flip during multiple magnetizations, which can reflect the cumulative magnetization effect of multiple magnetizations on the magnetic domains and obtain the final remanence distribution that conforms to the actual magnetization process. This provides an important basis for formulating the optimal magnetization strategy for the permanent magnet.

[0025] One embodiment of this application obtains a two-dimensional model of the permanent magnet of the rotor, and divides the two-dimensional model into multiple magnetic domain units, including: A two-dimensional model of the permanent magnet is constructed using the permanent magnet portion of one-quarter of the rotor structure model. The two-dimensional model is divided into multiple magnetic domain units, each of which includes multiple magnetic domains. Each magnetic domain unit is configured such that the magnetic field strength is uniformly distributed and has the same magnitude and direction, and the remanence after magnetization is the statistical result of the average magnetization degree of all magnetic domains in the magnetic domain unit. The magnetization direction is set to be consistent with the parallel magnetization direction of the rotor; The magnetic moment direction of each domain takes the value of 1 or -1. 1 indicates that the magnetic moment direction of the domain is in the same direction as the magnetization direction, and -1 indicates that the magnetic moment direction of the domain is opposite to the magnetization direction.

[0026] To simulate the transient evolution of magnetic domains in a permanent magnet under a pulsed magnetic field, a two-dimensional analysis model based on domain units was established. Due to the symmetry of the motor, the two-dimensional model of the permanent magnet was constructed using one-quarter of the permanent magnet portion of the rotor structure model. The number of domain units and domain divisions can be determined according to the required accuracy of the model analysis.

[0027] For example, such as Figure 2As shown, the two-dimensional model of the permanent magnet is divided into four parts: PM1, PM2, PM3, and PM4. Each part is further divided into 18 domain units, resulting in 72 domain units. Each domain unit is further divided into 50*50=2500 domains. Each domain unit is configured to have a uniform magnetic field strength distribution with consistent magnitude and direction, and to have the same remanence value after magnetization. To reduce the computational complexity of the model, the remanence of a domain unit after magnetization is taken as the statistical result of the average magnetization of all domains within that domain unit, i.e., the average value of the magnetic moment direction of all domains is calculated, with a value ranging from [0,1], to characterize the magnetization degree of the permanent magnet from its unmagnetized state to its fully saturated state.

[0028] Considering that permanent magnets generally have obvious easy magnetization axis characteristics, that is, permanent magnets are most easily magnetized in a certain direction but difficult to magnetize in other directions, for surface-mounted permanent magnet rotors, the easy magnetization direction of the permanent magnets is usually arranged along the thickness direction or radial direction of the magnet. Therefore, in the model, the magnetization direction is set to be consistent with the parallel magnetization direction of the rotor, and the magnetic moment direction of each magnetic domain is oriented along the easy magnetization axis direction, that is, it takes a value of 1 or -1. 1 indicates that the magnetic moment direction of the magnetic domain is consistent with the magnetization direction, and -1 indicates that the magnetic moment direction of the magnetic domain is opposite to the magnetization direction.

[0029] In this embodiment, by constructing a microscopic magnetic domain model of the permanent magnet, the domain flipping behavior of the permanent magnet during the magnetization process can be effectively simulated, including the movement of domain walls, the orientation change of local magnetic moments driven by an external magnetic field, and the cooperative evolution caused by the coupling between domains, laying the foundation for subsequent transient magnetization process solutions and remanent magnetization distribution calculations.

[0030] One embodiment of this application, such as Figure 3 As shown, the model for determining the energy change of each magnetic domain unit includes: S301, For each magnetic domain, the energy model of the Ising model of that domain is described by the Hamiltonian energy function, which is determined based on the magnetic moment direction of the domain itself, the magnetic moment direction of each adjacent magnetic domain, the coupling coefficient between adjacent magnetic domains, the effective magnetic moment of the domain spin, and the magnetizing current. S302, the energy difference between two adjacent time steps is determined based on the Hamiltonian energy function, and the energy change model between two adjacent time steps of the magnetic domain is determined based on the energy difference and the energy barrier of the magnetic domain.

