A method and device for identifying magnetic flux of a six-phase permanent magnet synchronous motor

Abstract

The present application discloses a flux linkage identification method and device for a six-phase permanent magnet synchronous motor, relating to the technical field of computational electromagnetics. The method includes: constructing a motor model of a target motor in a synchronous speed coordinate system; constructing a model reference adaptive system of the target motor based on the motor model; performing inductance identification on the parameter to be identified based on the model reference adaptive system to obtain an accurate inductance value; determining an inductance error factor based on the accurate inductance value, and further obtaining a flux linkage error factor, and substituting the flux linkage error factor into a flux linkage identification model to obtain an accurate flux linkage value, realizing the flux linkage identification of the motor based on inductance identification transfer and the model reference adaptive system, effectively improving the parameter identification efficiency and accuracy, enhancing the robustness of the motor model to parameter changes, and improving the control performance of the permanent magnet synchronous motor.

Description

Technical Field

[0001] The present application relates to the technical field of motor parameter identification, and more specifically, to a method and device for flux linkage identification of a six-phase permanent magnet synchronous motor. Background Art

[0002] Model predictive control has the advantages of fast dynamic response, simple implementation, and easy inclusion of nonlinear conditions, etc., so it has received more and more attention. The core of model predictive control depends on the established mathematical model to simulate the dynamic behavior of the system. Therefore, model predictive control is very sensitive to changes in electrical parameters. The direct and quadrature axis inductances and the permanent magnet flux linkage of a permanent magnet synchronous motor are easily affected by factors such as the degree of magnetic saturation, load changes, and ambient temperature. The resulting parameter mismatch problem will affect the output performance of the motor and is not conducive to the stable operation of the system.

[0003] In order to enhance the robustness of the motor model to parameter changes and improve the control performance of the permanent magnet synchronous motor, a model reference adaptive system that can identify inductance is introduced into the parameter identification of multi-phase motors. In addition, there are multi-parameter identification algorithms. However, simultaneously identifying multiple parameters will increase the complexity of the system model, and the identification algorithm also needs to consider more constraint conditions and optimization objectives, etc. Therefore, how to achieve stable and efficient multi-parameter identification is of great significance for the research and development of motor control. Summary of the Invention

[0004] In view of at least one defect or improvement requirement of the prior art, the present invention provides a method and device for flux linkage identification of a six-phase permanent magnet synchronous motor, aiming to solve the defects of the prior art, and realizing the flux linkage identification of the motor based on inductance identification transfer and a model reference adaptive system, so as to achieve the purpose of simultaneously realizing inductance identification and flux linkage identification, and effectively improving the parameter identification efficiency and accuracy.

[0005] To achieve the above object, according to the first aspect of the present invention, there is provided

[0006] Construct a motor model of the target motor in the synchronous speed coordinate system;

[0007] Based on the motor model, construct a model reference adaptive system of the target motor;

[0008] Based on the model reference adaptive system, perform inductance identification on the parameter to be identified to obtain an accurate inductance value;

[0009] Determine an inductance error factor based on the accurate inductance value, and determine a flux linkage error factor based on the inductance error factor;

[0010] Input the flux linkage error factor into the flux linkage identification model to obtain an accurate flux linkage value. The flux linkage identification model is specifically:

[0011] ;

[0012] Among them, is the exact flux linkage value; is the initial flux linkage value; is the error factor between the initial flux linkage value and the exact flux linkage value; is axis current; is axis current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; "^" represents the identification value.

[0013] For the flux linkage identification method of the six-phase permanent magnet synchronous motor as described above, the steps of constructing the motor model of the target motor in the synchronous speed coordinate system include:

[0014] Construct the motor model of the target motor in the natural coordinate system;

[0015] Perform coordinate transformation on the motor model in the natural coordinate system using the Clarke-Park transformation matrix to obtain the motor model of the target motor in the synchronous speed coordinate system.

