Six-phase permanent magnet synchronous motor flux linkage identification method and device

Abstract

The invention discloses a flux linkage identification method and device for a six-phase permanent magnet synchronous motor, and relates to the technical field of computational electromagnetics, and the method comprises the steps: constructing a motor model of a target motor in a synchronous speed coordinate system; based on the motor model, constructing a model reference adaptive system of the target motor; performing inductance identification on a to-be-identified parameter based on the model reference adaptive system to obtain an accurate inductance value; and determining an inductance error factor based on the accurate inductance value to obtain 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, thereby realizing flux linkage identification of the motor based on the inductance identification transmission and model reference adaptive system, effectively improving the parameter identification efficiency and accuracy, and improving the flux linkage identification accuracy of the motor. The robustness of the motor model to parameter change is enhanced, and the control performance of the permanent magnet synchronous motor is improved.

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 identifying the flux linkage 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, so it has received more and more attention. The core of model predictive control relies on the built mathematical model to simulate the dynamic behavior of the system, so model predictive control is very sensitive to changes in electrical parameters. The quadrature and direct axis inductances and permanent magnet flux linkage of permanent magnet synchronous motors are easily affected by factors such as 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, the model reference adaptive system with identifiable inductance is introduced into the parameter identification of the multi-phase motor. In addition, there is a multi-parameter identification algorithm. However, identifying multiple parameters at the same time will increase the complexity of the system model, and the identification algorithm also needs to consider more constraints and optimization objectives. Therefore, how to achieve stable and efficient multi-parameter identification is of great significance to the research and development of motor control. Summary of the invention

[0004] In response to at least one defect or improvement need in the prior art, the present invention provides a six-phase permanent magnet synchronous motor flux identification method and device to address the defects of the prior art, and implements the flux identification of the motor based on inductance identification transmission and a model reference adaptive system to achieve the purpose of simultaneously realizing inductance identification and flux identification, thereby effectively improving parameter identification efficiency and accuracy.

[0005] To achieve the above object, according to a first aspect of the present invention, there is provided Construct a motor model of the target motor in a synchronous speed coordinate system; Based on the motor model, construct a model reference adaptive system of the target motor; Based on the model reference adaptive system, the inductance is identified on the parameter to be identified to obtain an accurate inductance value; determining an inductance error factor based on the precise inductance value, and determining a flux linkage error factor based on the inductance error factor; The flux error factor is input into the flux identification model to obtain an accurate flux value. The flux identification model is specifically: ; in, is the precise flux linkage value; is the initial flux linkage value; is the error factor between the initial flux value and the precise flux value; yes Shaft current; yes Shaft current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; “^” represents the identification value.

[0006] As described in the six-phase permanent magnet synchronous motor flux identification method, the step of constructing a motor model of the target motor in the synchronous speed coordinate system includes: Construct a motor model of the target motor in a natural coordinate system; The motor model in the natural coordinate system is transformed using a Clarke-Park transformation matrix to obtain a motor model of the target motor in the synchronous speed coordinate system.

[0007] As described in the six-phase permanent magnet synchronous motor flux identification method, the model reference adaptive system of the target motor is constructed based on the motor model, including: The model reference adaptive system includes a reference model, an adjustable model and an adaptive rate; The reference model is specifically: ; The adjustable model is specifically: ; The adaptive rate is determined by the Popov hyperstability principle and expressed in a proportional integral form, specifically: ; in, yes Shaft current; yes Shaft current; is the stator winding resistance coefficient matrix; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; yes Shaft voltage; yes Shaft voltage; is the permanent magnet flux linkage; and Represent the proportional and integral coefficients respectively; “^” represents the identification value.

[0008] As described in the six-phase permanent magnet synchronous motor flux identification method, the inductance identification of the identification parameter based on the model reference adaptive system is performed to obtain an accurate inductance value, including: Based on the inductance identification reference model and the inductance identification adjustable model, the parameters to be identified are adjusted in real time through an adaptive law so that the inductance identification reference model converges to the inductance identification adjustable model, parameter identification is achieved, and an accurate inductance value is obtained.

