Magnetization estimation apparatus, method for estimating magnetization, and program

Abstract

To provide a magnetization estimation apparatus capable of directly estimating the state of magnetization of a permanent magnet loaded in a magnetic material.SOLUTION: A magnetization estimation apparatus (10) estimates the state of magnetization of a permanent magnet (24) loaded in a magnetic material. The magnetization estimation apparatus (10) includes: a measuring unit (11) for measuring a first induced electromotive force V0(t) induced on the basis of the permanent magnet (24) in accordance with rotation of the magnetic material; and a control unit (15) for estimating the state of magnetization of the permanent magnet (24) when the first induced electromotive force V0(t) is induced by using a magnetization estimation algorithm on the basis of the first induced electromotive force V0(t) measured by the measuring unit (11).SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a magnetization estimation device, a magnetization estimation method, and a program. [Background technology]

[0002] Conventionally, there are known techniques for calculating the magnetization state of a permanent magnet, including the magnetization distribution, etc. For example, Patent Document 1 discloses a magnetization distribution calculation processing device that can calculate the magnetization distribution of a magnet using an existing general-purpose magnetic field calculation solver. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-328956 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the conventional technology described in Patent Document 1, sufficient consideration is not given to directly estimating the magnetization state of the permanent magnet loaded in the magnetic body.

[0005] An object of the present disclosure is to provide a magnetization estimation device, a magnetization estimation method, and a program that are capable of directly estimating the magnetization state of a permanent magnet loaded on a magnetic body. [Means for solving the problem]

[0006] A magnetization estimation device according to a first aspect for solving the above problem comprises: A magnetization estimation device that estimates the magnetization state of a permanent magnet loaded on a magnetic body, a measurement unit that measures a first induced electromotive force induced by the permanent magnet in accordance with the rotation of the magnetic body; a control unit that estimates a magnetization state of the permanent magnet when the first induced electromotive force is induced using a magnetization estimation algorithm based on the first induced electromotive force measured by the measurement unit; Equipped with.

[0007] A magnetization estimation method according to a second aspect includes: A magnetization estimation method for estimating a magnetization state of a permanent magnet loaded on a magnetic body, comprising: measuring a first induced electromotive force induced by the permanent magnet in association with rotation of the magnetic body; estimating a magnetization state of the permanent magnet when the first induced electromotive force is induced using a magnetization estimation algorithm based on the measured first induced electromotive force; Includes:

[0008] The third perspective program is A magnetization estimation device that estimates the magnetization state of a permanent magnet loaded on a magnetic body, measuring a first induced electromotive force induced by the permanent magnet in association with rotation of the magnetic body; estimating a magnetization state of the permanent magnet when the first induced electromotive force is induced using a magnetization estimation algorithm based on the measured first induced electromotive force; Execute an operation including: [Effects of the Invention]

[0009] According to a magnetization estimation device, a magnetization estimation method, and a program according to an embodiment of the present disclosure, it is possible to directly estimate the magnetization state of a permanent magnet loaded on a magnetic body. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a configuration diagram illustrating a schematic example of a portion of the configuration of a magnetization estimation system including a magnetization estimation device according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a block diagram showing an example of the configuration of the magnetization estimation device of FIG. [Figure 3]3 is a functional block diagram mainly showing an example of the configuration of a control unit in FIG. 2. FIG. [Figure 4] 3 is a flowchart illustrating an example of a magnetization estimation method executed by the magnetization estimation device of FIG. 2. [Figure 5A] 3 is a schematic diagram showing a target magnetization distribution to be compared with the estimation result by the magnetization estimation device of FIG. 2. FIG. [Figure 5B] 5B is a graph showing the time waveform of a first induced electromotive force obtained due to the magnetization distribution shown in FIG. 5A. FIG. [Figure 5C] FIG. 3 is a schematic diagram showing an initial distribution in a simulation performed by the control unit of FIG. 2. [Figure 5D] 5D is a graph showing the time waveform of a second induced electromotive force obtained due to the magnetization distribution shown in FIG. 5C. FIG. [Figure 5E] 3 is a schematic diagram showing a first example of an estimation result output to the output unit in FIG. 2. FIG. [Figure 5F] 5F is a graph mainly showing the time waveform of a second induced electromotive force obtained due to the magnetization distribution shown in FIG. 5E. FIG. [Figure 5G] FIG. 10 is a graph showing how the value of the objective function changes with the number of iterations. [Figure 6A] 3 is a schematic diagram showing a target magnetization distribution to be compared with the estimation result by the magnetization estimation device of FIG. 2. FIG. [Figure 6B] 6B is a graph showing the time waveform of a first induced electromotive force obtained due to the magnetization distribution shown in FIG. 6A. FIG. [Figure 6C] FIG. 3 is a schematic diagram showing an initial distribution in a simulation performed by the control unit of FIG. 2. [Figure 6D] 6D is a graph showing the time waveform of a second induced electromotive force obtained due to the magnetization distribution shown in FIG. 6C. FIG. [Figure 6E] 3 is a schematic diagram showing a second example of the estimation result output to the output unit in FIG. 2. FIG. [Figure 6F] 6F is a graph mainly showing the time waveform of a second induced electromotive force obtained due to the magnetization distribution shown in FIG. 6E. FIG. [Figure 6G] FIG. 10 is a graph showing how the value of the objective function changes with the number of iterations. [Figure 7] FIG. 10 is a configuration diagram illustrating a schematic example of a part of the configuration of a magnetization estimation system including a magnetization estimation device according to a first modified example of the present disclosure. [Figure 8A] FIG. 10 is a configuration diagram illustrating a schematic example of a part of the configuration of a magnetization estimation system including a magnetization estimation device according to a second modified example of the present disclosure. [Figure 8B] 8B is an enlarged cross-sectional view of the area enclosed by the two-dot chain line in FIG. 8A. FIG. [Figure 9A] FIG. 10 is a schematic diagram showing a first target magnetization distribution to be compared with the estimation result by the magnetization estimation device according to the second modified example. [Figure 9B] 3 is a schematic diagram showing an example of an estimation result output to an output unit in FIG. 2. FIG. [Figure 9C] 9C is a graph mainly showing the time waveform of a second induced electromotive force obtained due to the magnetization distribution shown in FIG. 9B. FIG. [Figure 10A] FIG. 10 is a schematic diagram showing a second target magnetization distribution to be compared with the estimation result by the magnetization estimation device according to the second modified example. [Figure 10B] 3 is a schematic diagram showing an example of an estimation result output to an output unit in FIG. 2. FIG. [Figure 10C] 10C is a graph mainly showing the time waveform of a second induced electromotive force obtained due to the magnetization distribution shown in FIG. 10B. DETAILED DESCRIPTION OF THE INVENTION

[0011] The background and problems of the prior art will now be described in more detail.

[0012] Permanent magnets are used in a variety of electromagnetic devices, including smartphones, hard disks, speakers, and motors, and are an essential electromagnetic material in manufacturing. In the mass production process of electromagnetic devices, a post-magnetization method is often used, in which an unmagnetized permanent magnet is loaded into the magnetic circuit and then magnetized. For example, when diagnosing the magnetization quality of a permanent magnet synchronous motor, the magnetization or demagnetization status of the permanent magnet is roughly determined by measuring the no-load induced electromotive force waveform.

[0013] Post-magnetization is also widely adopted in the manufacturing process of synchronous motors. To evaluate the quality of post-magnetization, a known method is to measure the radial magnetic flux density on the rotor core surface using a magnet analyzer (a magnetic field measuring instrument with automatic positioning control of a Tesla meter) and compare the measured magnetic flux distribution with that of the actual magnetization. This method has the advantage of being able to obtain information (harmonic analysis of radial magnetic flux density) that can be used to predict motor vibrations and other issues by measuring the radial magnetic flux density of the rotor core. However, this method has the disadvantage of being difficult to directly evaluate the magnetization distribution inside the permanent magnet. Additionally, this method has the disadvantages of high installation costs for the magnet analyzer, the time required for setup (such as specifying the measurement origin position and setting the measurement point coordinates), and the time required for magnetic field measurement.

[0014] A method for measuring the surface magnetic flux of a magnetic circuit using a flux meter installed next to a magnetizer is known. In this method, a rotor core loaded with a permanent magnet moves near a pickup coil at a low speed, and the electromotive force induced in the pickup coil is measured. Therefore, this method has the advantage of being able to reuse the excitation yoke and excitation coil of the magnetizer. This allows for the evaluation of magnetization quality at a low cost. However, this method has the disadvantage that the rotor core or stator core must be moved at a low speed due to the risk of moving a loaded core at high speed inside the magnetizer, which may result in a decrease in the measurement accuracy of the electromotive force induced in the pickup coil.