[0016] For the flux linkage identification method of the six-phase permanent magnet synchronous motor as described above, based on the motor model, constructing the model reference adaptive system of the target motor includes:

[0017] The model reference adaptive system includes a reference model, an adjustable model, and an adaptation rate;

[0018] The reference model is specifically:

[0019] ;

[0020] The adjustable model is specifically:

[0021] ;

[0022] The adaptation rate is determined using the Popov hyperstability principle and is expressed in the proportional-integral form, specifically:

[0023] ;

[0024] Among them, is axis current; is axis current; is the stator winding resistance coefficient matrix; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; is Axis voltage; is Axis voltage; is the permanent magnet flux linkage; and respectively represent the proportional and integral coefficients; "^" represents the identification value.

[0025] For the flux linkage identification method of the six-phase permanent magnet synchronous motor as described above, the inductance identification of the parameter to be identified is performed based on the model reference adaptive system to obtain an accurate inductance value, including:

[0026] Based on the inductance identification reference model and the inductance identification adjustable model, the parameter to be identified is adjusted in real time through the adaptive law, so that the inductance identification reference model converges to the inductance identification adjustable model, realizing parameter identification and obtaining an accurate inductance value.

[0027] For the flux linkage identification method of the six-phase permanent magnet synchronous motor as described above, the inductance error factor is determined based on the accurate inductance value, specifically:

[0028] ;

[0029] wherein, is the inductance error factor; is the quadrature-axis inductance; is the direct-axis inductance; is axis current; is axis current; is the stator winding resistance coefficient matrix; is the electrical angular velocity; is axis voltage; is the initial flux linkage value; is the accurate flux linkage value; "^" represents the identification value.

[0030] For the flux linkage identification method of the six-phase permanent magnet synchronous motor as described above, the flux linkage error factor is determined based on the inductance error factor, specifically:

[0031] ;

[0032] wherein, is the flux linkage error factor.

[0033] According to the second aspect of the present invention, there is also provided a magnetic flux identification device for a six-phase permanent magnet synchronous motor. The device includes: a first construction unit for constructing a motor model of a target motor in a synchronous speed coordinate system; a second construction unit for constructing a model reference adaptive system of the target motor based on the motor model; a processing unit for performing inductance identification on parameters to be identified based on the model reference adaptive system to obtain an accurate inductance value; an error analysis unit for determining an inductance error factor based on the accurate inductance value and determining a magnetic flux error factor based on the inductance error factor; and an identification unit for inputting the magnetic flux error factor into a magnetic flux identification model to obtain an accurate magnetic flux value. The magnetic flux identification model is specifically:

[0034] ;

[0035] wherein, is the accurate magnetic flux value; is the initial magnetic flux value; is the error factor between the initial magnetic flux value and the accurate magnetic flux value; is axis current; is axis current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; "^" represents an identification value.

[0036] According to the third aspect of the present invention, there is also provided a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the above-mentioned six-phase permanent magnet synchronous motor magnetic flux identification method when running.

[0037] According to the fourth aspect of the present invention, there is also provided an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor executes the above-mentioned six-phase permanent magnet synchronous motor magnetic flux identification method through the computer program.

[0038] Generally speaking, compared with the prior art through the above technical solutions conceived by the present invention, the following beneficial effects can be achieved:

[0039] The present invention provides a method for identifying the magnetic flux linkage of a six-phase permanent magnet synchronous motor. The method constructs a motor model of the target motor in the synchronous speed coordinate system; based on the motor model, a model reference adaptive system of the target motor is constructed; based on the model reference adaptive system, the inductance is identified for the parameter to be identified to obtain an accurate inductance value; based on the accurate inductance value, an inductance error factor is determined, and further a magnetic flux linkage error factor is obtained, and the magnetic flux linkage error factor is brought into the magnetic flux linkage identification model to obtain an accurate magnetic flux linkage value, realizing the magnetic flux linkage identification of the motor based on inductance identification transfer and the model reference adaptive system, effectively improving the parameter identification efficiency and accuracy, enhancing the robustness of the motor model to parameter changes, and improving the control performance of the permanent magnet synchronous motor. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0041] Figure 1 It is a schematic flow chart of an optional method for identifying the magnetic flux linkage of a six-phase permanent magnet synchronous motor provided by an embodiment of the present application;