[0031] The Ising model, a two-dimensional magnetic domain model of a permanent magnet, demonstrates how, under the influence of a pulsed magnetic field, each domain updates its magnetic moment orientation within a time step based on its own magnetic field energy and the coupling energy of neighboring domains. This enables the movement of domain walls, the expansion and contraction of domains, and irreversible flipping of domains. As the pulsed magnetic field increases and decreases, the spin orientation state of the domains gradually evolves over time, thus forming a time-dependent multi-domain dynamic model. The Ising model not only captures the local details of domain dynamics but also reflects the interactions and evolution of domains in real time throughout the magnetization process, providing a fine-grained domain-level physical model for subsequent transient magnetization analysis.

[0032] To describe the interaction between magnetic domain units within a permanent magnet and the energy change process of the domains under an applied pulsed magnetic field, an energy model based on the Ising model is constructed. This energy model is described by the Hamiltonian energy function, which characterizes the energy state of the magnetic domains. The Hamiltonian energy function is expressed as: ; Among them, S i S represents the direction of the magnetic moment of the i-th domain. j J represents the direction of the magnetic moment of the j-th magnetic domain adjacent to the i-th magnetic domain. ij J represents the coupling coefficient between the i-th and j-th magnetic domains. ij A value greater than zero indicates ferromagnetic coupling characteristics, meaning the spins tend to align in parallel.<i,j> The combination of magnetic domains adjacent to the i-th magnetic domain is represented by μ, where μ represents the effective magnetic moment of the domain spin, and h is the effective magnetic moment of the domain spin. j This represents the input magnetizing current.

[0033] The Hamiltonian energy function indicates that the domain behavior of a permanent magnet is driven by two factors: the coupling between adjacent domains and the influence of the applied magnetic field on domain orientation. The first term of the function describes the coupling between domains, which causes adjacent domain units to tend to maintain the same orientation, thus reflecting domain wall movement and domain expansion behavior. The second term describes the energy of the interaction between the applied pulsed magnetic field and the domain units. During magnetization, the Hamiltonian energy function continuously changes throughout the magnetization cycle because the pulsed magnetic field exhibits a rising-peak-decreasing waveform over time. During the rising phase of the pulsed magnetic field, the external magnetic field energy term increases rapidly, driving the spin orientation of the domain units to flip along the direction of the external field. During the peak phase, the coupling energy between domains decreases rapidly, causing the domains to tend to merge. During the decay phase, the spin orientation gradually stabilizes. When the external magnetic field is completely removed, the system remains in a low-energy stable state determined by the domain coupling, which corresponds to the magnetization remanence of the permanent magnet.

[0034] For example, the energy change model is expressed as: ; Where H(t) represents the energy of the magnetic domain at time t, H(t+Δt) represents the energy of the magnetic domain at time t+Δt, ΔE represents the energy change of the magnetic domain between time t+Δt and time t, and E barrier It represents an energy barrier.

[0035] For example, the energy barrier characterizes the energy threshold that needs to be overcome for the domain flip, and the energy barrier setting follows a normal distribution.

[0036] The Hamiltonian energy function based on the Ising model includes the coupling energy between adjacent magnetic domains and the energy exerted by the external magnetic field on the domains. However, when the magnetic field strength is insufficient, if a sufficiently long time step is calculated, almost all magnetic domains may still complete the positive flip. In reality, if the applied magnetic field is insufficient to overcome the magnetocrystalline anisotropy energy and domain pinning effect, the macroscopic remanence of the permanent magnet will never reach saturation, regardless of the duration of the magnetic field. Therefore, introducing an energy barrier into the energy change model can effectively avoid the model misjudging domain flipping when the external magnetic field strength is insufficient, making the domain flipping results closer to the actual magnetization behavior of permanent magnets, thereby improving the accuracy of transient magnetization simulation.