[0009] As described in the six-phase permanent magnet synchronous motor flux identification method, the inductance error factor is determined based on the precise inductance value, specifically: ; in, is the inductance error factor; is the quadrature-axis inductance; is the direct-axis inductance; yes Shaft current; yes Shaft current; is the stator winding resistance coefficient matrix; is the electrical angular velocity; yes Shaft voltage; is the initial flux linkage value; It is the exact magnetic linkage value; “^” represents the identification value.

[0010] As described in the six-phase permanent magnet synchronous motor flux identification method, the flux error factor is determined based on the inductance error factor, specifically: ; in, is the flux linkage error factor.

[0011] According to a second aspect of the present invention, a six-phase permanent magnet synchronous motor flux identification device is also provided, the device comprising: a first construction unit, used to construct a motor model of a target motor in a synchronous speed coordinate system; a second construction unit, used to construct a model reference adaptive system of the target motor based on the motor model; a processing unit, used to perform inductance identification on a parameter to be identified based on the model reference adaptive system to obtain an accurate inductance value; an error analysis unit, used to determine an inductance error factor based on the accurate inductance value, and determine a flux error factor based on the inductance error factor; an identification unit, used to input the flux error factor into a flux identification model to obtain an accurate flux value, wherein the flux identification model is specifically: ; in, is the precise flux linkage value; is the initial flux linkage value; is the error factor between the initial flux value and the precise flux value; yes Shaft current; yes Shaft current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; “^” represents the identification value.

[0012] According to a third aspect of the present invention, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned six-phase permanent magnet synchronous motor flux identification method when running.

[0013] According to a fourth aspect of the present invention, there is also provided an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-mentioned six-phase permanent magnet synchronous motor flux identification method through the computer program.

[0014] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art: The present invention provides a six-phase permanent magnet synchronous motor flux identification method, the method constructs a motor model of a target motor in a 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, inductance identification is performed on a parameter to be identified to obtain a precise inductance value; based on the precise inductance value, an inductance error factor is determined to further obtain a flux error factor, and the flux error factor is brought into the flux identification model to obtain a precise flux value, thereby realizing flux identification of the motor based on inductance identification transmission and a model reference adaptive system, effectively improving 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

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A schematic flow chart of an optional six-phase permanent magnet synchronous motor flux identification method provided in an embodiment of the present application; Figure 2 An optional motor model provided in the embodiment of the present application Schematic diagram of the coordinate transformation framework; Figure 3 A schematic diagram of the structure of an optional model reference adaptive system provided in an embodiment of the present application; Figure 4 A schematic diagram of a topological structure of an optional two-level voltage source inverter provided in an embodiment of the present application; Figure 5 A schematic diagram of an optional voltage vector distribution framework provided in an embodiment of the present application; Figure 6 A schematic diagram of an optional framework of finite set model predictive current control provided in an embodiment of the present application; Figure 7 A schematic structural diagram of an optional six-phase permanent magnet synchronous motor flux identification device provided in an embodiment of the present application; Figure 8 A schematic diagram of the structure of an optional electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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 intended 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.

[0018] The terms "first", "second", "third", etc. in the specification 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 "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. 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 includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0019] According to one aspect of the embodiments of the present application, a method for identifying the flux linkage of a six-phase permanent magnet synchronous motor is provided. Figure 1 The present invention describes a method for identifying the flux linkage of a six-phase permanent magnet synchronous motor provided in an embodiment of the present application.

[0020] Figure 1 is a flow chart of an optional six-phase permanent magnet synchronous motor flux identification method provided in an embodiment of the present application, such as Figure 1 As shown, the process of the method may include the following steps (STEP, referred to as S): S101, constructing a motor model of the target motor in a synchronous speed coordinate system.

[0021] S102: constructing a model reference adaptive system of the target motor based on the motor model.

[0022] S103, performing inductance identification on the parameters to be identified based on the model reference adaptive system to obtain accurate inductance values.

[0023] S104: determining an inductance error factor based on the precise inductance value, and determining a flux linkage error factor based on the inductance error factor.

[0024] S105, inputting the flux error factor into a flux identification model to obtain an accurate flux value, wherein the flux identification model is specifically: ; in, is the precise flux linkage value; is the initial flux linkage value; is the error factor between the initial flux value and the precise flux value; yes Shaft current; yes Shaft current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; “^” represents the identification value.