[0042] Figure 2 It is an optional motor model provided by an embodiment of the present application Schematic diagram of the framework of coordinate transformation;

[0043] Figure 3 It is a schematic structural diagram of an optional model reference adaptive system provided by an embodiment of the present application;

[0044] Figure 4 It is a schematic topological structure diagram of an optional two-level voltage source inverter provided by an embodiment of the present application;

[0045] Figure 5 It is a schematic framework diagram of an optional voltage vector distribution provided by an embodiment of the present application;

[0046] Figure 6 It is a schematic framework diagram of an optional finite set model predictive current control provided by an embodiment of the present application;

[0047] Figure 7 It is a schematic structural diagram of an optional device for identifying the magnetic flux linkage of a six-phase permanent magnet synchronous motor provided by an embodiment of the present application;

[0048] Figure 8 It is a schematic structural diagram of an optional electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0050] The terms "first", "second", "third", etc. in the description and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0051] According to one aspect of the embodiments of this application, a method for identifying the flux linkage of a six-phase permanent magnet synchronous motor is provided. The following combines Figure 1 Describe the method for identifying the flux linkage of a six-phase permanent magnet synchronous motor provided by the embodiments of this application.

[0052] Figure 1 is a schematic flow chart of an optional method for identifying the flux linkage of a six-phase permanent magnet synchronous motor provided by the embodiments of this application. As Figure 1 shown, the flow of the method may include the following steps (STEP, abbreviated as S):

[0053] S101, construct a motor model of the target motor in the synchronous speed coordinate system.

[0054] S102, based on the motor model, construct a model reference adaptive system of the target motor.

[0055] S103, based on the model reference adaptive system, perform inductance identification on the parameter to be identified to obtain an accurate inductance value.

[0056] S104, determine an inductance error factor based on the accurate inductance value, and determine a flux linkage error factor based on the inductance error factor.

[0057] S105, input the flux linkage error factor into the flux linkage identification model to obtain an accurate flux linkage value. The flux linkage identification model is specifically:

[0058] ;

[0059] Wherein, is the accurate flux linkage value; is the initial flux linkage value; is the error factor between the initial flux linkage value and the accurate flux linkage value; is the d-axis current; is the q-axis current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; “^” represents the identification value.

[0060] An optional flux linkage identification method for a six-phase permanent magnet synchronous motor provided by this application can be used in the parameter identification of a six-phase motor. It should be noted that the target motor here can also be a multi-phase permanent magnet synchronous motor or a three-phase permanent magnet synchronous motor. Similar methods for indirect parameter identification using relationship transmission are also expected to provide new ideas for induction motors.

[0061] In the motor parameter identification of the embodiments of this application, taking a six-phase permanent magnet synchronous motor as an example, regarding S101, construct the motor model of the target motor in the synchronous speed coordinate system:

[0062] S1: Construct the motor model of the target motor in the natural coordinate system.

[0063] Construct the mathematical model of the six-phase permanent magnet synchronous motor in the natural coordinate system. Similar to the three-phase motor, the voltage equation and flux linkage equation of the motor are respectively listed as:

[0064] (1)

[0065] (2)

[0066] In the formula:

[0067]

[0068]

[0069]

[0070]

[0071]

[0072] Among them, is the stator winding voltage, is the stator winding current, is the total flux linkage of the stator winding, is the stator winding resistance coefficient matrix ( is the sixth-order identity matrix), is the flux linkage coefficient matrix, is the stator inductance matrix, is the permanent magnet flux linkage.

[0073] The torque equation of the motor is as follows:

[0074] (3)

[0075] Wherein, is the electromagnetic torque, is the magnetic field energy storage, is the mechanical angle, is the number of pole pairs.

[0076] The motion equation of the motor is as follows:

[0077] (4)

[0078] Wherein, is the moment of inertia, is the mechanical angular velocity, is the load torque, is the damping coefficient.

[0079] It can be seen from the above equations that the parameters of the six-phase permanent magnet synchronous motor are mutually coupled and the order is higher than that of the three-phase motor. Therefore, to simplify the model and control algorithm, a synchronous speed coordinate system can be established to reduce the order of the multi-phase motor equation and achieve decoupling.

