Position sensorless control method, device and equipment for permanent magnet synchronous motor

Abstract

The embodiment of the invention provides a sensorless control method, device and equipment for a permanent magnet synchronous motor, and belongs to the technical field of motor control. The method comprises the following steps: obtaining an initial flux linkage observation change model; performing error determination on the initial flux linkage observation change model to obtain a flux linkage observation error model; performing rotor position calculation through the initial flux linkage observation change model to obtain the rotor position of the target motor, and performing variable quantity analysis on the rotor position to obtain the motor rotating speed of the target motor; updating initial model parameters in the initial flux linkage observation change model through the flux linkage observation error model to obtain a target flux linkage observation change model; obtaining a target observation flux linkage and a target two-phase static coordinate system current of the target motor; and performing rotor position calculation on the target observation flux linkage and the target two-phase current through the target flux linkage observation change model to obtain a target rotor position. According to the embodiment of the invention, the rotor position can be calculated for the motor in different operation stages.

Description

Technical Field

[0001] The present application relates to the field of motor control technology, and in particular to a position sensorless control method, device and equipment for a permanent magnet synchronous motor. Background Art

[0002] Permanent Magnet Synchronous Motor (PMSM) is a type of motor that is widely used in electric vehicles, aircraft, household appliances, and other scenarios. During the operation of the permanent magnet synchronous motor, the rotor position of the motor needs to be obtained to control the motor. Considering that the reliability of directly measuring the rotor position using a position sensor is not high (for example, the position sensor may fail and fail to measure the rotor position), a position sensorless control method can be used, such as estimating the rotor position of the motor based on parameters such as the motor current.

[0003] However, the motor has different speeds in different operating stages (such as the startup stage, low-speed operation stage, medium-high speed operation stage, etc.), and the current position sensorless control method is difficult to control the motor in different operating stages. For example, the current position sensorless methods include the sliding mode observer method and the harmonic injection observer method, among which the sliding mode observer method is difficult to estimate the rotor position in the startup stage or low-speed operation stage of the motor, and the harmonic injection observer method is difficult to apply to the medium-high speed operation stage of the motor; and, the sliding mode observer method and the harmonic injection observer method cannot be used at the same time to control the same motor, because it is still unknown whether the switching of these two methods will cause the motor to be unstable. It can be seen that the current position sensorless control method is difficult to obtain the rotor position in different operating stages of the motor, which may cause the speed fluctuation of the motor or even cause the motor to shut down.

[0004] Therefore, how to calculate the rotor position of the motor at different operating stages (including different speeds and different loads) has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The main purpose of the embodiments of the present application is to propose a position sensorless control method, device and equipment for a permanent magnet synchronous motor, aiming to calculate the rotor position of the motor in different operating stages, thereby achieving control of the motor.

[0006] To achieve the above object, a first aspect of an embodiment of the present application provides a position sensorless control method for a permanent magnet synchronous motor, the method comprising:

[0007] A flux mathematical model is constructed according to the initial observed flux and initial two-phase current of the target motor to obtain an initial flux observer model; wherein the initial flux observer model has initial model parameters;

[0008] Constructing a current state space function according to the initial two-phase voltage and the initial two-phase current of the target motor to obtain a current state space function;

[0009] Performing a variation analysis on the initial flux linkage observer model according to the current state space function to obtain an initial flux linkage observation variation model; wherein the initial flux linkage observation variation model has the initial model parameters;

[0010] Performing error determination on the initial flux observation change model to obtain a flux observation error model;

[0011] Calculating the rotor position through the initial flux observation change model to obtain the initial rotor position of the target motor, and analyzing the change of the initial rotor position to obtain the motor speed of the target motor;

[0012] By using the flux observation error model, the initial model parameters in the initial flux observation change model are updated to obtain a target flux observation change model;

[0013] Obtaining a target observed flux and a target two-phase current of the target motor;

[0014] The target rotor position is calculated by using the target flux observation change model for the target observed flux and the target two-phase current to obtain the target rotor position.