[0025] An optional six-phase permanent magnet synchronous motor flux identification method provided in the present application can be used for 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 of indirect parameter identification using relationship transfer are also expected to provide new ideas for induction motors.

[0026] In the motor parameter identification of the embodiment of the present application, a six-phase permanent magnet synchronous motor is taken as an example. Regarding S101, a motor model of the target motor in the synchronous speed coordinate system is constructed: S1: Construct a motor model of the target motor in the natural coordinate system.

[0027] The mathematical model of the six-phase permanent magnet synchronous motor in the natural coordinate system is constructed. Similar to the three-phase motor, the voltage equation and flux equation of the motor are respectively as follows: (1) (2) Where:

[0028]

[0029]

[0030]

[0031]

[0032] in, 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 a sixth-order unit array), is the flux linkage coefficient matrix, is the stator inductance matrix, is the permanent magnet flux.

[0033] The torque equation for a motor is: (3) in, is the electromagnetic torque, To store magnetic field energy, is the mechanical angle, is the pole pair number.

[0034] The equation of motion for a motor is: (4) in, is the moment of inertia, is the mechanical angular velocity, is the load torque, is the damping coefficient.

[0035] From the above equations, it can be seen that the parameters of the six-phase permanent magnet synchronous motor are coupled with each other, and the order is higher than that of the three-phase motor. Therefore, in order 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.

[0036] S2: performing coordinate transformation on the motor model in the natural coordinate system using a Clarke-Park transformation matrix to obtain a motor model of the target motor in the synchronous speed coordinate system.

[0037] To construct a mathematical model of a six-phase permanent magnet synchronous motor in a synchronous speed coordinate system, the Clarke-Park transformation matrix can be used to transform the stator and rotor windings from the natural coordinate system to the synchronous speed coordinate system.

[0038] The Clarke transformation matrix of the six-phase permanent magnet synchronous motor is: (5) The coefficient of It is obtained based on the constant amplitude principle. If it is based on the constant power principle, the coefficient becomes . The first two rows correspond to The subspace participates in the electromechanical energy conversion, so only the first two rows are transformed in coordinates. Figure 2 The motor model provided for this embodiment Coordinate transformation diagram, by Figure 2 The Park transformation matrix of the six-phase permanent magnet synchronous motor is obtained as follows:

[0039] (6) in, It is a fourth-order unit array.

[0040] Then, equation (5) and equation (6) can be multiplied to obtain the Clarke-Park transformation matrix of the six-phase permanent magnet synchronous motor: (7) By multiplying equation (1) and equation (2) with equation (7), we can obtain the voltage and flux equations of the motor in the synchronous speed coordinate system: (8) (9) in, is the electrical angular velocity, is the electrical angular velocity, is the quadrature-axis inductance, It's leakage inductance.

[0041] By multiplying equation (3) and equation (7), the torque equation of the motor in the synchronous speed coordinate system can be obtained as follows: (10) In an exemplary embodiment, regarding S102, a model reference adaptive system of the target motor is constructed based on the motor model: Model reference adaptive system has been widely used in parameter identification due to its advantages such as simple structure and low computational complexity. Figure 3 is a schematic diagram of the structure of an optional model reference adaptive system according to an embodiment of the present application, such as Figure 3 As shown, the model reference adaptive system consists of three parts: reference model, adjustable model and adaptive rate.

[0042] 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 changes in the parameters to be identified. The adaptive 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.

[0043] 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: (11) According to the reference model, the adjustable model containing the inductance to be identified can be written as follows: (12) Here, “^” represents the identification value.

[0044] The adaptive rate is obtained from the Popov hyperstability principle and expressed in proportional integral form as follows: (13) in, and Represent the proportional and integral coefficients respectively. From the model reference adaptive system here, the inductance value can be identified as well as .

[0045] Regarding S103, performing inductance identification on the parameters 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, the parameters to be identified are adjusted in real time through an adaptive law so that the inductance identification reference model converges to the inductance identification adjustable model, parameter identification is achieved, and an accurate inductance value is obtained.