[0037] In this embodiment, by constructing an energy change model, the energy change of magnetic domains with the change of external pulse magnetic field can be calculated at each time step, providing a basis for judging the magnetic domain flipping and magnetic domain structure update at each time step, thereby enabling transient analysis of residual magnetism in the magnetization process.

[0038] One embodiment of this application, such as Figure 4 As shown, the domain reversal state of each domain unit is determined based on the energy change model of each domain unit, and the remanence of the permanent magnet after this magnetization is determined according to the domain reversal state of each domain unit, including... S401, during the process of receiving a magnetizing current, the magnetizing current is input to the rotor through a magnetizer to magnetize the permanent magnets in the rotor; S402 divides the pulse duration of the magnetizing current into multiple time steps within the pulse duration. S403, within each time step, for each magnetic domain unit, the Monte Carlo algorithm and energy change model are used to determine the domain flipping state of each domain in the magnetic domain unit, the mean value of the magnetic moment direction of the magnetic domain unit is determined based on the domain flipping state of each domain, the remanence of the permanent magnet within the time step is determined based on the mean value of the magnetic moment direction of each magnetic domain unit, and the remanence of the permanent magnet is used as the initial state of the next time step; S404: After obtaining the residual magnetism of the permanent magnet in the last time step, stop magnetizing the permanent magnet.

[0039] This magnetization process includes both a process with and without magnetization current input. For example, the transient analysis method is implemented collaboratively using the Ising domain model built in the Matlab platform and the static magnetic field analysis model established in Ansys Maxwell. Ansys Maxwell is used to calculate the magnetic field distribution of the permanent magnet under different magnetization currents, while Matlab is used to execute the domain changes over time in the Ising domain model. During initialization, the waveform of the magnetizer's pulse current over time is obtained through capacitor bank discharge analysis. The remanence value of the permanent magnet in the static magnetic field analysis model is initialized to 0 to simulate the unmagnetized state. Random 1 and -1 values ​​are assigned to the domains in the Ising domain model to represent the disordered structure of domain orientation in the unmagnetized permanent magnet. Through this cross-platform collaborative method, a complete transient analysis process—magnetization current-magnetic field distribution-magnetic domain dynamic evolution-remanence output—is realized, enabling the model to simultaneously consider the actual magnetic field distribution and the microscopic behavior of the domains, thereby obtaining a more realistic surface magnetic distribution result for the permanent magnet rotor. The rotor of the permanent magnet motor is rotated multiple times at a preset angle. After each rotation, a magnetizing current is input into the rotor via a magnetizer to magnetize the permanent magnets within the rotor. Based on an energy change model of each domain unit, the domain flipping state of each domain unit is determined, thereby determining the remanence of the permanent magnet after that magnetization. The remanence of the permanent magnet after that magnetization is used as the initial state for the next magnetization, thus simulating the influence of the remanence after the previous magnetization on the next magnetization.

[0040] Specifically, the pulse duration of the magnetizing current is divided into multiple time steps. Within each time step, the following operations are performed on each magnetic domain unit: using the Monte Carlo algorithm and energy change model, the domain flipping state of each domain in the unit is determined; based on the domain flipping state, the mean value of the magnetic moment direction of the unit is determined; based on the mean value of the magnetic moment direction, the remanence of the permanent magnet within that time step is determined, and this remanence is used as the initial state for the next time step. The remanence of the permanent magnet within that time step is then reassigned to the material parameters of the corresponding permanent magnet unit in the static magnetic field analysis model. The process continues into the next time step, continuing the magnetic field solution, domain flipping, and remanence update process until the end of the time step is reached. If the time step is sufficiently small, the dynamic changes in the domain structure and magnetic field distribution during the magnetization process can be reflected in real time. Magnetic domain information is stored in the form of a cell array, which makes the evolution of magnetic domains continuous between multiple magnetizations, thus truly reflecting the influence of the previous magnetization on the result of the next magnetization.