[0015] In the above methods, the magnetization quality is estimated using only the rotor core after post-magnetization. In addition to these conventional techniques, various other techniques exist. For example, a method is known for evaluating the magnetization quality of permanent magnets and the performance of synchronous motors by rotating the rotor core using mechanical energy and measuring the induced electromotive force induced in the armature windings wound in the stator slots in an actual synchronous motor (rotating field type). For example, a method is known in which the no-load induced electromotive force (line voltage) is measured to estimate the demagnetization of permanent magnets installed in synchronous motors for railway vehicles, and the measured value is used as a guideline for evaluating the soundness of the permanent magnets. For example, a system is also known that automatically evaluates the soundness of permanent magnets by measuring the no-load induced electromotive force waveform and comparing it with the induced electromotive force waveform when a sound permanent magnet is installed. For example, a system is also known that installs a search coil in the air gap of a synchronous motor, measures the induced electromotive force associated with rotor rotation, and performs harmonic analysis of the waveform to quickly evaluate the soundness of permanent magnets. For example, there is known a prior art technique that considers the influence of demagnetization of the trailing edge of a permanent magnet on induced electromotive force when a synchronous motor is driven.

[0016] In the above-mentioned conventional techniques, the magnetization state of the permanent magnet is suggested by utilizing the no-load induced electromotive force of the synchronous motor or the back electromotive force when the motor is running. However, the more detailed magnetization state of the permanent magnet is not directly estimated. In the above-mentioned conventional techniques, only the amount of change in the induced electromotive force is monitored.

[0017] In order to solve the above-mentioned problems, the present disclosure aims to provide a magnetization estimation device, a magnetization estimation method, and a program capable of directly estimating the magnetization state of a permanent magnet loaded on a magnetic body. The present disclosure provides a new technology that can directly estimate the magnetization distribution and magnetization quality of a permanent magnet by solving a nonlinear optimization problem using measured values ​​of no-load induced electromotive force used in the manufacturing process of a synchronous motor as input values. The technical content of the present disclosure includes measurement of no-load induced electromotive force, calculation of the magnetic field and no-load induced electromotive force of a synchronous motor, and nonlinear optimization calculation. Therefore, the technical content belongs to an interdisciplinary field based on measurement engineering, numerical analysis, and mathematical optimization.

[0018] Hereinafter, one embodiment of the present disclosure will be mainly described with reference to the accompanying drawings.

[0019] FIG. 1 is a configuration diagram illustrating a schematic example of a portion of the configuration of a magnetization estimation system 1 including a magnetization estimation device 10 according to an embodiment of the present disclosure. For the purpose of simplifying the illustration, FIG. 1 omits the illustration of a storage unit 12, an input unit 13, an output unit 14, and a control unit 15, which will be described later with reference to FIG. 2. Regarding the magnetization estimation device 10, only the configuration of a measurement unit 11 is illustrated. With reference to FIG. 1, an overview of the magnetization estimation system 1 including the magnetization estimation device 10 according to an embodiment of the present disclosure will be mainly described. In addition to the magnetization estimation device 10, the magnetization estimation system 1 includes an interior permanent magnet synchronous motor (IPMSM) 20. The IPMSM 20 can also be used as a drive source for, for example, an EV (electric vehicle) or the like.

[0020] The IPMSM 20 has a fixed cylindrical stator core 21. The IPMSM 20 has a rotor core 22 arranged inside the stator core 21. The rotor core 22 is surrounded by the stator core 21. The IPMSM 20 has a shaft 23 attached to the rotor core 22 so as to pass through the rotor core 22. The IPMSM 20 has a permanent magnet 24 embedded inside the rotor core 22. The permanent magnet 24 contains rare earth elements such as neodymium and dysprosium. In the IPMSM 20, an armature winding 11a included in a measurement unit 11 of a magnetization estimation device 10 (described later) is arranged on the stator core 21. The stator is made up of the stator core 21. The rotor is made up of the rotor core 22, the permanent magnet 24, and the shaft 23.

[0021] The permanent magnets 24 are loaded onto the rotor core 22, which serves as a magnetic body. In the present disclosure, the term "magnetic body" includes any of a ferromagnetic body, including a soft magnetic body and a hard magnetic body, and a paramagnetic body. The soft magnetic body includes, for example, an iron core. The hard magnetic body includes, for example, a permanent magnet. The paramagnetic body includes, for example, aluminum, copper, glass, and diamond. In the magnetization estimation system 1 according to an embodiment of the present disclosure, the permanent magnets 24 are loaded onto the rotor core 22, which serves as a soft magnetic body, in the IPMSM 20, as an example.

[0022] In the IPMSM 20, four permanent magnets 24 are periodically arranged in the circumferential direction of a rotor core 22, with the center of rotation as the reference. The IPMSM 20 is, for example, a four-pole motor. In the IPMSM 20, an armature winding 11a is arranged so as to surround the four permanent magnets 24 by 360°. In the IPMSM 20, a rotor having a shaft 23 rotates relative to a stator.

[0023] The magnetization estimation device 10 estimates the magnetization state of, for example, the permanent magnets 24 loaded on the rotor core 22 serving as a magnetic body of the IPMSM 20. In the present disclosure, the "magnetization state" includes, for example, the magnetization distribution, the degree and location of demagnetization, and damaged locations. The magnetization estimation device 10 estimates the magnetization state of the permanent magnets 24 while, for example, rotating the rotor of the IPMSM 20 loaded with the permanent magnets 24. The magnetization estimation device 10 is disposed in a state electrically connected to the IPMSM 20 so as to be able to acquire a signal waveform of an induced electromotive force generated in the IPMSM 20. The magnetization estimation device 10 nondestructively estimates the magnetization state of the permanent magnets 24 by measuring a first induced electromotive force induced by the permanent magnets 24.

[0024] The magnetization estimation device 10 includes a measurement unit 11 that measures, for example, a first induced electromotive force induced by a permanent magnet 24 as a magnetic body on which the permanent magnet 24 is loaded rotates. The measurement unit 11 includes a multi-phase armature winding 11a that is continuously arranged along the outer periphery of a magnetic body in a stator that surrounds a rotor core 22 serving as a magnetic body. For example, the armature winding 11a constitutes three phases: a U phase, a V phase, and a W phase. The armature winding 11a that is arranged so as to surround the four permanent magnets 24 by 360° constitutes, for example, a U phase (negative), a U phase (negative), a V phase (positive), a V phase (positive), a W phase (negative), a W phase (negative), a U phase (positive), a U phase (positive), a V phase (negative), a V phase (negative), a W phase (positive), and a W phase (positive) in this order in a clockwise direction. The armature windings 11a have the same configuration every 180° around the four permanent magnets 24.

[0025] 2 is a block diagram showing an example of the configuration of the magnetization estimation device 10 of FIG. 1. As shown in FIG. 2, the magnetization estimation device 10 includes, in addition to a measurement unit 11, a storage unit 12, an input unit 13, an output unit 14, and a control unit 15. The storage unit 12, the input unit 13, the output unit 14, and the control unit 15 may be included in any general-purpose electronic device, such as a personal computer (PC), a tablet PC, a smartphone, or a smartwatch, used by a user who estimates the magnetization state of the permanent magnet 24 using the magnetization estimation device 10. Without being limited thereto, the storage unit 12, the input unit 13, the output unit 14, and the control unit 15 may be included in one or more server devices that can communicate with each other, or may be included in another electronic device dedicated to estimating the magnetization state of the permanent magnet 24.

[0026] The storage unit 12 is, for example, a semiconductor memory, a magnetic memory, an optical memory, or the like, but is not limited to these. The storage unit 12 functions as a main storage module, an auxiliary storage module, or a cache memory. The storage unit 12 stores any information necessary to realize the operation of the magnetization estimation device 10. The storage unit 12 stores any information obtained by the operation of the magnetization estimation device 10. For example, the storage unit 12 stores a system program, an application program, and various information calculated by the control unit 15. The storage unit 12 is not limited to being built into the magnetization estimation device 10, and may include an external storage module connected via a digital input / output port such as a USB (Universal Serial Bus).

[0027] The input unit 13 includes one or more input interfaces that detect user input and acquire input information based on the user's operation. The input interfaces include physical keys, capacitive keys, a touch screen that is integrated with the display of the output unit 14, an imaging module such as a camera, and a microphone that accepts audio input.

[0028] The output unit 14 includes one or more output interfaces that output information to provide it to the user, such as a display that visually outputs information as an image, a speaker, earphones, and headphones that audibly outputs information as sound, and a vibrator that tactilely outputs information as vibration.

[0029] The control unit 15 includes one or more processors. In the present disclosure, a "processor" refers to, but is not limited to, a general-purpose processor or a dedicated processor specialized for a specific process. The control unit 15 includes, for example, a CPU (Central Processing Unit). The control unit 15 is communicably connected to each component of the magnetization estimation device 10 and controls the overall operation of the magnetization estimation device 10.