[0015] In some embodiments, updating the initial model parameters in the initial flux observation change model by using the flux observation error model to obtain the target flux observation change model includes:

[0016] Determine the stability factor according to the flux observation error model, the initial observed flux, the rotor position and the motor speed to obtain a model stability factor;

[0017] The initial model parameters are updated according to the model stability factor to obtain target model parameters, and the initial flux observation change model is updated according to the target model parameters to obtain a target flux observation change model.

[0018] In some embodiments, determining the stability factor according to the flux observation error model, the initial observed flux, the rotor position, and the motor speed to obtain the model stability factor includes:

[0019] Constructing a flux rotor mapping factor according to the initial observed flux and the rotor position to obtain a flux rotor mapping factor;

[0020] Constructing a speed mapping factor according to the motor speed to obtain a speed mapping factor;

[0021] Substituting the flux rotor mapping factor into the flux observation error model to obtain an initial chaotic flux observer model;

[0022] Constructing a factor state space function according to the flux rotor mapping factor to obtain a factor state space function;

[0023] Substituting the factor state space function and the speed mapping factor into the initial chaotic flux observer model to obtain a target chaotic flux observer model;

[0024] The target chaotic flux observer model is substituted into a preset stability function to obtain the model stability factor.

[0025] In some embodiments, performing a variation analysis on the initial flux observer model according to the current state space function to obtain the initial flux observation variation model includes:

[0026] Substituting the current state space function into the initial flux observer model to obtain a target flux derivative model;

[0027] An update model is constructed according to a preset update excitation value, the initial observed flux linkage and the initial two-phase current to obtain a flux linkage update model;

[0028] The target flux derivative model is substituted into the flux update model to obtain the initial flux observation change model.

[0029] In some embodiments, the initial flux linkage observation change model includes at least two candidate sub-formulas;

[0030] The step of performing error determination on the initial flux observation change model to obtain a flux observation error model includes:

[0031] Screening the candidate sub-formulas according to the initial observed magnetic flux, and determining the candidate sub-formulas containing the initial observed magnetic flux as magnetic flux error formulas;

[0032] The flux linkage error formula is substituted to obtain the flux linkage observation error model.

[0033] In some embodiments, the initial observed flux linkage includes a first observed flux linkage and a second observed flux linkage, the initial two-phase current includes a first current and a second current, and the initial two-phase voltage includes a first voltage and a second voltage;

[0034] The initial magnetic flux observation change model is shown in the following formula:

[0035]

[0036] in, Represents the first observed magnetic flux The derivative of The second observed flux is The derivative of α represents the first current, I β represents the second current; R represents the stator resistance of the target motor; L represents the inductance of the target motor; U α represents the first voltage corresponding to the first current, U β represents the second voltage corresponding to the second current; γ represents the updated excitation value; k1 represents the initial model parameter; ψ f Represents the rotor flux of the target motor.

[0037] In some embodiments, the flux rotor mapping factor includes a first flux rotor mapping factor and a second flux rotor mapping factor;

[0038] The model stability factor is defined as follows:

[0039]

[0040] in, represents the model stability factor; X1 represents the first flux rotor mapping factor, X2 represents the second flux rotor mapping factor; k1 represents the initial model parameter;

[0041] The flux rotor mapping factor is defined as:

[0042]

[0043] Wherein, X represents the flux rotor mapping factor; ψ f represents the rotor flux of the target motor; θ represents the rotor position of the target motor; Represents the magnetic flux linkage with the first observation The corresponding first observed flux error is, Represents the magnetic linkage with the second observation The corresponding second observed flux error.

[0044] To achieve the above object, a second aspect of an embodiment of the present application provides a position sensorless control device for a permanent magnet synchronous motor, the device comprising:

[0045] An initial flux observer model construction module is used to construct a flux mathematical model according to the initial observed flux and initial two-phase current of the target motor to obtain an initial flux observer model; wherein the initial flux observer model has initial model parameters;

[0046] A current state space function construction module, used to construct a current state space function according to the initial two-phase voltage and the initial two-phase current of the target motor to obtain a current state space function;

[0047] a variation analysis module, configured to perform variation analysis on the initial flux observer model according to the current state space function to obtain an initial flux observation variation model; wherein the initial flux observation variation model has the initial model parameters;

[0048] An error determination module, used for performing error determination on the initial flux observation change model to obtain a flux observation error model;