[0046] In this embodiment, regarding step S104, 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: In this embodiment, the six-phase permanent magnet synchronous motor The voltage equation in the axial direction can be used for flux identification and can be rewritten as follows: (14) It should be noted that from formula (11) we can see The voltage equation in the axial direction does not include the flux linkage , so the relationship between magnetic flux and inductance cannot be obtained. The voltage equation in the axial direction includes the flux linkage , which can be used for magnetic linkage identification.

[0047] The corresponding adjustable model of formula (14) is: (15) By analyzing the relationship between inductance and flux change, the inductance value obtained above can be used as well as Obtain the magnetic linkage value indirectly.

[0048] In practical applications, the flux in equation (15) of the adjustable model is the offline measurement value, that is, the initial flux value Rather than the exact flux value Therefore, the error factor of the flux value can be determined by the initial flux value and the precise flux value. , the relationship can be expressed as: (16) Then Substituting into formula (15), we can obtain: (17) From formula (14), we can get: (18) Further, the determining of the flux error factor based on the inductance error factor is specifically: Subtract (17) from (18) (note that when the model reference adaptive system is stable, , ), we can get the value caused by the change of magnetic flux Shaft Inductance The error is: (19) Further, the flux linkage error factor is determined based on the inductance error factor, specifically: From formula (19), we can get: (20) In this embodiment, regarding step S106, based on the inductance error factor, a flux error factor is obtained, and the flux error factor is brought into the flux identification model to obtain an accurate flux value: Based on the above, the accurate magnetic flux value can be obtained: (twenty one) It is worth noting that for surface mounted permanent magnet synchronous motors, , then formula (21) can be simplified to: (twenty two) At this point, the offline measurement value of the magnetic link can be used (initial flux value), inductance identification value With the true value Get accurate magnetic linkage value .

[0049] Based on the content of the above embodiment, in an exemplary embodiment, after determining the accurate flux value based on the inductance identification value, the method further includes: The motor model is discretized to construct a discrete prediction model; based on the discrete prediction model, the precise inductance value and the precise flux value, the prediction state under different voltage control sets is output to obtain a prediction result.

[0050] In this embodiment, a discretized model of the motor is constructed, and the finite set model predictive control predicts the future state of the system under different voltage control sets through the motor model, and evaluates these prediction results based on the cost function, and then selects the control set corresponding to the optimal result (with the minimum cost function) for output.

[0051] Optionally, the forward Euler method can be used to discretize equations (8) and (9) to obtain a discrete prediction model: (twenty three) (twenty four) According to different control objectives, model predictive control can be mainly divided into two categories: model predictive current control and model predictive torque control.

[0052] When using a finite set model to predict current control, and selecting a one-step prediction method to reduce the computational burden, the cost function can be set, for example, as: (25) For example, a two-level voltage source inverter can be used to power a six-phase motor. Figure 4 A schematic diagram of a structure of an optional two-level voltage source inverter provided in an embodiment of the present application, wherein the inverter topology is as follows Figure 4 As shown, in this structure, each bridge arm has two possible switching states, and the entire inverter can produce 64 different switching states.

[0053] Each switching state corresponds to a specific voltage vector: (26) (27) Figure 5 A schematic diagram of an optional voltage vector distribution framework provided in an embodiment of the present application, such as Figure 5 As shown, for the convenience of analysis, the voltage vector is usually The amplitude size in the subspace divides the 60 non-zero vectors into 4 groups, namely large vector , Medium Vector , basic vector and small vector .

[0054] Preferably, Figure 6 A schematic diagram of a framework of an optional finite set model predictive current control is provided for this embodiment, such as Figure 6 In order to reduce the computational burden, the common practice is to select 13 voltage vectors (including 12 large vectors and a zero vector 00) as the control set.

[0055] According to another aspect of the embodiments of the present application, a six-phase permanent magnet synchronous motor flux identification device for implementing the above-mentioned six-phase permanent magnet synchronous motor flux identification method is also provided. Figure 7 is a schematic structural diagram of an optional six-phase permanent magnet synchronous motor flux identification device according to an embodiment of the present application, such as Figure 7 As shown, the device may include: A first construction unit 701 is used to construct a motor model of a target motor in a synchronous speed coordinate system; A second construction unit 702 is used to construct a model reference adaptive system of the target motor based on the motor model; A processing unit 703 is used to perform inductance identification on the parameters to be identified based on the model reference adaptive system to obtain an accurate inductance value; 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; The identification unit is used to input the flux error factor into a flux identification model to obtain an accurate flux value. The flux identification model is specifically: ; in, is the precise flux linkage value; is the initial flux linkage value; is the error factor between the initial flux value and the precise flux value; yes Shaft current; yes Shaft current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; “^” represents the identification value.