[0030] The control unit 15 estimates the state of magnetization of the permanent magnet 24 when the first induced electromotive force is induced using a magnetization estimation algorithm based on the first induced electromotive force measured by the measurement unit 11. The control unit 15 has a plurality of functional blocks corresponding to the respective steps of the magnetization estimation algorithm.

[0031] Fig. 3 is a functional block diagram mainly showing an example of the configuration of the control unit 15 in Fig. 2. With reference to Fig. 3, the functional blocks of the control unit 15 corresponding to each step of the magnetization estimation algorithm will be mainly described.

[0032] First, while controlling the measurement unit 11, the control unit 15 measures the first induced electromotive force induced in the armature winding 11a by the permanent magnet 24 as the magnetic body rotates. As a result, the control unit 15 acquires the first induced electromotive force V0(t) measured by the measurement unit 11 as information on a voltage waveform that changes over time. As an example, the first induced electromotive force V0(t) may be a no-load induced electromotive force.

[0033] The magnetization generation unit 151 of the control unit 15 generates a tentative magnetization distribution as an initial distribution by simulation, which is a vector including three numerical values ​​corresponding to the x-coordinate, y-coordinate, and z-coordinate in the Cartesian coordinate system. k (k=0) is obtained by generating the same number of data points on the permanent magnet 24 by simulation, i.e., the same number of cells inside the permanent magnet 24. k is the repetition number in the simulation, i.e., the number of iterations. Note that the provisional magnetization distribution may be expressed based on polar coordinates, cylindrical coordinates, etc. instead of Cartesian coordinates.

[0034] The electromagnetic field calculation unit 152 of the control unit 15 calculates a magnetic field based on the provisional magnetization distribution generated by simulation in the magnetization generation unit 151, by electromagnetic field analysis that takes into account magnetic nonlinearity. For example, when calculating a magnetic field from a model that includes magnetic field sources such as an iron core or permanent magnet and excitation current, numerical analysis methods such as the finite element method and magnetic moment method are used as electromagnetic field analysis methods that can take into account the magnetic nonlinearity of the iron core. The magnetic field is a vector containing three numerical values ​​along three axes in a Cartesian coordinate system.

[0035] For example, the magnetic field is calculated based on the following nonlinear equation:

number

[0036] The line voltage calculation unit 153 of the control unit 15 uses the magnetic vector potential A calculated from Equation 1 based on the finite element method or the like to calculate the interlinkage magnetic flux Φ of the windings in each of the U-phase, V-phase, and W-phase in the armature winding 11a according to the following Equation 2.

number

[0037] The line voltage calculation unit 153 calculates the induced electromotive force V(t) of each phase according to Faraday's law of electromagnetic induction using the interlinkage magnetic flux Φ calculated for each phase according to Equation 2. The line voltage calculation unit 153 calculates the line voltage based on the induced electromotive force V(t) of each phase. For example, the line voltage calculation unit 153 calculates the line voltage V between the U phase and the V phase. UV When calculating (t), the induced electromotive force V of the U phase U From (t), the induced electromotive force V of the V phase V Subtract (t).

[0038] The objective function calculation unit 154 of the control unit 15 calculates an objective function including the difference between the first induced electromotive force V0(t) measured by the measurement unit 11 and the second induced electromotive force based on the magnetization distribution generated by simulation. The control unit 15 estimates the magnetization state of the permanent magnet 24 by solving an optimization problem based on the calculated objective function in a magnetization estimation algorithm. In the present disclosure, the "second induced electromotive force" is, for example, the above-mentioned line voltage calculated by the line voltage calculation unit 153. The second induced electromotive force may be a line voltage between different phases. For example, the second induced electromotive force may be a no-load induced electromotive force. The first induced electromotive force V0(t) is a target line voltage at time t actually measured by the measurement unit 11.

[0039] The objective function W is roughly expressed by the following equation 3, for example. In equation 3, as an example, the line voltage V between the U phase and the V phase is UV (t) is used as the second induced electromotive force.

number

[0040] In the magnetization estimation algorithm, the control unit 15 estimates the magnetization state of the permanent magnet 24 by solving an optimization problem that minimizes the objective function W as shown in Equation 3. At this time, the control unit 15 estimates the magnetization state of the permanent magnet 24 by solving the optimization problem that minimizes the objective function W as shown in Equation 3. In this optimization problem, the control unit 15 calculates M x , M y、 M z is set as a design variable. The control unit 15 finally calculates the distribution of magnetization vectors M set for all finite elements in the area of ​​the permanent magnet 24 so as to minimize the objective function W. Hereinafter, the distribution of magnetization vectors M will be referred to as "magnetization distribution M."

[0041] The correction amount calculation unit 155 of the control unit 15 calculates the amount of correction of the magnetization distribution M by an optimization method based on the objective function W calculated by the objective function calculation unit 154. Such a correction amount is calculated based on the gradient of the objective function W. The correction amount calculation unit 155 calculates the amount of correction of the magnetization distribution M by an optimization method based on the gradient of the objective function W. The correction amount calculation unit 155 calculates the amount of correction of the magnetization distribution M by an optimization method based on the gradient of the objective function W. x , M y、 M z A solution search is performed using the gradient ∂W / ∂M with respect to

[0042] When calculating the gradient ∂W / ∂M, care must be taken to avoid the fact that using numerical differentiation can result in a decrease in calculation accuracy due to cancellation errors and an extreme increase in calculation time. Therefore, the correction amount calculation unit 155 calculates the gradient ∂W / ∂M of the objective function W using the adjoint variable method, which can take into account the magnetic nonlinearity of the iron core and can calculate ∂W / ∂M with high accuracy at a calculation cost comparable to that of numerical analysis methods such as the finite element method used in forward problems.

[0043] For example, the correction amount calculation unit 155 calculates the magnetization M based on the gradient ∂W / ∂M obtained by the adjoint variable method. k The correction amount δM k When the magnetization distribution M asymptotically approaches the actual magnetization distribution of the permanent magnet 24, the objective function W becomes smaller and the amount of correction of the magnetization distribution M also becomes smaller.

[0044] The update unit 156 of the control unit 15 updates the magnetization distribution M based on the correction amount calculated by the correction amount calculation unit 155 for the magnetization distribution M generated by simulation in the magnetization generation unit 151. The update unit 156 updates the magnetization vector M from the correction amount δM of the magnetization vector M of each finite element by applying mathematical programming to the gradient ∂W / ∂M obtained by the adjoint variable method. Mathematical programming includes, for example, the steepest descent method and the quasi-Newton method. The update unit 156 uses, as an example, an update equation based on the steepest descent method, as shown in Equation 4.

[0045]

number

[0046] The convergence determination unit 157 of the control unit 15 terminates the magnetization estimation algorithm when a predetermined condition is satisfied. On the other hand, when the predetermined condition is not satisfied, the convergence determination unit 157 of the control unit 15 moves to the magnetization generation unit 151 and repeats the magnetization estimation algorithm. In the present disclosure, the "predetermined condition" refers to, for example, when the number of iterations k is specified. max The first condition is that the objective function W k The first condition is that k is smaller than the allowable value ε. For example, the convergence determination unit 157 of the control unit 15 determines whether k is smaller than the allowable value ε. max For example, the convergence determination unit 157 of the control unit 15 determines whether W k When ε<ε, the magnetization estimation algorithm is terminated. At this time, a magnetization distribution M close to the actual magnetization distribution of the permanent magnet 24 is obtained.

[0047] When the control unit 15 ends the magnetization estimation algorithm, it outputs the estimation result of the magnetization state of the permanent magnet 24 obtained by the magnetization estimation algorithm to the output unit 14. For example, the control unit 15 may display on the display of the output unit 14 a distribution map, a graph, or the like that compares the actual magnetization distribution immediately after the permanent magnet 24 is magnetized with the magnetization distribution M after aging that is estimated by the magnetization estimation algorithm.

[0048] Fig. 4 is a flowchart for explaining an example of a magnetization estimation method executed by the magnetization estimation device 10 of Fig. 2. With reference to Fig. 4, an example of the magnetization estimation method executed by the magnetization estimation device 10 of Fig. 2 for estimating the magnetization state of the permanent magnet 24 loaded on a magnetic body will be mainly described.

[0049] In step S100, the control unit 15 of the magnetization estimation device 10 causes the measurement unit 11 to measure the first induced electromotive force V0(t) induced by the permanent magnet 24 as the magnetic body rotates. The control unit 15 applies mechanical energy to the IPMSM 20 to rotate the rotor when the measurement unit 11 measures the first induced electromotive force V0(t). Because the rotor is loaded with the permanent magnet 24 whose magnetization state is to be estimated, the flux linkage of the armature winding 11a arranged in the stator changes over time as the rotor rotates. The measurement unit 11 measures the first induced electromotive force V0(t) induced in the armature winding 11a.