[0080] S2: Coordinate transform the motor model in the natural coordinate system by using the Clarke-Park transformation matrix to obtain the motor model of the target motor in the synchronous speed coordinate system.

[0081] To construct the mathematical model of the six-phase permanent magnet synchronous motor in the synchronous speed coordinate system, the stator and rotor windings can be transformed from the natural coordinate system to the synchronous speed coordinate system by using the Clarke-Park transformation matrix.

[0082] The Clarke transformation matrix of the six-phase permanent magnet synchronous motor is:

[0083] (5)

[0084] The coefficient of is obtained based on the constant amplitude principle. If based on the constant power principle, the coefficient becomes . The first two rows of correspond to the Figure 2 subspace and participate in the electromechanical energy conversion. Therefore, only the first two rows are coordinate-transformed. is the motor model coordinate transformation diagram provided in this embodiment, which is composed of Figure 2The Park transformation matrix of the six-phase permanent magnet synchronous motor is obtained as follows:

[0085] (6)

[0086] wherein, is a fourth-order identity matrix.

[0087] Furthermore, multiplying Equation (5) by Equation (6) can obtain the Clarke-Park transformation matrix of the six-phase permanent magnet synchronous motor:

[0088] (7)

[0089] Multiplying Equation (1) and Equation (2) by Equation (7) respectively can obtain the voltage and flux linkage equations of the motor in the synchronous speed coordinate system as follows:

[0090] (8)

[0091] (9)

[0092] wherein, is the electrical angular velocity, is the electrical angular velocity, is the quadrature-axis inductance, is the leakage inductance.

[0093] Multiplying Equation (3) by Equation (7) can obtain the torque equation of the motor in the synchronous speed coordinate system as follows:

[0094] (10)

[0095] In an exemplary embodiment, regarding S102, based on the motor model, a model reference adaptive system of the target motor is constructed:

[0096] The model reference adaptive system has been widely used in parameter identification due to its advantages such as simple structure and less computational complexity. Figure 3 is a schematic structural diagram of an optional model reference adaptive system according to an embodiment of the present application. As Figure 3 shown, the model reference adaptive system is composed of three parts: a reference model, an adjustable model, and an adaptation rate.

[0097] Among them, the reference model is used to represent the desired control performance and does not contain the parameters to be identified; the adjustable model adjusts the system output according to the change of the parameters to be identified. The adaptation law adjusts the parameters to be identified in real time according to the output error between the reference model and the adjustable model, so that the output of the adjustable model gradually approaches the output of the reference model. Finally, through error convergence, the adjustable model achieves the same control performance as the reference model, that is, the adjustable model converges to the reference model, thereby realizing parameter identification.

[0098] Taking the current equation of the six-phase permanent magnet synchronous motor in the synchronous speed coordinate system as the reference model, the reference model can be obtained from Equations (8) and (9) as follows:

[0099] (11)

[0100] According to the reference model, the adjustable model containing the inductance to be identified can be written as follows:

[0101] (12)

[0102] Wherein, “^” represents the identification value.

[0103] The adaptation rate is obtained from the Popov hyperstability principle and expressed in the proportional-integral form as follows:

[0104] (13)

[0105] Wherein, and represent the proportional and integral coefficients respectively. From the model reference adaptive system herein, the inductance value as well as can be identified.

[0106] Regarding S103, based on the model reference adaptive system, the inductance identification of the parameter to be identified is performed, and obtaining the accurate inductance value includes:

[0107] Based on the inductance identification reference model and the inductance identification adjustable model, the parameter to be identified is adjusted in real time through the adaptation law, so that the inductance identification reference model converges to the inductance identification adjustable model, realizing parameter identification and obtaining the accurate inductance value.

[0108] In this embodiment, regarding step S104, based on the accurate inductance value, the inductance error factor is determined, and based on the inductance error factor, the flux linkage error factor is determined:

[0109] In this embodiment, the voltage equation of the six-phase permanent magnet synchronous motor in the axis direction can be used for flux linkage identification and is rewritten as follows:

[0110] (14)

[0111] It should be noted that it can be seen from Equation (11) that the voltage equation in the axis direction does not contain the flux linkage , so the relationship between the flux linkage and the inductance cannot be obtained. Only the voltage equation in the axis direction contains the flux linkage and can be used for flux linkage identification.