[0041] In this embodiment, during the process of inputting a magnetizing current into the rotor, the magnetic domain structure, remanent magnetization distribution, and local magnetic field of the permanent magnet are iteratively updated at each time step of each magnetizing current. This enables the model to approximate the real physical evolution law of the magnetization process of the permanent magnet rotor and achieve high-precision simulation of the transient magnetization behavior of the permanent magnet.

[0042] One embodiment of this application employs the Monte Carlo algorithm and an energy change model to determine the domain flipping state of each domain in the domain unit, and determines the average value of the magnetic moment direction of the domain unit based on the domain flipping state of each domain, including: Divide the time step into M Monte Carlo steps; Perform the following operation within the Lth Monte Carlo step: Based on the pulse waveform of the magnetizing current, obtain the current value corresponding to the Monte Carlo step size; A domain is randomly selected from the domain unit. Assuming that the domain flips, the energy of the domain in the Lth Monte Carlo step is calculated using the Hamiltonian energy function based on the magnetic moment direction of the flipped domain and the magnetic moment directions of each adjacent domain. According to the energy and energy change model in the (L-1)th Monte Carlo step, the energy change of the domain in the Lth Monte Carlo step is calculated. Based on the energy change and the Metropolis decision criterion, it is determined whether the domain accepts flipping. The magnetic moment direction of the domain is determined based on the result of the determination. Repeat the above steps until the number of randomly flipped domains reaches M. Based on the average magnetic moment direction of each domain of the acquired domain unit, determine the average magnetic moment direction of the domain unit within that time step. Figure 5 The diagram shows the domain distribution as a function of the external magnetic field strength. (a) shows the domain distribution of an unmagnetized permanent magnet with an average domain value of -0.0352; (b) shows the domain distribution when the external magnetic field strength is insufficient, with a remanence of 0.4154; (c) shows the domain distribution when the magnetization pulse duration is insufficient, with a remanence of 0.6664; and (d) shows the domain distribution of a saturated magnetized permanent magnet with a remanence of 0.9488.

[0043] Because of the large number of magnetic domains and their inherent probabilistic statistical laws, the Monte Carlo algorithm is used to randomly select domains and attempt spin-flipping. This involves assuming the domain unit flips from its current orientation to the opposite orientation. The energy change is calculated based on the changes in coupling energy between the domain unit and its four adjacent domain units, the applied magnetic field energy, and the inherent energy barrier before and after the flip. The Metropolis decision criterion is then used to determine whether the domain unit accepts the flip. This process is repeated. The number of Monte Carlo step sizes reflects the number of random domain flipping attempts made by the system within the pulsed magnetic field duration, thus demonstrating the influence of the duration of the external pulsed magnetic field on the domain evolution behavior. By employing Monte Carlo random sampling updates, the domain flipping behavior evolves gradually with the time variation of the external pulsed magnetic field, simulating the real domain flipping dynamics of a permanent magnet during pulsed magnetization.

[0044] One embodiment of this application determines whether a magnetic domain receives a flip based on energy changes and the Metropolis decision criterion, including: If the energy change is less than or equal to 0, the magnetic domain is determined to be subject to flipping. If the energy change is greater than 0, the domain is determined to be subject to flipping with domain flipping probability P.

[0045] The formula for calculating the domain reversal probability P is: ; Where, ΔE l k represents the energy change of a magnetic domain within the Lth Monte Carlo step. B denoted as Boltzmann constant, and T represents absolute temperature.

[0046] According to the Metropolis criterion, a system always tends to operate at low energy levels, but even when the system's energy increases, it accepts "unfavorable" moves with a certain probability, rather than only accepting moves that decrease energy. If the energy change is less than or equal to 0, spin flips can reduce the system's total energy, and the system unconditionally accepts the flip. If the energy change is greater than 0, spin flips will cause the system's energy to tend to increase, and flips can still occur. The system still accepts the flip with a certain probability, which is positively correlated with temperature: the higher the temperature, the greater the probability that the system will accept spin flips when the energy increases, characterizing the effect of temperature increases on the system's magnetic domain perturbations.