[0050] In the following, the control unit 15 of the magnetization estimation device 10 uses the measured first induced electromotive force V0(t) as an input value and estimates, by mathematical programming, the magnetization state of the permanent magnet 24 such that the second induced electromotive force calculated by the finite element method asymptotically approaches V0(t).

[0051] In step S101, the magnetization generation unit 151 of the control unit 15 generates, by simulation, a tentative magnetization distribution as an initial distribution for the actual magnetization distribution of the permanent magnet 24 when the first induced electromotive force V0(t) obtained in step S100 is obtained.

[0052] In step S102, the electromagnetic field calculation unit 152 of the control unit 15 calculates a magnetic field based on the provisional magnetization distribution generated in step S101 by electromagnetic field analysis taking into account magnetic nonlinearity.

[0053] In step S103, the line voltage calculation unit 153 of the control unit 15 calculates the line voltage based on the finite element method or the like.

[0054] In step S104, the objective function calculation unit 154 of the control unit 15 calculates an objective function W including the difference between the first induced electromotive force V0(t) measured in step S100 and the second induced electromotive force based on the magnetization distribution generated in step S101.

[0055] In step S105, the correction amount calculation unit 155 of the control unit 15 calculates the gradient ∂W / ∂M of the objective function W calculated in step S104.

[0056] In step S106, the correction amount calculation unit 155 of the control unit 15 calculates the amount of correction of the magnetization distribution M by an optimization method based on the gradient ∂W / ∂M calculated in step S105.

[0057] In step S107, the update unit 156 of the control unit 15 updates the magnetization distribution M generated by simulation in step S101 based on the correction amount calculated in step S106.

[0058] In step S108, the convergence determination unit 157 of the control unit 15 determines whether or not a predetermined condition is satisfied. If the control unit 15 determines that the predetermined condition is satisfied, it ends the magnetization estimation algorithm including the above steps and executes the process of step S109. If the control unit 15 determines that the predetermined condition is not satisfied, it returns to step S102 and repeats the magnetization estimation algorithm based on the magnetization distribution M updated in step S107.

[0059] In step S109, when the control unit 15 ends the magnetization estimation algorithm in step S108, the control unit 15 outputs to the output unit 14 the estimation result of the magnetization state of the permanent magnet 24 obtained by the magnetization estimation algorithm.

[0060] Specific examples of results when the magnetization estimation device 10 estimates the magnetization state of a permanent magnet 24 loaded on a magnetic body will be described. First, a first example of the results will be described. In the first example, the target permanent magnet 24 is a neodymium magnet. The magnetization strength of the permanent magnet 24 is 0.625 T and it is in a demagnetized state. The orientation of the permanent magnet 24 is parallel magnetized.

[0061] 5A is a schematic diagram showing a target magnetization distribution to be compared with the estimation result by the magnetization estimation device 10 of FIG. 2. FIG. 5A is a diagram seen from above, focusing on the four permanent magnets 24 loaded on the rotor core 22 of the IPMSM 20 of FIG. 1. FIG. 5A shows the magnetization distribution of the permanent magnets 24. In FIG. 5A, the magnitude of magnetization is represented by shades of color. The darker the color, the larger the absolute value of the magnetization, and the lighter the color, the smaller the absolute value of the magnetization. The magnetization distribution shown in FIG. 5A is obtained by simulating the actual magnetization distribution of the permanent magnets 24 based on input data acquired by, for example, the input unit 13.

[0062] Fig. 5B is a graph showing the time waveform of the first induced electromotive force V0(t) obtained due to the magnetization distribution shown in Fig. 5A. The control unit 15 of the magnetization estimation device 10 uses the first induced electromotive force V0(t) shown in Fig. 5B as a target waveform for the objective function W shown in Equation 3.

[0063] Fig. 5C is a schematic diagram showing an initial distribution in a simulation by the control unit 15 of Fig. 2. Fig. 5C shows the initial distribution of a tentative magnetization distribution M generated by simulation in the magnetization generation unit 151 of the control unit 15. Fig. 5C corresponds to Fig. 5A, and the same explanation applies. The control unit 15 of the magnetization estimation device 10 uses the magnetization distribution M shown in Fig. 5C as an initial value for the steepest descent method, i.e., as the initial magnetization distribution.

[0064] 5D is a graph showing the time waveform of the second induced electromotive force obtained due to the magnetization distribution M shown in FIG. 5C. In FIG. 5D, the line voltage V UV 5D is used for the objective function W shown in Equation 3. When the time waveform of the second induced electromotive force shown in FIG. 5D is compared with the time waveform of the first induced electromotive force V0(t) shown in FIG. 5B, it can be seen that the voltage value of the second induced electromotive force is generally significantly different from the voltage value of the first induced electromotive force V0(t).

[0065] FIG. 5E is a schematic diagram showing a first example of the estimation results output to the output unit 14 in FIG. 2. FIG. 5E corresponds to FIG. 5A, and the same explanation applies. FIG. 5E shows the magnetization distribution M obtained by iterative calculation using the steepest descent method. Comparing FIG. 5E with FIG. 5A, it can be seen that the magnetization distribution M of all permanent magnets 24 converges to the target magnetization distribution.

[0066] 5F is a graph mainly showing a time waveform W1 of the second induced electromotive force obtained due to the magnetization distribution M shown in FIG. 5E. In FIG. 5F, the line voltage V UV FIG. 5F also shows the time waveform W2 of the first induced electromotive force V0(t) shown in FIG. 5B. FIG. 5F also shows the time waveform W3 of the initial second induced electromotive force shown in FIG. 5D. FIG. 5F also shows the time waveform W4 of the second induced electromotive force calculated during the iterative calculation using the steepest descent method. As shown in FIG. 5F, it can be seen that the time waveform W1 of the second induced electromotive force asymptotically approaches the time waveform W2 of the target first induced electromotive force V0(t) as the iterative calculation using the mathematical programming method is performed.

[0067] Figure 5G is a graph showing how the value of the objective function W changes with the number of iterations k. As shown in Figure 5G, it can be seen that the value of the objective function W steadily decreases with repeated calculations by mathematical programming.

[0068] The magnetization estimation device 10 uses a magnetization distribution based on input data such as that shown in Fig. 5A to estimate the magnetization state of the permanent magnet 24 based on an initial distribution such as that shown in Fig. 5C as a result such as that shown in Fig. 5E. The target magnetization distribution shown in Fig. 5A and the magnetization distribution M in the estimation result shown in Fig. 5E are very similar to each other. Therefore, the magnetization estimation device 10 can accurately estimate the magnetization distribution of the permanent magnet 24.

[0069] Next, a second example of the estimation results will be described. In the second example, the target permanent magnet 24 is a neodymium magnet. The magnetization strength of the permanent magnet 24 is 1.25 T, and it is in a state immediately after post-magnetization. The orientation of the permanent magnet 24 is parallel magnetization.

[0070] 6A is a schematic diagram showing a target magnetization distribution to be compared with the estimation result by the magnetization estimation device 10 of FIG. 2. FIG. 6A is a diagram seen from above, focusing on the four permanent magnets 24 loaded on the rotor core 22 of the IPMSM 20 of FIG. 1. FIG. 6A shows the magnetization distribution of the permanent magnets 24. In FIG. 6A, the magnitude of magnetization is represented by shades of color. The darker the color, the greater the absolute value of the magnetization, and the lighter the color, the smaller the absolute value of the magnetization. The magnetization distribution shown in FIG. 6A is obtained by simulating the actual magnetization distribution of the permanent magnets 24 based on input data acquired by, for example, the input unit 13.

[0071] Fig. 6B is a graph showing the time waveform of the first induced electromotive force V0(t) obtained due to the magnetization distribution shown in Fig. 6A. The control unit 15 of the magnetization estimation device 10 uses the first induced electromotive force V0(t) shown in Fig. 6B as a target waveform for the objective function W shown in Equation 3.

[0072] Fig. 6C is a schematic diagram showing an initial distribution in a simulation by the control unit 15 of Fig. 2. Fig. 6C shows the initial distribution of a tentative magnetization distribution M generated by simulation in the magnetization generation unit 151 of the control unit 15. Fig. 6C corresponds to Fig. 6A, and the same explanation applies. The control unit 15 of the magnetization estimation device 10 uses the magnetization distribution M shown in Fig. 6C as an initial value for the steepest descent method, i.e., as the initial magnetization distribution.

[0073] 6D is a graph showing the time waveform of the second induced electromotive force obtained due to the magnetization distribution M shown in FIG. 6C. In FIG. 6D, the line voltage V UV6D is used for the objective function W shown in Equation 3. When the time waveform of the second induced electromotive force shown in FIG. 6D is compared with the time waveform of the first induced electromotive force V0(t) shown in FIG. 6B, it can be seen that the voltage value of the second induced electromotive force is generally significantly different from the voltage value of the first induced electromotive force V0(t).