[0112] The corresponding adjustable model of Equation (14) is as follows:

[0113] (15)

[0114] By analyzing the relationship between the inductor and the change of magnetic flux linkage, the inductor value obtained above can be used and to indirectly obtain the magnetic flux linkage value.

[0115] In practical applications, the magnetic flux linkage of Equation (15) of the adjustable model is an off-line measured value, that is, the initial magnetic flux linkage value rather than the accurate magnetic flux linkage value , therefore, the error factor of the magnetic flux linkage value can be determined by the initial magnetic flux linkage value and the accurate magnetic flux linkage value , and its relationship can be expressed as:

[0116] (16)

[0117] Then substitute into Equation (15), and we can get:

[0118] (17)

[0119] From Equation (14), we can get:

[0120] (18)

[0121] Furthermore, the determination of the magnetic flux linkage error factor based on the inductor error factor is specifically as follows:

[0122] Take the difference between Equation (17) and Equation (18) (also note that when the model reference adaptive system is stable, there are , ), and the error of the axis inductor caused by the change of magnetic flux linkage can be obtained as:

[0123] (19)

[0124] Furthermore, the determination of the magnetic flux linkage error factor based on the inductor error factor is specifically as follows:

[0125] From Equation (19), we can get:

[0126] (20)

[0127] In this embodiment, regarding step S106, based on the inductor error factor, the magnetic flux linkage error factor is further obtained, and the magnetic flux linkage error factor is substituted into the magnetic flux linkage identification model to obtain the accurate magnetic flux linkage value:

[0128] Based on the above, the accurate flux linkage value can be obtained:

[0129] (21)

[0130] It should be noted that for surface-mounted permanent magnet synchronous motors, due to , Equation (21) can be simplified to:

[0131] (22)

[0132] At this time, the offline measured value of the flux linkage (initial flux linkage value), the identified value of the inductance and the true value and other information can be used to obtain the accurate flux linkage value .

[0133] Based on the content of the above embodiments, in an exemplary embodiment, after determining the accurate flux linkage value based on the identified inductance value, it further includes:

[0134] Discretize the motor model to construct a discrete prediction model; based on the discrete prediction model, the accurate inductance value, and the accurate flux linkage value, output the predicted states under different voltage control sets to obtain the prediction results.

[0135] In this embodiment, a discrete model of the motor is constructed. The finite set model predictive control predicts the future states of the motor model prediction system under different voltage control sets, and evaluates these prediction results based on the cost function, and then selects the control set corresponding to the optimal result (the minimum cost function) for output.

[0136] Optionally, the forward Euler method can generally be used to discretize Equations (8) and (9) to obtain the discrete prediction model as:

[0137] (23)

[0138] (24)

[0139] According to different control objectives, model predictive control can be mainly divided into two categories: model predictive current control and model predictive torque control.

[0140] When using finite set model predictive current control and selecting a one-step prediction method to reduce the computational burden, the cost function can be set, for example, as:

[0141] (25)

[0142] A two-level voltage source inverter can be used to supply power to the six-phase motor,Figure 4 FIG. is a schematic structural diagram of an optional two-level voltage source inverter provided by an embodiment of the present application. The inverter topology is as follows Figure 4 shown. In this structure, each arm has two possible switching states, and the entire inverter can generate 64 different switching states.

[0143] Each switching state corresponds to a specific voltage vector:

[0144] (26)

[0145] (27)

[0146] Figure 5 FIG. is a schematic framework diagram of an optional voltage vector distribution provided by an embodiment of the present application. As Figure 5 shown, for the convenience of analysis, usually according to the magnitude of the voltage vector in the subspace, the 60 non-zero vectors are divided into 4 groups, namely large vectors , medium vectors , basic vectors and small vectors .