[0049] A motor speed calculation module, used to calculate the rotor position through the initial flux observation change model to obtain the initial rotor position of the target motor, and to analyze the change amount of the initial rotor position to obtain the motor speed of the target motor;

[0050] An initial model parameter updating module, used to update the initial model parameters in the initial flux observation change model through the flux observation error model to obtain a target flux observation change model;

[0051] A flux current acquisition module, used to acquire a target observed flux and a target two-phase current of the target motor;

[0052] The rotor position calculation module is used to calculate the rotor position of the target observed flux and the target two-phase current through the target flux observation change model to obtain the target rotor position.

[0053] To achieve the above objectives, a third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in the first aspect is implemented.

[0054] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0055] The present application proposes a position sensorless control method, device, and equipment for a permanent magnet synchronous motor, which calculates the initial rotor position through an initial flux observation change model, and obtains the motor speed of the target motor according to the change in the initial rotor position; the motor speed has an impact on the stability of the initial flux observation change model. The initial flux observation change model is converted into a flux observation error model, and then the model stability factor is determined according to the flux observation error model and the motor speed, and the initial model parameters are updated according to the model stability factor. It can be seen that no matter how the speed of the target motor changes, the present application can update the initial model parameters of the initial flux observation change model according to the motor speed to obtain a stable target flux observation change model, thereby ensuring the accuracy of the target rotor position calculated by it. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a flow chart of a position sensorless control method for a permanent magnet synchronous motor provided in an embodiment of the present application;

[0057] Figure 2 yes Figure 1 Flow chart of step 103 in;

[0058] Figure 3 yes Figure 1 Flowchart of step 104 in;

[0059] Figure 4 yes Figure 1 Flow chart of step 106 in;

[0060] Figure 5 yes Figure 4 Flow chart of step 401 in;

[0061] Figure 6 It is a schematic diagram of the structure of a position sensorless control device for a permanent magnet synchronous motor;

[0062] Figure 7 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application 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 application and are not used to limit the present application.

[0064] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0065] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0066] First, some nouns involved in this application are analyzed:

[0067] Artificial Intelligence (AI): It is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. AI is a branch of computer science. AI attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a similar way to human intelligence. Research in this field includes robots, language recognition, image recognition, natural language processing and expert systems. AI can simulate the information process of human consciousness and thinking. AI is also a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0068] Permanent Magnet Synchronous Motor (PMSM): a synchronous motor that can be used in electronic devices or equipment such as electric vehicles, more electric aircraft, and flying cars.

[0069] The position sensorless control method, device and equipment for a permanent magnet synchronous motor provided in the embodiments of the present application are specifically illustrated through the following embodiments. First, the position sensorless control method for a permanent magnet synchronous motor in the embodiments of the present application is described.

[0070] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0071] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0072] The position sensorless control method for a permanent magnet synchronous motor provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, and can also be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements a position sensorless control method for a permanent magnet synchronous motor, etc., but is not limited to the above forms.

[0073] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0074] Figure 1 is an optional flow chart of a position sensorless control method for a permanent magnet synchronous motor provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps 101 to 108.

[0075] Step 101, constructing a flux mathematical model according to the initial observed flux and initial two-phase current of the target motor to obtain an initial flux observer model; wherein the initial flux observer model has initial model parameters;

[0076] Step 102, constructing a current state space function according to the initial two-phase voltage and the initial two-phase current of the target motor to obtain a current state space function;

[0077] Step 103, analyzing the variation of the initial flux observer model according to the current state space function to obtain an initial flux observation variation model; wherein the initial flux observation variation model has initial model parameters;

[0078] Step 104, performing error determination on the initial flux observation change model to obtain a flux observation error model;

[0079] Step 105, calculating the rotor position through the initial flux observation change model to obtain the initial rotor position of the target motor, and analyzing the change of the initial rotor position to obtain the motor speed of the target motor;

[0080] Step 106, updating the initial model parameters in the initial flux observation change model through the flux observation error model to obtain a target flux observation change model;

[0081] Step 107, obtaining a target observed flux and a target two-phase current of the target motor;

[0082] Step 108 , calculating the rotor position of the target observed flux and the target two-phase current by using the target flux observation change model to obtain the target rotor position.