[0074] FIG. 6E is a schematic diagram showing a second example of the estimation results output to the output unit 14 in FIG. 2. FIG. 6E corresponds to FIG. 6A, and the same explanation applies. FIG. 6E shows the magnetization distribution M obtained by iterative calculation using the steepest descent method. Comparing FIG. 6E with FIG. 6A, it can be seen that the magnetization distribution M of all permanent magnets 24 converges to the target magnetization distribution.

[0075] 6F is a graph mainly showing a time waveform W1 of the second induced electromotive force obtained due to the magnetization distribution M shown in FIG. 6E. In FIG. 6F, the line voltage V UV FIG. 6F also shows the time waveform W2 of the first induced electromotive force V0(t) shown in FIG. 6B. FIG. 6F also shows the time waveform W3 of the initial second induced electromotive force shown in FIG. 6D. FIG. 6F also shows the time waveform W4 of the second induced electromotive force calculated during the iterative calculation using the steepest descent method. As shown in FIG. 6F, it can be seen that the time waveform W1 of the second induced electromotive force asymptotically approaches the time waveform W2 of the target first induced electromotive force V0(t) as the iterative calculation using the mathematical programming method is performed.

[0076] Figure 6G is a graph showing how the value of the objective function W changes with the number of iterations k. As shown in Figure 6G, it can be seen that the value of the objective function W steadily decreases with repeated calculations by mathematical programming.

[0077] The magnetization estimation device 10 uses a magnetization distribution based on input data such as shown in Fig. 6A to estimate the magnetization state of the permanent magnet 24 as a result shown in Fig. 6E based on an initial distribution such as shown in Fig. 6C. The target magnetization distribution shown in Fig. 6A and the magnetization distribution M in the estimation result shown in Fig. 6E are very similar to each other. Therefore, the magnetization estimation device 10 can accurately estimate the magnetization distribution of the permanent magnet 24, similar to the estimation results when the permanent magnet 24 is in a demagnetized state shown in Figs. 5A to 5G.

[0078] According to the above embodiment, as shown in, for example, FIGS. 5E and 6E, it is possible to directly estimate the magnetization state of the permanent magnet 24 loaded on a magnetic body. The magnetization estimation device 10 estimates the magnetization state of the permanent magnet 24 when the first induced electromotive force V0(t) is induced using a magnetization estimation algorithm based on the first induced electromotive force V0(t) measured by the measurement unit 11. This allows the magnetization estimation device 10 to directly evaluate the magnetization state of the permanent magnet 24 based on the measured value of the first induced electromotive force V0(t). Therefore, the user can accurately grasp the magnetization state of the permanent magnet 24 by checking the estimation result output to the output unit 14 of the magnetization estimation device 10, for example.

[0079] The magnetization estimation device 10 can more specifically estimate deterioration information of the permanent magnet 24, including demagnetization and damaged locations of the permanent magnet 24. For example, the magnetization estimation device 10 can more specifically estimate deterioration information of the permanent magnet 24 by comparing the estimated magnetization distribution M with the magnetization distribution of the permanent magnet 24 immediately after magnetization. The magnetization estimation device 10 can nondestructively estimate the magnetization state of the permanent magnet 24 based on the first induced electromotive force V0(t) in a state in which the permanent magnet 24 is loaded in the IPMSM 20.

[0080] As described above, the magnetization estimation device 10 can easily estimate the demagnetization and damaged portions of the permanent magnets 24 over time, thereby contributing to the effective use of the permanent magnets 24. As a result, the magnetization estimation device 10 enables the maintenance management of the IPMSM 20 used in, for example, an EV, and can contribute to extending the life of the IPMSM 20 and the EV itself. For example, the magnetization estimation device 10 can nondestructively detect the permanent magnets 24 in which irreversible demagnetization has occurred, and can prompt the user to perform maintenance management such as removing the demagnetized permanent magnet 24 from the IPMSM 20, remagnetizing it, and reloading it into the IPMSM 20.

[0081] Even if it is not easy to remove only the demagnetized permanent magnets 24 from the IPMSM 20, the magnetization estimation device 10 can urge the user to perform maintenance such as removing the entire rotor including the rotor core 22, the shaft 23, and the permanent magnets 24 from the IPMSM 20, remagnetizing the entire rotor, and reloading it into the IPMSM 20. As described above, the magnetization estimation device 10 can prevent the depletion of rare metals due to the reuse of rare earths.

[0082] Additionally, the magnetization estimation device 10 is applicable not only to magnetization testing after re-magnetization, but also to magnetization testing after magnetization of the permanent magnets 24 during the manufacture of the IPMSM 20. The magnetization estimation device 10 can easily test the accuracy of magnetization even in such post-assembly magnetization after assembling a rotor including the permanent magnets 24 by estimating the magnetization state, such as the magnetization distribution, of the permanent magnets 24. As described above, the magnetization estimation device 10 can also estimate locations with inhomogeneous magnetization distribution that may occur in the permanent magnets 24 during post-assembly magnetization. The magnetization estimation device 10 can also non-destructively and quickly estimate the magnetization quality of the permanent magnets 24 during post-assembly magnetization.

[0083] As a result, a user can input the deteriorated magnetization distribution M of the permanent magnet 24 into electromagnetic field analysis software, for example, to have the device predict motor performance in a demagnetized state. The magnetization estimation device 10 can be configured by implementing only the functions of the control unit 15 in a general-purpose electronic device such as a PC, as long as it has a measurement unit 11 that measures the first induced electromotive force V0(t). Therefore, the magnetization estimation device 10 can reduce increases in costs other than software development costs.

[0084] In a magnetization estimation algorithm, the magnetization estimation device 10 estimates the magnetization state of the permanent magnet 24 by solving an optimization problem based on an objective function W including the difference between the first induced electromotive force V0(t) and the second induced electromotive force. This allows the magnetization estimation device 10 to accurately estimate the magnetization state of the permanent magnet 24. For example, the magnetization estimation device 10 can accurately generate, in a simulation, a magnetization distribution M that is close to the actual magnetization distribution of the permanent magnet 24 for which the first induced electromotive force V0(t) is measured by the measurement unit 11. As a result, the magnetization estimation device 10 can also estimate deterioration information of the permanent magnet 24 with higher accuracy.

[0085] In the magnetization estimation algorithm, the magnetization estimation device 10 calculates the amount of correction of the magnetization distribution M generated by simulation and updates the magnetization distribution M, thereby generating, in simulation, a magnetization distribution M that is close to the actual magnetization distribution of the permanent magnet 24. As a result, the magnetization estimation device 10 can also estimate deterioration information of the permanent magnet 24 with higher accuracy.

[0086] The magnetization estimation device 10 calculates the gradient ∂W / ∂M of the objective function W and calculates the correction amount by an optimization method, thereby generating in a simulation a magnetization distribution M that is close to the actual magnetization distribution of the permanent magnet 24. As a result, the magnetization estimation device 10 can also estimate deterioration information of the permanent magnet 24 with higher accuracy.

[0087] The magnetization estimation device 10 can reduce the occurrence of unphysical solutions in the magnetization estimation algorithm by calculating the gradient ∂W / ∂M of the objective function W using the adjoint variable method. This allows the magnetization estimation device 10 to estimate the magnetization state of the permanent magnet 24 with high accuracy. As a result, the magnetization estimation device 10 can also estimate deterioration information of the permanent magnet 24 with higher accuracy.

[0088] When the objective function W becomes less than the allowable value ε, the magnetization estimation device 10 terminates the magnetization estimation algorithm, thereby finally generating, by repeating the magnetization estimation algorithm, a magnetization distribution M that is close to the actual magnetization distribution of the permanent magnet 24. As a result, the magnetization estimation device 10 can also estimate deterioration information of the permanent magnet 24 with higher accuracy.

[0089] The magnetization estimation device 10 can realize a magnetization estimation method that takes magnetic nonlinearity into account by calculating a magnetic field from the magnetization distribution M generated by simulation using electromagnetic field analysis that takes magnetic nonlinearity into account. Typically, the stator and rotor of an IPMSM 20 almost always include an iron core that has material nonlinearity. The magnetization estimation device 10 can estimate the magnetization state of the permanent magnet 24 by taking into account the magnetic nonlinearity of the iron core in such a magnetic circuit. Therefore, the magnetization estimation device 10 can also estimate the magnetization state of the permanent magnet 24 when the permanent magnet 24 is loaded in the IPMSM 20.

[0090] The magnetization estimation device 10 can estimate the magnetization state of the permanent magnet 24 with high accuracy by using a higher order of discretization used in the electromagnetic field analysis, for example, a method using high-order nodal elements and high-order edge elements in the case of the finite element method, and an approximation method such as a homogenization method that can model the laminated electromagnetic steel sheets of the IPMSM 20 with high accuracy.