[0047] In this embodiment, the spin-flipping mechanism of the Metropolis criterion can simultaneously consider the coupling effect between adjacent magnetic domains, the effect of the applied pulsed magnetic field, and the influence of temperature, making the simulation results closer to the physical behavior of permanent magnets in the actual magnetization process.

[0048] One embodiment of this application, such as Figure 6As shown, the domain reversal state of each domain unit is determined based on the energy change model of each domain unit, and the remanence of the permanent magnet after this magnetization is determined based on the domain reversal state of each domain unit. The method also includes: S601, during the process of no magnetizing current input, sets the magnetizing current to zero within a preset time period, and takes the residual magnetism of the permanent magnet in the last time step as the initial state; S602, the preset time period is divided into multiple calculation steps. Within each calculation step, for each magnetic domain unit, the domain flipping state of each magnetic domain in the magnetic domain unit is determined based on the energy change model. The mean value of the magnetic moment direction of the magnetic domain unit is determined based on the domain flipping state of each magnetic domain. S603, Based on the average value of the magnetic moment direction of each magnetic domain unit, determine the remanence of the permanent magnet within the calculation step, and use the remanence of the permanent magnet as the initial state of the next calculation step; S604, the remanence of the permanent magnet after this magnetization is determined by the remanence of the permanent magnet obtained from the last calculation step.

[0049] Specifically, the domain flipping state of each domain in the domain unit is determined based on the energy change model, and the mean value of the magnetic moment direction of the domain unit is determined based on the domain flipping state of each domain, including: The preset time period is divided into Q calculation steps. Within the Kth calculation step, A domain is randomly selected from the domain unit. Assuming that the domain flips, the energy corresponding to the domain at the Kth calculation step is calculated using the Hamiltonian energy function based on the magnetic moment direction of the flipped domain and the magnetic moment directions of each domain adjacent to the flipped domain. According to the energy and energy change model corresponding to the (K-1)th calculation step, the energy change of the domain at the Kth calculation step is calculated. Based on the energy change and the Metropolis decision criterion, it is determined whether the domain accepts flipping. Based on the result of the determination, the magnetic moment direction of the domain is determined. Based on the average magnetic moment direction of each domain in the domain unit, the average magnetic moment direction of the domain unit in the Kth calculation step is determined. Then, the mean value of the magnetic moment direction of each magnetic domain unit in the Kth calculation step is obtained, the remanence of the permanent magnet in the Kth calculation step is determined, and the remanence of the permanent magnet in the Kth calculation step is used as the initial state of the K+1th calculation step.

[0050] Although the transient evolution of magnetic domains mainly occurs during the application of an external pulsed magnetic field, the domain structure does not immediately stabilize after the pulsed magnetic field is removed. Instead, it continues to undergo minor adjustments for a short period due to factors such as the interaction energy between domains, the inherent energy barrier, and temperature. Therefore, this embodiment sets multiple second calculation steps and uses the Metropolis criterion to determine domain flipping. Through iteration of multiple calculation steps, the domains gradually eliminate the random disturbances left over from the application of the pulsed magnetic field, tending towards a domain structure determined by both domain coupling and energy barriers. This allows the transient magnetization process to fully simulate the transition of the permanent magnet from the "pulse-driven flipping stage" to the "stable remanent magnetization formation stage," obtaining the magnetic moment direction of the average domain after stabilization as the remanent magnetization output value of the permanent magnet.

[0051] In this embodiment, the transient analysis of the overall magnetization of the permanent magnet is carried out by introducing an iterative update of the dual-step structure of the domains, consisting of a Monte Carlo step and a computational step. The Monte Carlo step is used to simulate the random flipping of the domains under the drive of the external field during the pulsed magnetic field, so that the domains gradually evolve with the time change of the pulsed magnetic field. The computational step is used for the spontaneous stabilization stage after the pulsed magnetic field is removed. Through continuous iteration under the condition of no pulsed magnetic field, the domain structure transitions from the transient state under the pulse to the stable state. This can fully reflect the transient magnetization behavior of the permanent magnet during the pulsed magnetization process and the stable convergence process after the removal of the external pulsed magnetic field, improve the stability of the remanence calculation results, and provide a reliable basis for the optimization of the subsequent magnetization strategy.