[0147] Preferably, Figure 6 FIG. is a schematic framework diagram of an optional finite set model predictive current control provided for this embodiment. As Figure 6 shown. To reduce the computational burden, the usual practice is to select 13 voltage vectors (including 12 large vectors and a zero vector 00) as the control set.

[0148] According to another aspect of the embodiment of the present application, there is also provided a six-phase permanent magnet synchronous motor flux linkage identification device for implementing the above six-phase permanent magnet synchronous motor flux linkage identification method. Figure 7 FIG. is a schematic structural diagram of an optional six-phase permanent magnet synchronous motor flux linkage identification device according to an embodiment of the present application. As Figure 7 shown, the device may include:

[0149] A first construction unit 701 for constructing a motor model of the target motor in the synchronous speed coordinate system;

[0150] A second construction unit 702 for constructing a model reference adaptive system of the target motor based on the motor model;

[0151] A processing unit 703 for performing inductance identification on the parameter to be identified based on the model reference adaptive system to obtain an accurate inductance value;

[0152] An error analysis unit 704 determines an inductance error factor based on the precise inductance value and determines a flux linkage error factor based on the inductance error factor;

[0153] An identification unit is configured to input the flux linkage error factor into a flux linkage identification model to obtain a precise flux linkage value. The specific form of the flux linkage identification model is:

[0154] ;

[0155] where is the precise flux linkage value; is the initial flux linkage value; is the error factor between the initial flux linkage value and the precise flux linkage value; is the d-axis current; is the q-axis current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; "^" represents the identification value.

[0156] It should be noted that the first construction unit 701 in this embodiment can be used to execute the above-mentioned step S101, the second construction unit 702 in this embodiment can be used to execute the above-mentioned step S102, the processing unit 703 in this embodiment can be used to execute the above-mentioned step S103, the error analysis unit 704 in this embodiment can be used to execute the above-mentioned step S104, and the identification unit 705 in this embodiment can be used to execute the above-mentioned step S105.

[0157] Through the above modules, a motor model of the target motor in the synchronous speed coordinate system is constructed; based on the motor model, a model reference adaptive system of the target motor is constructed; inductance identification is performed on the parameters to be identified based on the model reference adaptive system to obtain a precise inductance value; an inductance error factor is determined based on the precise inductance value, and a flux linkage error factor is determined based on the inductance error factor; the flux linkage error factor is input into the flux linkage identification model to obtain a precise flux linkage value, realizing the flux linkage identification of the motor based on inductance identification transfer and the model reference adaptive system, effectively improving the parameter identification efficiency and accuracy, enhancing the robustness of the motor model to parameter changes, and improving the control performance of the permanent magnet synchronous motor.

[0158] It should be noted here that the implementation examples and scenarios of the above modules and the corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules, as part of the device, can run in a hardware environment, can be implemented by software, or can be implemented by hardware, where the hardware environment includes a network environment.

[0159] According to another aspect of the embodiments of the present application, a storage medium is further provided. Optionally, in this embodiment, the above storage medium can be used to execute the program code of any one of the above six-phase permanent magnet synchronous motor flux linkage identification methods in the embodiments of the present application.

[0160] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps:

[0161] S1: Construct a motor model of the target motor in the synchronous speed coordinate system;

[0162] S2: Based on the motor model, construct a model reference adaptive system of the target motor;

[0163] S3: Based on the model reference adaptive system, perform inductance identification on the parameter to be identified to obtain an accurate inductance value;

[0164] S4: Determine an inductance error factor based on the accurate inductance value, and determine a flux linkage error factor based on the inductance error factor;

[0165] S5: Input the flux linkage error factor into the flux linkage identification model to obtain an accurate flux linkage value, and construct a motor model of the target motor in the synchronous speed coordinate system. The flux linkage identification model is specifically:

[0166] ;

[0167] Wherein, is the accurate flux linkage value; is the initial flux linkage value; is the error factor between the initial flux linkage value and the accurate flux linkage value; is axis current; is axis current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; "^" represents the identification value.

[0168] Optionally, the specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be elaborated herein.