[0091] In the magnetization estimation device 10, the measurement unit 11 includes a multi-phase armature winding 11a that is continuously arranged along the outer periphery of the magnetic body in a stator that surrounds the periphery of the magnetic body, so that it is also possible to arrange windings around the permanent magnets 24 that are loaded on the magnetic body. For example, as shown in FIG. 1 , the magnetization estimation device 10 can also arrange windings to surround the periphery of the permanent magnets 24 by 360°. This allows the magnetization estimation device 10 to calculate the line voltages using all the magnetization vectors M in the multiple permanent magnets 24. Therefore, the magnetization estimation device 10 can accurately estimate a magnetization distribution that is uniform across the multiple permanent magnets 24.

[0092] The magnetization estimation device 10 outputs the estimation result of the magnetization state of the permanent magnet 24 obtained by the magnetization estimation algorithm to the output unit 14, thereby making it possible to easily visualize the magnetization distribution of the permanent magnet 24 without destroying the permanent magnet 24. This facilitates the task of estimating the magnetization state of the permanent magnet 24 using the magnetization estimation device 10, improving convenience for the user of the magnetization estimation device 10.

[0093] Although the present disclosure has been described based on the drawings and examples, it should be noted that those skilled in the art can make various modifications and alterations based on the present disclosure. Therefore, it should be noted that these modifications and alterations are included in the scope of the present disclosure. For example, the functions included in each configuration or step can be rearranged so as not to be logically inconsistent, and multiple configurations or steps can be combined or divided into one.

[0094] For example, the shape, pattern, size, arrangement, orientation, type, number, etc. of each of the above-described components are not limited to the above description and the illustrations in the drawings, and may be configured arbitrarily as long as the function can be realized.

[0095] For example, a general-purpose electronic device such as a smartphone or a computer can be configured to function as the magnetization estimation device 10 according to the above-described embodiment. Specifically, a program describing processing content for realizing each function of the magnetization estimation device 10 according to the embodiment is stored in a memory of the electronic device, and the program is read and executed by a processor of the electronic device. Therefore, the disclosure according to an embodiment can also be realized as a program executable by a processor.

[0096] Alternatively, the disclosure according to an embodiment may be realized as a non-transitory computer-readable medium storing a program executable by one or more processors to cause the magnetization estimation device 10 according to the embodiment or the like to execute each function. It should be understood that these are also included within the scope of the present disclosure.

[0097] In the above embodiment, the magnetization estimation device 10 estimates the magnetization state of the permanent magnet 24 by solving an optimization problem based on an objective function W including the difference between the first induced electromotive force V0(t) and the second induced electromotive force in the magnetization estimation algorithm, but the present invention is not limited to this. The magnetization estimation device 10 may estimate the magnetization state of the permanent magnet 24 when the first induced electromotive force V0(t) measured by the measurement unit 11 is induced using any other magnetization estimation algorithm as long as it is possible to directly estimate the magnetization state of the permanent magnet 24 loaded on a magnetic body.

[0098] In the above embodiment, the magnetization estimation device 10 calculates the amount of correction of the magnetization distribution M generated by simulation in the magnetization estimation algorithm, and updates the magnetization distribution M. However, the present invention is not limited to this. The magnetization estimation device 10 may update the magnetization distribution M by any method in the other magnetization estimation algorithms described above.

[0099] In the above embodiment, the magnetization estimation device 10 calculates the gradient of the objective function W and calculates the correction amount by an optimization method, but this is not limiting. When calculating the correction amount, the magnetization estimation device 10 may use an evolutionary algorithm such as a genetic algorithm instead of or in addition to a mathematical programming method that uses the gradient ∂W / ∂M of the objective function W, such as the steepest descent method or the quasi-Newton method. The magnetization estimation device 10 may also use AI (Artificial Intelligence) technology such as a neural network and deep learning.

[0100] In the above embodiment, the magnetization estimation device 10 calculates the gradient ∂W / ∂M of the objective function W using the adjoint variable method to derive the physical magnetization distribution M. However, this is not limiting. The magnetization estimation device 10 may calculate the gradient ∂W / ∂M of the objective function W based on any other method other than the adjoint variable method. Alternatively, the magnetization estimation device 10 may use any constraint function in the magnetization estimation algorithm to derive a more physical magnetization distribution M that satisfies the constraint conditions. For example, the magnetization estimation device 10 may additionally use constraint conditions related to the magnetic flux in the air gap between the rotor core 22 as a magnetic body and the stator core 21 as a stator, the magnetic flux in a specific region within the core, and the like.

[0101] In the above embodiment, the "predetermined condition" is, for example, the number of repetitions k. max The first condition is that the objective function W k Although the above description has been given to include an OR condition in which the objective function W is combined with the second condition that W is less than the allowable value ε, the present invention is not limited to this. For example, the predetermined condition may include only the second condition without including the first condition. That is, the magnetization estimation device 10 calculates the objective function W by k The magnetization estimation algorithm may be terminated only when ε is less than the tolerance value ε.

[0102] In the above embodiment, the magnetization estimation device 10 calculates the magnetic field from the magnetization distribution M generated by simulation by electromagnetic field analysis that takes magnetic nonlinearity into consideration, but the present invention is not limited to this. The magnetization estimation device 10 may calculate the magnetic field from the magnetization distribution M generated by simulation by any other analysis that does not take magnetic nonlinearity into consideration.

[0103] In the above embodiment, the measurement unit 11 is described as including a multi-phase armature winding 11a that is continuously arranged along the outer periphery of the magnetic body in a stator that surrounds the periphery of the magnetic body, but this is not limited to this. The measurement unit 11 may be embedded inside the stator core 21. The measurement unit 11 may measure the first induced electromotive force V0(t) while embedded inside the stator core 21.

[0104] In the above embodiment, the permanent magnet 24 is described as being embedded inside the rotor core 22, but this is not limiting. The permanent magnet 24 may be embedded inside the stator core 21 instead of the rotor core 22. In this case, the measuring unit 11 may be disposed in the rotor instead of the stator. For example, the armature winding 11a may be disposed in the rotor core 22 instead of the stator core 21.

[0105] Fig. 7 is a configuration diagram illustrating a schematic example of a part of the configuration of a magnetization estimation system 1 including a magnetization estimation device 10 according to a first modified example of the present disclosure. For the purpose of simplifying the illustration, Fig. 7 omits the illustration of the storage unit 12, input unit 13, output unit 14, and control unit 15 described above with reference to Fig. 2. Regarding the magnetization estimation device 10, only the configuration of the measurement unit 11 is illustrated.

[0106] The measurement unit 11 of the magnetization estimation device 10 may further include a pickup coil 11b in addition to or instead of the multi-phase armature windings 11a that are continuously arranged along the outer periphery of the magnetic body in the stator surrounding the rotor core 22 as a magnetic body. The pickup coil 11b of the measurement unit 11 is arranged in the air gap G between the rotor core 22 as a magnetic body and the stator core 21 as a stator. Although FIG. 7 illustrates both the armature winding 11a and the pickup coil 11b as an example of the configuration of the measurement unit 11, the measurement unit 11 may include only either the armature winding 11a or the pickup coil 11b.

[0107] The magnetization estimation device 10 includes a pickup coil 11b in the measurement unit 11, which allows local measurement of the first induced electromotive force V0(t), unlike the armature winding 11a that surrounds the four permanent magnets 24 by 360°. The magnetization estimation device 10 measures the first induced electromotive force V0(t) from the flux linkage in the air gap G and can execute a process of estimating the magnetization state using the first induced electromotive force V0(t). This allows the magnetization estimation device 10 to accurately estimate a magnetization distribution that is non-uniform across the multiple permanent magnets 24. For example, the magnetization estimation device 10 can accurately estimate the magnetization state when demagnetization occurs partially in one permanent magnet 24.

[0108] Fig. 8A is a configuration diagram schematically illustrating a portion of the configuration of a magnetization estimation system 1 including a magnetization estimation device 10 according to a second modified example of the present disclosure. Fig. 8B is an enlarged cross-sectional view of the area enclosed by the two-dot chain line in Fig. 8A. For the purpose of simplifying the illustration, Figs. 8A and 8B omit the illustration of the storage unit 12, input unit 13, output unit 14, and control unit 15 described above with reference to Fig. 2. Regarding the magnetization estimation device 10, only the configuration of the measurement unit 11 is illustrated.

[0109] The magnetization estimation system 1 has a surface permanent magnet synchronous motor (SPMSM) 30 as a target on which a magnetization estimation device 10 according to the second modification is disposed. Similar to the IPMSM 20 of Fig. 7 , the SPMSM 30 has a stator core 21, a rotor core 22, a shaft 23, and permanent magnets 24. Unlike the IPMSM 20 of Fig. 7 , the SPMSM 30 has the permanent magnets 24 attached to the surface of the rotor core 22.