[0052] In one specific embodiment of this application, a magnetic field waveform with continuously varying forward and reverse pulse widths is applied to the model to obtain the magnetization curve and hysteresis loop of the model, such as... Figure 7 As shown, this application can effectively simulate the hysteresis characteristics of permanent magnets and is sensitive to the duration of the magnetic field. When the magnetic field duration is less than 5ms, the magnetization and demagnetization effects are more significant with the increase of time at the same field strength. When the magnetic field duration exceeds 5ms, the system response no longer changes, which is important in the design and analysis of magnetizers. Figure 8 The model shown exhibits hysteresis loop waveforms under different temperature conditions. Below 120℃, the effect of temperature on hysteresis characteristics is negligible, and the domain reversal probability changes little. Above 120℃, domain reversal judgment gradually becomes dominated by temperature probability, random reversals increase, the overall area of ​​the hysteresis loop (magnetic energy product) shrinks, and the macroscopic remanence value decreases. Figure 9The magnetic distribution of the permanent magnet rotor under different magnetization voltage excitations is shown. In the simulation environment, the magnetic results of the rotor after four magnetizations under different magnetization voltages are as follows: when the magnetization field strength is low, the overall magnetic value is low. The result of one magnetization is easily affected by the next magnetization, resulting in irregular waveforms. When the capacitor bank discharge voltage and the magnetization field strength are sufficient, the magnetization direction of the four permanent magnets in one magnetic pole is inconsistent in the four magnetization methods of this embodiment. Therefore, the rotor magnetic waveform in each magnetic pole range has four peaks, which is consistent with reality.

[0053] Based on the same concept, this application provides a magnetizer, comprising: The magnetization circuit is used to magnetize the permanent magnets in the rotor; The controller includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-mentioned transient analysis method for the overall magnetization of the permanent magnet motor.

[0054] like Figure 10 The magnetization circuit shown includes a charging circuit and a magnetization circuit. In the charging circuit, closing the switch... K And disconnect the switch D The capacitor bank is powered by DC power supply E. C The capacitor bank C is charged to store energy. In the magnetization circuit, after the capacitor bank C is fully charged, switch K is opened and switch K is closed. D The capacitor bank C discharges instantaneously into the coil L circuit, generating a pulse current and achieving magnetization. The diode in the magnetization circuit... DL It serves to prevent reverse current. The processor can perform transient analysis of the permanent magnet during magnetization. In the experimental verification environment, methods such as... Figure 11 The magnetizer and magnetization process shown, as well as... Figure 12 The rotor to be magnetized, as shown, is obtained using the magnetization transient analysis method of this application, as follows: Figure 13 The rotor surface magnetic distribution under different magnetization voltage excitations shown indicates that the experimental results are basically consistent with the simulation calculation results.