[0169] Among them, the computer-readable storage medium can include but is not limited to any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, micro drives, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nano-systems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0170] According to another aspect of the embodiments of the present application, there is also provided an electronic device for implementing the above-mentioned six-phase permanent magnet synchronous motor flux linkage identification method, and the electronic device can be a server, a terminal, or a combination thereof.

[0171] Figure 8 is a schematic structural diagram of an optional electronic device according to an embodiment of the present application. As Figure 8 shown, it includes a processor 802, a communication interface 804, a memory 806, and a communication bus 808. Among them, the processor 802, the communication interface 804, and the memory 806 communicate with each other through the communication bus 808. Among them,

[0172] The memory 806 is used to store computer programs;

[0173] The processor 802, when executing the computer program stored on the memory 806, realizes the following steps:

[0174] S1: Construct a motor model of the target motor in the synchronous speed coordinate system;

[0175] S2: Based on the motor model, construct a model reference adaptive system of the target motor;

[0176] S3: Based on the model reference adaptive system, perform inductance identification on the parameter to be identified to obtain an accurate inductance value;

[0177] S4: Determine an inductance error factor based on the accurate inductance value, and determine a flux linkage error factor based on the inductance error factor;

[0178] S5: Input the flux linkage error factor into the flux linkage identification model to obtain an accurate flux linkage value, and construct a motor model of the target motor in the synchronous speed coordinate system. The flux linkage identification model is specifically:

[0179] ;

[0180] Among them, is the accurate flux linkage value; is the initial flux linkage value; is the error factor between the initial flux linkage value and the accurate flux linkage value; is axis current; is axis current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; "^" represents the identification value.

[0181] Optionally, the communication bus may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 8 only one line is used to represent it in Figure 8 , but it does not mean that there is only one bus or one type of bus. The communication interface is used for communication between the above-mentioned electronic device and other devices.

[0182] The memory may include a RAM, and may also include a non-volatile memory, for example, at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0183] As an example, the above-mentioned memory 806 may but is not limited to include the first construction unit 701, the second construction unit 702, the processing unit 703, the error analysis unit 704, and the identification unit 705 in the above-mentioned six-phase permanent magnet synchronous motor flux linkage identification device. In addition, it may also include but is not limited to other module units in the above-mentioned six-phase permanent magnet synchronous motor flux linkage identification device, which will not be elaborated in this example.

[0184] The above-mentioned processor may be a general-purpose processor, which may include but is not limited to: a CPU (Central Processing Unit), an NP (Network Processor), etc.; it may also be a DSP (Digital Signal Processing), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0185] Optionally, the specific examples in this embodiment may refer to the examples described in the above-mentioned embodiment, and will not be elaborated here.

[0186] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0187] In the above embodiments, the descriptions of the respective embodiments have their own focuses. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0188] In the several embodiments provided by this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0189] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0190] In addition, in each embodiment of this application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0191] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned memory includes: various media such as USB flash drives, read-only memory (ROM), random access memory (RAM), external hard drives, magnetic disks, or optical discs that can store program codes.

[0192] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory, and the memory can include: flash drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs, etc.

[0193] The above are only exemplary embodiments of the present disclosure, and the scope of the present disclosure cannot be limited thereby. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. Those skilled in the art will easily think of other embodiments of the present disclosure after considering the specification and practicing the present disclosure. This application aims to cover any variations, uses, or adaptive changes of the present disclosure, and these variations, uses, or adaptive changes follow the general principles of the present disclosure and include common general knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and embodiments are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

[0194] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as within the scope described in this specification.