[0110] In the SPMSM 30, four permanent magnets 24 are periodically arranged in the circumferential direction of a rotor core 22, with the center of rotation as the reference. The SPMSM 30 is, for example, a four-pole motor. In the SPMSM 30, an armature winding 11a is arranged so as to surround the four permanent magnets 24 by 360°. In the SPMSM 30, a rotor having a shaft 23 rotates relative to a stator.

[0111] Measurement unit 11 of magnetization estimation device 10 may further include a pickup coil 11b similar to that of the first modified example in addition to or instead of multi-phase armature windings 11a continuously arranged along the outer periphery of a magnetic body in a stator surrounding rotor core 22 as a magnetic body. Pickup coil 11b of measurement unit 11 is arranged in air gap G between rotor core 22 as a magnetic body and stator core 21 as a stator. Magnetization estimation device 10 according to the second modified example estimates the magnetization state of permanent magnet 24 loaded on rotor core 22 as a magnetic body of, for example, SPMSM 30, using pickup coil 11b.

[0112] The material of the pickup coil 11b may include any conductive material. In addition, the circumferential spacing D of the pickup coil 11b shown in FIG. 8B may be determined appropriately depending on the SPMSM 30. The radius R of the coil wire of the pickup coil 11b may be determined appropriately depending on the SPMSM 30. The length L of the pickup coil 11b in the stack thickness direction shown in FIG. 7 may be determined appropriately depending on the SPMSM 30.

[0113] Fig. 8B shows a schematic cross section of each of a pair of coil wires spaced apart in the circumferential direction of the stator in a portion of pickup coil 11b shown in Fig. 7 that is configured to be wider in the circumferential direction of the stator. While Fig. 8B shows both armature winding 11a and pickup coil 11b as an example of the configuration of measurement unit 11, measurement unit 11 may include only pickup coil 11b.

[0114] The magnetization estimation device 10 includes a pickup coil 11b in the measurement unit 11, which allows local measurement of the first induced electromotive force V0(t), unlike the armature winding 11a that surrounds the four permanent magnets 24 by 360°. The magnetization estimation device 10 measures the first induced electromotive force V0(t) from the flux linkage in the air gap G and can execute a process of estimating the state of magnetization using the first induced electromotive force V0(t). As with the magnetization estimation method in the above embodiment, the magnetization estimation device 10 uses the measured first induced electromotive force V0(t) as an input value and estimates, by mathematical programming, the state of magnetization of the permanent magnets 24 such that the second induced electromotive force calculated by the finite element method asymptotically approaches V0(t).

[0115] 9A is a schematic diagram showing a first target magnetization distribution to be compared with the estimation result by the magnetization estimation device 10 according to the second modified example. FIG. 9A is a diagram seen from above, focusing on the four permanent magnets 24 loaded on the rotor core 22 of the SPMSM 30 in FIG. 8A. FIG. 9A shows the magnetization distribution of the uniformly magnetized permanent magnets 24. In FIG. 9A, the magnitude of magnetization is represented by shades of color. The darker the color, the larger the absolute value of the magnetization, and the lighter the color, the smaller the absolute value of the magnetization. The magnetization distribution shown in FIG. 9A is obtained by simulating the actual magnetization distribution of the permanent magnets 24 based on input data acquired by, for example, the input unit 13.

[0116] FIG. 9B is a schematic diagram showing an example of the estimation results output to the output unit 14 in FIG. 2. FIG. 9B corresponds to FIG. 9A, and the same explanation applies. FIG. 9B shows the magnetization distribution M obtained by iterative calculation using the steepest descent method. Comparing FIG. 9B with FIG. 9A, it can be seen that the magnetization distribution M of all permanent magnets 24 converges to the target magnetization distribution. Note that due to the influence of the density of the triangular elements, the magnetization intensity in the magnetization distribution M appears slightly striped.

[0117] 9C is a graph mainly showing a time waveform W1 of the second induced electromotive force resulting from the magnetization distribution M shown in FIG. 9B. In FIG. 9C, the induced electromotive force V of the pickup coil 11b is shown as an example of the second induced electromotive force. P FIG. 9C also shows a time waveform W2 of the first induced electromotive force V0(t). FIG. 9C also shows a time waveform W3 of the initial second induced electromotive force. FIG. 9C also shows a time waveform W4 of the second induced electromotive force calculated during the iterative calculation using the steepest descent method. As shown in FIG. 9C, it can be seen that the time waveform W1 of the second induced electromotive force asymptotically approaches the time waveform W2 of the target first induced electromotive force V0(t) as the iterative calculation using the mathematical programming method is performed.

[0118] FIG. 10A is a schematic diagram showing a second target magnetization distribution to be compared with the estimation result by the magnetization estimation device 10 according to the second modified example. FIG. 10A is a diagram seen from above, focusing on the four permanent magnets 24 loaded on the rotor core 22 of the SPMSM 30 in FIG. 8A. FIG. 10A shows the magnetization distribution of a permanent magnet 24 in which a specific portion is incompletely magnetized. In FIG. 10A, the magnitude of magnetization is represented by shades of color. The darker the color, the larger the absolute value of the magnetization, and the lighter the color, the smaller the absolute value of the magnetization. The magnetization distribution shown in FIG. 10A is obtained by simulating the actual magnetization distribution of the permanent magnet 24 based on input data acquired by, for example, the input unit 13.

[0119] FIG. 10B is a schematic diagram showing an example of the estimation result output to the output unit 14 in FIG. 2. FIG. 10B corresponds to FIG. 10A, and the same explanation applies. FIG. 10B shows the magnetization distribution M obtained by iterative calculation using the steepest descent method. Comparing FIG. 10B with FIG. 10A, it can be seen that the magnetization distribution M of all permanent magnets 24 converges to the target magnetization distribution. It can also be seen that the incomplete magnetized regions of the permanent magnets 24 are reproduced in the estimated magnetization distribution M.

[0120] 10C is a graph mainly showing a time waveform W1 of the second induced electromotive force resulting from the magnetization distribution M shown in FIG. 10B. In FIG. 10C, the induced electromotive force V of the pickup coil 11b is shown as an example of the second induced electromotive force. P FIG. 10C also shows a time waveform W2 of the first induced electromotive force V0(t). FIG. 10C also shows a time waveform W3 of the initial second induced electromotive force. Furthermore, FIG. 10C also shows a time waveform W4 of the second induced electromotive force calculated during the iterative calculation using the steepest descent method.

[0121] As shown in Fig. 10C, it can be seen that the time waveform W1 of the second induced electromotive force gradually approaches the time waveform W2 of the target first induced electromotive force V0(t) as a result of repeated calculations using mathematical programming. Note that times t0 and t1, located at both ends of the horizontal axis in Fig. 10C, correspond to the timing at which the incompletely magnetized portion of permanent magnet 24 passes through pickup coil 11b. The induced electromotive force V at times t0 and t1 P It can be seen that the values ​​of (t) are underestimated compared to the corresponding values ​​at times t0 and t1 in Fig. 9C. The scales of the vertical axes are the same in Fig. 9C and Fig. 10C.

[0122] As described above, the magnetization estimation device 10 can accurately estimate a magnetization distribution that is non-uniform across multiple permanent magnets 24. For example, the magnetization estimation device 10 can accurately estimate the magnetization state when incomplete magnetization occurs partially in one permanent magnet 24.

[0123] Furthermore, the magnetization estimation device 10 can estimate the effect on magnetization distribution of a temperature rise in the permanent magnet 24, which has received particular attention in recent motor design, by utilizing actual experimental data. More specifically, the magnetization estimation device 10 can directly estimate the magnetization distribution of the permanent magnet 24 by placing a pickup coil 11b in the air gap G, measuring the first induced electromotive force V0(t) as the IPMSM 20 is driven, and executing the magnetization estimation method of the present disclosure. That is, the magnetization estimation device 10 can also output the relationship between the heat generation and magnetization distribution of the permanent magnet 24 during operation of the IPMSM 20 to the output unit 14 in real time. Therefore, the magnetization estimation device 10 can extract the thermal demagnetization characteristics of the permanent magnet 24 and allow the user to consider a magnet structure and arrangement position with high heat resistance. Therefore, the magnetization estimation device 10 can contribute to the high-quality design of synchronous motors such as the IPMSM 20.

[0124] In the above embodiment, the magnetization estimation device 10 is described as estimating the magnetization state of the permanent magnet 24 of the IPMSM 20, but the present invention is not limited to this. The magnetization estimation device 10 may be used for any motor other than the IPMSM 20, such as a DC motor or a surface permanent magnet motor. The magnetization estimation device 10 may be used for general electrical equipment equipped with a permanent magnet 24, such as an actuator.