[0056] 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.

[0057] 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; based on the model reference adaptive system, inductance identification is performed on the parameters to be identified to obtain accurate inductance values; based on the accurate inductance value, the inductance error factor is determined, and based on the inductance error factor, the flux error factor is determined; the flux error factor is input into the flux identification model to obtain accurate flux values, and the flux identification of the motor based on inductance identification transmission and model reference adaptive system is realized, which effectively improves the parameter identification efficiency and accuracy, enhances the robustness of the motor model to parameter changes, and improves the control performance of the permanent magnet synchronous motor.

[0058] It should be noted here that the examples and scenarios implemented by the above-mentioned modules and corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned embodiments. It should be noted that the above-mentioned modules as part of the device can run in a hardware environment and can be implemented by software or hardware, wherein the hardware environment includes a network environment.

[0059] According to another aspect of the embodiments of the present application, a storage medium is further provided. Optionally, in this embodiment, the storage medium can be used to execute the program code of any of the above six-phase permanent magnet synchronous motor flux identification methods in the embodiments of the present application.

[0060] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps: S1: construct a motor model of the target motor in a synchronous speed coordinate system; S2: Based on the motor model, a model reference adaptive system of the target motor is constructed; S3: Perform inductance identification on the parameters to be identified based on the model reference adaptive system to obtain accurate inductance value; S4: determining an inductance error factor based on the precise inductance value, and determining a flux linkage error factor based on the inductance error factor; S5: Input the flux error factor into the flux identification model to obtain an accurate flux value, and construct a motor model of the target motor in the synchronous speed coordinate system. The flux identification model is specifically: ; in, is the precise flux linkage value; is the initial flux linkage value; is the error factor between the initial flux value and the precise flux value; yes Shaft current; yes Shaft current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; “^” represents the identification value.

[0061] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, which will not be described in detail in this embodiment.

[0062] Among them, computer-readable storage media may include, but are not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0063] According to another aspect of the embodiments of the present application, an electronic device for implementing the above-mentioned six-phase permanent magnet synchronous motor flux identification method is also provided. The electronic device can be a server, a terminal, or a combination thereof.

[0064] Figure 8 is a schematic diagram of the structure of an optional electronic device according to an embodiment of the present application, such as Figure 8 As shown, it includes a processor 802, a communication interface 804, a memory 806 and a communication bus 808, wherein the processor 802, the communication interface 804, and the memory 806 communicate with each other through the communication bus 808, wherein: Memory 806, used for storing computer programs; The processor 802 is used to implement the following steps when executing the computer program stored in the memory 806: S1: construct a motor model of the target motor in a synchronous speed coordinate system; S2: Based on the motor model, a model reference adaptive system of the target motor is constructed; S3: Perform inductance identification on the parameters to be identified based on the model reference adaptive system to obtain accurate inductance value; S4: determining an inductance error factor based on the precise inductance value, and determining a flux linkage error factor based on the inductance error factor; S5: Input the flux error factor into the flux identification model to obtain an accurate flux value, and construct a motor model of the target motor in the synchronous speed coordinate system. The flux identification model is specifically: ; in, is the precise flux linkage value; is the initial flux linkage value; is the error factor between the initial flux value and the precise flux value; yes Shaft current; yes Shaft current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; “^” represents the identification value.

[0065] Optionally, the communication bus may be a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 The communication interface is used for communication between the electronic device and other devices.

[0066] The memory may include RAM, or may include non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0067] As an example, the memory 806 may include, but is not limited to, 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 six-phase permanent magnet synchronous motor flux identification device. In addition, other module units in the six-phase permanent magnet synchronous motor flux identification device may also be included but are not limited to, which will not be repeated in this example.