[0055] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0056] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0057] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0058] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0059] The above are merely preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A method for transient analysis of the overall magnetization of a permanent magnet motor, characterized in that, The method includes: A two-dimensional model of the permanent magnet of the rotor is obtained, the two-dimensional model is divided into multiple magnetic domain units, and the energy change model of each magnetic domain unit is determined. The energy change model is determined based on the energy model and energy barrier of the Ising model. The rotor of the permanent magnet motor is rotated multiple times at a preset angle, and the following operation is performed after each rotation: The permanent magnets in the rotor are magnetized using a magnetizer; During this magnetization process, the domain flipping state of each domain unit is determined based on the energy change model of each domain unit, and the remanence of the permanent magnet after this magnetization is determined according to the domain flipping state of each domain unit. The remanence of the permanent magnet after this magnetization is used as the initial state for the next magnetization. The final remanence of the permanent magnet is determined by the remanence of the permanent magnet after the last magnetization. The magnetization process includes a process with magnetizing current input and a process without magnetizing current input. The domain reversal state of each domain unit is determined based on the energy change model of each domain unit, and the remanence of the permanent magnet after magnetization is determined based on the domain reversal state of each domain unit. During the process of receiving a magnetizing current, the magnetizing current is input to the rotor through a magnetizer to magnetize the permanent magnets in the rotor. Within the pulse duration of the magnetizing current, the pulse duration is divided into multiple time steps, wherein, within each time step, For each magnetic domain unit, the Monte Carlo algorithm and energy change model are used to determine the domain flipping state of each domain in the magnetic domain unit, and the mean value of the magnetic moment direction of the magnetic domain unit is determined based on the domain flipping state of each domain. Based on the average value of the magnetic moment direction of each magnetic domain unit, the remanence of the permanent magnet within this time step is determined, and the remanence of the permanent magnet is used as the initial state for the next time step. If the residual magnetism of the permanent magnet is obtained within the last time step, the magnetization of the permanent magnet is stopped; During the process without magnetizing current input, the magnetizing current is set to zero within a preset time period, and the residual magnetism of the permanent magnet at the last time step is taken as the initial state. The preset time period is divided into multiple calculation steps, wherein, within each calculation step, For each magnetic domain unit, the domain flipping state of each domain in the magnetic domain unit is determined based on the energy change model, and the mean value of the magnetic moment direction of the magnetic domain unit is determined based on the domain flipping state of each domain. Based on the average value of the magnetic moment direction of each magnetic domain unit, the remanence of the permanent magnet within the calculation step is determined, and the remanence of the permanent magnet is used as the initial state of the next calculation step. The remanence of the permanent magnet after this magnetization is determined by the remanence of the permanent magnet obtained from the last calculation step.

2. The transient analysis method for overall magnetization of a permanent magnet motor according to claim 1, characterized in that, A two-dimensional model of the permanent magnet of the rotor is obtained, and the two-dimensional model is divided into multiple magnetic domain units, including: A two-dimensional model of the permanent magnet is constructed using the permanent magnet portion of one-quarter of the rotor structure model. The two-dimensional model is divided into multiple magnetic domain units, each of which includes multiple magnetic domains. Each magnetic domain unit is configured such that the magnetic field strength is uniformly distributed and has the same magnitude and direction, and the remanence after magnetization is the statistical result of the average magnetization degree of all magnetic domains in the magnetic domain unit. The magnetization direction is set to be consistent with the parallel magnetization direction of the rotor; The magnetic moment direction of each domain is either 1 or -1. 1 indicates that the magnetic moment direction of the domain is consistent with the magnetization direction, and -1 indicates that the magnetic moment direction of the domain is opposite to the magnetization direction.

3. The transient analysis method for overall magnetization of a permanent magnet motor according to claim 2, characterized in that, Determine the energy change model for each magnetic domain unit, including: For each magnetic domain, The energy model of the Ising model of the magnetic domain is described by the Hamiltonian energy function, which is determined based on the magnetic moment direction of the domain itself, the magnetic moment direction of each adjacent domain, the coupling coefficient between adjacent domains, the effective magnetic moment of the domain spin, and the magnetizing current. The energy difference between two adjacent time steps is determined based on the Hamiltonian energy function. The energy change model between two adjacent time steps of the magnetic domain is determined based on the energy difference and the energy barrier of the magnetic domain. The energy barrier characterizes the energy threshold that the magnetic domain needs to overcome to flip. The energy barrier follows a normal distribution.