[0195] Those skilled in the art can easily understand that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying the magnetic flux of a six-phase permanent magnet synchronous motor, characterized in that Including: Constructing a motor model of the target motor in the synchronous speed coordinate system; Based on the motor model, constructing a model reference adaptive system for the target motor; the model reference adaptive system includes a reference model, an adjustable model, and an adaptation rate; The reference model is specifically: ； The adjustable model is specifically: ； The adaptation rate is determined using the Popov hyperstability principle and expressed in a proportional-integral form, specifically: ； Among them, is axial current; is axial current; is the stator winding resistance coefficient matrix; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; is axial voltage; is axial voltage; is the permanent magnet flux linkage; and respectively represent the proportional and integral coefficients; "^" represents the identification value; Based on the model reference adaptive system, performing inductance identification on the parameter to be identified to obtain an accurate inductance value; Based on the accurate inductance value, determining an inductance error factor, and based on the inductance error factor, determining a flux linkage error factor; Inputting the flux linkage error factor into a flux linkage identification model to obtain an accurate flux linkage value, and the flux linkage identification model is specifically: ； Among them, is the exact flux linkage value; is the initial flux linkage value; is the error factor between the initial flux linkage value and the exact flux linkage value; is the d-axis current; is the q-axis current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; "^" represents the identification value.

2. The method for identifying the magnetic flux of a six-phase permanent magnet synchronous motor according to claim 1, characterized in that The steps of constructing the motor model of the target motor in the synchronous speed coordinate system include: Constructing a motor model of the target motor in the natural coordinate system; Performing coordinate transformation on the motor model in the natural coordinate system using a Clarke-Park transformation matrix to obtain the motor model of the target motor in the synchronous speed coordinate system.

3. The flux linkage identification method of the six-phase permanent magnet synchronous motor according to claim 1, characterized in that The performing inductance identification on the parameter to be identified based on the model reference adaptive system to obtain an accurate inductance value includes: Based on the inductance identification reference model and the inductance identification adjustable model, adjusting the parameter to be identified in real time through an adaptation law so that the inductance identification reference model converges to the inductance identification adjustable model, realizing parameter identification and obtaining an accurate inductance value.

4. The method for identifying the magnetic flux of a six-phase permanent magnet synchronous motor according to claim 1, wherein, The determining the inductance error factor based on the accurate inductance value is specifically: ； Among them, is the inductance error factor; is the quadrature-axis inductance; is the direct-axis inductance; is the q-axis current; is the d-axis current; is the stator winding resistance coefficient matrix; is the electrical angular velocity; is the q-axis voltage; is the initial flux linkage value; is the exact flux linkage value; "^" represents the identification value.

5. The flux linkage identification method of the six-phase permanent magnet synchronous motor according to claim 4, characterized in that The determining the flux linkage error factor based on the inductance error factor is specifically: ； Among them, is the flux linkage error factor.

6. The flux linkage identification method for a six-phase permanent magnet synchronous motor according to claim 1, characterized in that, After determining the accurate flux linkage value based on the inductance identification value, further including: Performing discretization processing on the motor model to construct a discrete prediction model; Based on the discrete prediction model, the accurate inductance value, and the accurate flux linkage value, outputting predicted states under different voltage control sets to obtain a prediction result.

7. A magnetic flux identification device for a six-phase permanent magnet synchronous motor, characterized in that, Including: A first construction unit for constructing a motor model of the target motor in the synchronous speed coordinate system; A second construction unit for constructing a model reference adaptive system for the target motor based on the motor model; the model reference adaptive system includes a reference model, an adjustable model, and an adaptation rate; The reference model is specifically: ； The adjustable model is specifically: ； The adaptation rate is determined using the Popov hyperstability principle and expressed in a proportional-integral form, specifically: ； Among them, is axial current; is axial current; is the stator winding resistance coefficient matrix; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; is axial voltage; is axial voltage; is the permanent magnet flux linkage; and represent the proportional and integral coefficients respectively; "^" represents the identification value; A processing unit for performing inductance identification on the parameter to be identified based on the model reference adaptive system to obtain an accurate inductance value; An error analysis unit for determining an inductance error factor based on the accurate inductance value and determining a flux linkage error factor based on the inductance error factor; An identification unit for inputting the flux linkage error factor into a flux linkage identification model to obtain an accurate flux linkage value, and the flux linkage identification model is specifically: ； Among them, is the exact flux linkage value; is the initial flux linkage value; is the error factor between the initial flux linkage value and the exact flux linkage value; is the d-axis current; is the q-axis current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; "^" represents the identification value.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when running, executes the method according to any one of claims 1 to 6.

9. An electronic device, comprising a memory and a processor, characterized in that, A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

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