[0068] The above-mentioned processor can be a general-purpose processor, which can include but not be limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; it can also be DSP (Digital Signal Processing), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0069] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment will not be described in detail here.

[0070] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0071] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0072] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0073] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0074] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0075] If 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 the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, disk or optical disk and other media that can store program codes.

[0076] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable memory, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0077] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of the implementation scheme of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

[0078] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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, they should be considered to be within the scope of this specification.

[0079] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions 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 flux linkage of a six-phase permanent magnet synchronous motor, characterized in that: include: Construct a motor model of the target motor in a synchronous speed coordinate system; Based on the motor model, construct a model reference adaptive system of the target motor; Based on the model reference adaptive system, the inductance is identified on the parameter to be identified to obtain an accurate inductance value; determining an inductance error factor based on the precise inductance value, and determining a flux linkage error factor based on the inductance error factor; The flux error factor is input into the flux identification model to obtain an accurate flux value. The flux identification model is specifically: ； in, is the precise flux linkage value; is the initial flux linkage value; is the error factor between the initial flux value and the precise flux value; yes Shaft current; yes Shaft current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; "^" represents the identification value.

2. The six-phase permanent magnet synchronous motor flux identification method according to claim 1, characterized in that: The step of constructing a motor model of the target motor in a synchronous speed coordinate system comprises: Construct a motor model of the target motor in a natural coordinate system; The motor model in the natural coordinate system is transformed using a Clarke-Park transformation matrix to obtain a motor model of the target motor in the synchronous speed coordinate system.

3. The six-phase permanent magnet synchronous motor flux identification method according to claim 1, characterized in that: The method of constructing a model reference adaptive system of a target motor based on the motor model includes: The model reference adaptive system includes a reference model, an adjustable model and an adaptive rate; The reference model is specifically: ； The adjustable model is specifically: ； The adaptive rate is determined by the Popov hyperstability principle and expressed in a proportional integral form, specifically: ； in, yes Shaft current; yes Shaft current; is the stator winding resistance coefficient matrix; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; yes Shaft voltage; yes Shaft voltage; is the permanent magnet flux linkage; and Represent the proportional and integral coefficients respectively; "^" represents the identification value.

4. The six-phase permanent magnet synchronous motor flux identification method according to claim 3, characterized in that: The method of 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, the parameters to be identified are adjusted in real time through an adaptive law so that the inductance identification reference model converges to the inductance identification adjustable model, parameter identification is achieved, and an accurate inductance value is obtained.

5. The six-phase permanent magnet synchronous motor flux identification method according to claim 1, characterized in that: The determining of the inductance error factor based on the precise inductance value is specifically: ； in, is the inductance error factor; is the quadrature-axis inductance; is the direct-axis inductance; yes Shaft current; yes Shaft current; is the stator winding resistance coefficient matrix; is the electrical angular velocity; yes Shaft voltage; is the initial flux linkage value; It is the exact magnetic linkage value; "^" represents the identification value.

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

7. The six-phase permanent magnet synchronous motor flux identification method according to claim 1, characterized in that: After determining the precise flux value based on the inductance identification value, the method further includes: Discretizing the motor model to construct a discrete prediction model; Based on the discrete prediction model, the precise inductance value and the precise flux linkage value output the predicted state under different voltage control sets to obtain the prediction result.

8. A six-phase permanent magnet synchronous motor flux identification device, characterized in that: include: A first construction unit is used to construct a motor model of the target motor in a synchronous speed coordinate system; A second construction unit is used to construct a model reference adaptive system of the target motor based on the motor model; A processing unit, configured to perform inductance identification on the parameters to be identified based on the model reference adaptive system to obtain an accurate inductance value; an error analysis unit, configured to determine an inductance error factor based on the precise inductance value, and determine a flux linkage error factor based on the inductance error factor; The identification unit is used to input the flux error factor into a flux identification model to obtain an accurate flux value. The flux identification model is specifically: ； in, is the precise flux linkage value; is the initial flux linkage value; is the error factor between the initial flux value and the precise flux value; yes Shaft current; yes Shaft current; is the direct-axis inductance; is the quadrature-axis inductance; is the electrical angular velocity; "^" represents the identification value.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 7 when executed.

10. 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 7 through the computer program.

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