[0125] In the above embodiment, the permanent magnet 24 includes, but is not limited to, a neodymium magnet containing dysprosium. The permanent magnet 24 may also include a samarium-cobalt magnet, a ferrite magnet, etc. The magnetization estimation device 10 is applicable to various permanent magnets 24 loaded into various magnetic circuits and has excellent generalization performance.

[0126] 5E and 6E, the above embodiment has exemplified the distribution map of the magnetization distribution M as the estimation result output to the output unit 14, but the display format of the estimation result output to the output unit 14 is not limited to this. For example, the magnetization estimation device 10 may output the estimation result to the output unit 14 in other display formats such as a graph and a table.

[0127] The present disclosure is applicable to various fields, such as electromagnetic engineering, electrical engineering, non-destructive testing, and environmental energy. The present disclosure is applicable to evaluating the magnetization quality of post-magnetization in synchronous motor production lines. For example, the present disclosure is applicable to evaluating the validity of the magnetization distribution after magnetization in a state where the unmagnetized permanent magnet 24 is loaded in the magnetic circuit during the design process of the IPMSM 20.

[0128] The present disclosure is also applicable to the evaluation of irreversible demagnetization of permanent magnets 24 mounted in high-speed synchronous motors such as those for railway vehicles and EVs. For example, the present disclosure is applicable to inspection of the aging demagnetization of the permanent magnets 24 of an IPMSM 20 during EV inspections. For example, the present disclosure is applicable to inspection after the rotor or stator on which the permanent magnets 24 are mounted is removed and remagnetized after the aging demagnetization of the permanent magnets 24 of an IPMSM 20. For example, the present disclosure is applicable to evaluation of the demagnetization of the permanent magnets 24 after a demagnetization test in the prototype stage of an IPMSM 20.

[0129] The present disclosure can also be applied to extracting magnetization degradation characteristics caused by heat generation while a synchronous motor is being driven. In addition, the present disclosure can also be applied to building a high-quality design system for synchronous motors by making it possible to output the magnetization state estimated by the magnetization estimation device 10 to magnetic field analysis software such as JMAG.

[0130] Some embodiments of the present disclosure will be described below as examples, however, it should be noted that the embodiments of the present disclosure are not limited to these. [Appendix 1] A magnetization estimation device that estimates the magnetization state of a permanent magnet loaded on a magnetic body, a measurement unit that measures a first induced electromotive force induced by the permanent magnet in accordance with the rotation of the magnetic body; a control unit that estimates a magnetization state of the permanent magnet when the first induced electromotive force is induced using a magnetization estimation algorithm based on the first induced electromotive force measured by the measurement unit; Equipped with Magnetization estimation device. [Appendix 2] 10. The magnetization estimation device according to claim 1, the control unit estimates the state of magnetization by solving an optimization problem based on an objective function including a difference between the first induced electromotive force measured by the measurement unit and a second induced electromotive force based on a magnetization distribution generated by simulation in the magnetization estimation algorithm. Magnetization estimation device. [Appendix 3] 3. The magnetization estimation device according to claim 2, the control unit calculates a correction amount of the magnetization distribution generated by the simulation in the magnetization estimation algorithm and updates the magnetization distribution. Magnetization estimation device. [Appendix 4] 4. The magnetization estimation device according to claim 3, the control unit calculates the gradient of the objective function and calculates the correction amount by an optimization method. Magnetization estimation device. [Appendix 5] 5. The magnetization estimation device according to claim 2, wherein: The control unit calculates the gradient of the objective function by an adjoint variable method. Magnetization estimation device. [Appendix 6] 6. The magnetization estimation device according to claim 2, the control unit terminates the magnetization estimation algorithm when the objective function becomes less than a tolerance value. Magnetization estimation device. [Appendix 7] 7. The magnetization estimation device according to claim 2, further comprising: the control unit calculates a magnetic field from the magnetization distribution generated by the simulation by electromagnetic field analysis taking magnetic nonlinearity into consideration. Magnetization estimation device. [Appendix 8] 8. The magnetization estimation device according to claim 2, the measuring unit includes a multi-phase armature winding that is continuously arranged along the outer periphery of the magnetic body in a stator that surrounds the magnetic body, Magnetization estimation device. [Appendix 9] 9. The magnetization estimation device according to claim 8, The second induced electromotive force is a line voltage between different phases. Magnetization estimation device. [Appendix 10] 10. The magnetization estimation device according to claim 8 or 9, The measurement unit includes a pickup coil disposed in an air gap between the magnetic body and the stator. Magnetization estimation device. [Appendix 11] A magnetization estimation method for estimating a magnetization state of a permanent magnet loaded on a magnetic body, comprising: measuring a first induced electromotive force induced by the permanent magnet in association with rotation of the magnetic body; estimating a magnetization state of the permanent magnet when the first induced electromotive force is induced using a magnetization estimation algorithm based on the measured first induced electromotive force; Including, Magnetization estimation method. [Appendix 12] A magnetization estimation device that estimates the magnetization state of a permanent magnet loaded on a magnetic body, measuring a first induced electromotive force induced by the permanent magnet in association with rotation of the magnetic body; estimating a magnetization state of the permanent magnet when the first induced electromotive force is induced using a magnetization estimation algorithm based on the measured first induced electromotive force; performing an action including program. [Explanation of symbols]

[0131] 1. Magnetization estimation system 10 Magnetization estimation device 11 Measuring part 11a Armature winding 11b Pickup coil 12 Storage section 13 Input section 14 Output section 15 Control Unit 151 Magnetization generation part 152 Electromagnetic field calculation section 153 Line voltage calculation unit 154 Objective function calculation unit 155 Correction amount calculation section 156 Update Department 157 Convergence judgment unit 20 IPMSM 21 Stator iron core (stator) 22 Rotor core (magnetic material) 23 Shaft 24 Permanent Magnets 30 SPMSM D interval G void L length R radius W1, W2, W3, W4 time waveform

Claims

1. A magnetization estimation device that estimates the magnetization state of a permanent magnet loaded on a magnetic body, a measurement unit that measures a first induced electromotive force induced by the permanent magnet in accordance with rotation of the magnetic body; a control unit that estimates a magnetization state of the permanent magnet when the first induced electromotive force is induced using a magnetization estimation algorithm based on the first induced electromotive force measured by the measurement unit; Equipped with Magnetization estimation device.

2. The magnetization estimation device according to claim 1 , the control unit estimates the state of magnetization by solving an optimization problem based on an objective function including a difference between the first induced electromotive force measured by the measurement unit and a second induced electromotive force based on a magnetization distribution generated by simulation in the magnetization estimation algorithm. Magnetization estimation device.

3. The magnetization estimation device according to claim 2, the control unit calculates a correction amount of the magnetization distribution generated by the simulation in the magnetization estimation algorithm and updates the magnetization distribution. Magnetization estimation device.

4. The magnetization estimation device according to claim 3, the control unit calculates the gradient of the objective function and calculates the correction amount by an optimization method. Magnetization estimation device.

5. The magnetization estimation device according to any one of claims 2 to 4, The control unit calculates the gradient of the objective function by an adjoint variable method. Magnetization estimation device.

6. The magnetization estimation device according to any one of claims 2 to 4, the control unit terminates the magnetization estimation algorithm when the objective function becomes less than a tolerance value. Magnetization estimation device.

7. The magnetization estimation device according to any one of claims 2 to 4, the control unit calculates a magnetic field from the magnetization distribution generated by the simulation by electromagnetic field analysis taking magnetic nonlinearity into consideration. Magnetization estimation device.

8. The magnetization estimation device according to any one of claims 2 to 4, the measuring unit includes a multi-phase armature winding that is continuously arranged along the outer periphery of the magnetic body in a stator that surrounds the magnetic body, Magnetization estimation device.

9. The magnetization estimation device according to claim 8, The second induced electromotive force is a line voltage between different phases. Magnetization estimation device.

10. The magnetization estimation device according to claim 8, The measurement unit includes a pickup coil disposed in an air gap between the magnetic body and the stator. Magnetization estimation device.

11. A magnetization estimation method for estimating a magnetization state of a permanent magnet loaded on a magnetic body, comprising: measuring a first induced electromotive force induced by the permanent magnet in association with rotation of the magnetic body; estimating a magnetization state of the permanent magnet when the first induced electromotive force is induced using a magnetization estimation algorithm based on the measured first induced electromotive force; Including, Magnetization estimation method.

12. A magnetization estimation device that estimates the magnetization state of a permanent magnet loaded on a magnetic body, measuring a first induced electromotive force induced by the permanent magnet in association with rotation of the magnetic body; estimating a magnetization state of the permanent magnet when the first induced electromotive force is induced using a magnetization estimation algorithm based on the measured first induced electromotive force; performing an action including program.

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