4. The transient analysis method for overall magnetization of a permanent magnet motor according to claim 3, characterized in that, The Hamiltonian energy function is expressed as: ； Among them, S i S represents the direction of the magnetic moment of the i-th domain. j J represents the direction of the magnetic moment of the j-th magnetic domain adjacent to the i-th magnetic domain. ij This represents the coupling coefficient between the i-th and j-th magnetic domains.<i,j> The combination of magnetic domains adjacent to the i-th magnetic domain is represented by μ, where μ represents the effective magnetic moment of the domain spin, and h is the effective magnetic moment of the domain spin. j This indicates the input magnetizing current; The energy change model is expressed as follows: ； Where H(t) represents the energy of the magnetic domain at time t, H(t+Δt) represents the energy of the magnetic domain at time t+Δt, ΔE represents the energy change of the magnetic domain between time t+Δt and time t, and E barrier It represents an energy barrier.

5. The transient analysis method for overall magnetization of a permanent magnet motor according to claim 4, characterized in that, The Monte Carlo algorithm and energy change model are used to determine the domain flipping state of each domain in the domain unit. Based on the domain flipping state of each domain, the mean value of the magnetic moment direction of the domain unit is determined, including: Divide the time step into M Monte Carlo steps; Perform the following operation within the Lth Monte Carlo step: Based on the pulse waveform of the magnetizing current, obtain the current value corresponding to the Monte Carlo step size; A domain is randomly selected from the domain unit. Assuming that the domain flips, the energy of the domain in the Lth Monte Carlo step is calculated using the Hamiltonian energy function based on the magnetic moment direction of the flipped domain and the magnetic moment directions of each adjacent domain. According to the energy and energy change model in the (L-1)th Monte Carlo step, the energy change of the domain in the Lth Monte Carlo step is calculated. Based on the energy change and the Metropolis decision criterion, it is determined whether the domain accepts flipping. The magnetic moment direction of the domain is determined based on the result of the determination. Repeat the above steps until the number of randomly flipped domains reaches N. Based on the average value of the magnetic moment direction of each domain of the domain unit, determine the average value of the magnetic moment direction of the domain unit within the time step, where the value of N is the same as the value of M.

6. The transient analysis method for overall magnetization of a permanent magnet motor according to claim 5, characterized in that, Based on the energy change and the Metropolis decision criterion, it is determined whether the magnetic domain is open to flipping, including: If the energy change is less than or equal to 0, the magnetic domain is determined to be subject to flipping. If the energy change is greater than 0, the magnetic domain is determined to accept the flip with a domain flip probability P, wherein the formula for calculating the domain flip probability P is: ； Where, ΔE l k represents the energy change of a magnetic domain within the Lth Monte Carlo step. B denoted as Boltzmann constant, and T represents absolute temperature.

7. The transient analysis method for overall magnetization of a permanent magnet motor according to claim 6, characterized in that, The domain flipping state of each domain in the domain unit is determined based on the energy change model. The mean value of the magnetic moment direction of the domain unit is then determined based on the domain flipping state of each domain, including: The preset time period is divided into Q calculation steps. Within the Kth calculation step, A domain is randomly selected from the domain unit. Assuming that the domain flips, the energy corresponding to the domain at the Kth calculation step is calculated using the Hamiltonian energy function based on the magnetic moment direction of the flipped domain and the magnetic moment directions of each domain adjacent to the flipped domain. According to the energy and energy change model corresponding to the (K-1)th calculation step, the energy change of the domain at the Kth calculation step is calculated. Based on the energy change and the Metropolis decision criterion, it is determined whether the domain accepts flipping. Based on the result of the determination, the magnetic moment direction of the domain is determined. Based on the average magnetic moment direction of each domain in the domain unit, the average magnetic moment direction of the domain unit in the Kth calculation step is determined. Then, the mean value of the magnetic moment direction of each magnetic domain unit in the Kth calculation step is obtained, the remanence of the permanent magnet in the Kth calculation step is determined, and the remanence of the permanent magnet in the Kth calculation step is used as the initial state of the K+1th calculation step.

8. A magnetizer, characterized in that, include: The magnetization circuit is used to magnetize the permanent magnets in the rotor; A controller, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the transient analysis method for overall magnetization of a permanent magnet motor as described in any one of claims 1 to 7.

Images