[0083] The beneficial effects of the embodiments of the present application include but are not limited to: calculating the initial rotor position through the initial flux observation change model, and obtaining the motor speed of the target motor according to the change in the initial rotor position; the motor speed has an impact on the stability of the initial flux observation change model. The initial flux observation change model is converted into a flux observation error model, and then the model stability factor is determined according to the flux observation error model and the motor speed, and the initial model parameters are updated according to the model stability factor. It can be seen that no matter how the speed of the target motor changes, the present application can update the initial model parameters of the initial flux observation change model according to the motor speed to obtain a stable target flux observation change model, thereby ensuring the accuracy of the target rotor position calculated by it.

[0084] In some embodiments, it should be noted that the current motor control method can directly use a position sensor to measure the rotor position of a permanent magnet synchronous motor. However, the reliability of the above motor control method is not high in a strong electromagnetic interference environment. For example, the position sensor may fail and fail to measure the rotor position. Or, the cost of the position sensor is too high, resulting in the high cost of the motor control method. Considering the above problems, a position sensorless control method can be used, such as estimating the rotor position of the motor based on parameters such as the current of the motor. However, the motor has different speeds in different operating stages (such as the startup stage, the low-speed operation stage, the medium- and high-speed operation stage, etc.). The current position sensorless control method is difficult to obtain the rotor position in different operating stages of the motor, and the accuracy of the rotor position cannot be ensured. In the embodiment of the present application, it can be understood that the speed of the motor has an impact on the stability of the initial flux observation change model. Only when the initial flux observation change model is stable can the accuracy of the rotor position calculated by it be ensured. Considering the above situation, the embodiment of the present application can update the initial model parameters of the initial flux observation change model according to the motor speed to obtain a stable target flux observation change model, thereby calculating the accurate target rotor position through the target flux observation change model.

[0085] In some embodiments, the initial model parameters in the initial flux observation change model can also be updated according to the load of the target motor to improve the anti-disturbance performance of the target flux observation change model. For example, the initial model parameter is k1; when the target motor is in the startup stage, k1 can be set to 0.2; when the target motor is in the loading stage (such as the medium and high speed operation stage), k1 can be set to 5, thereby improving the accuracy of the target rotor position calculated by the target flux observation change model.

[0086] In step 101 of some embodiments, the initial model parameters are used to affect the mapping relationship between the initial observed flux and the rotor position of the target motor. The three-phase current of the target motor can be obtained by a current detection device, and then the three-phase current is transformed to obtain the initial two-phase current. The initial observed flux can be calculated based on the motor parameters such as the back electromotive force and resistance of the target motor. The initial observed flux or initial two-phase current of the target motor can also be obtained by other means, without limitation.

[0087] In some embodiments, the definition of the initial flux observer model is as shown in formula (1):

[0088]

[0089] Among them, x α represents the first real flux of the target motor on the first motor shaft (i.e., α axis), x βrepresents the second real flux of the target motor on the second motor shaft (i.e., β axis); L represents the inductance of the target motor; k1 represents the initial model parameter; ψ f represents the rotor flux of the target motor; θ represents the rotor position of the target motor, which can be specifically the rotor angle (also called electrical angle).

[0090] It should be noted that the initial two-phase current includes the first current and the second current, and I α represents the first current of the target motor on the first motor shaft, I β represents a second current of the target motor on the second motor shaft; represents a rotor flux of the target motor.

[0091] In some embodiments, the initial observed flux Including the first observation flux and the second observed flux It can be understood that the first real magnetic flux x α Refers to the first observed magnetic flux The corresponding true value of magnetic flux, the second true magnetic flux x β Refers to the second observation flux The corresponding true value of magnetic linkage.

[0092] In step 102 of some embodiments, the current state space function is defined as shown in formula (2):

[0093]

[0094] in, Represents the first current I α The derivative of The second current I β The derivative of; R represents the stator resistance of the target motor; ω represents the motor speed (also called electrical angular velocity) of the target motor; It should be noted that the initial two-phase voltage includes the first voltage and the second voltage, and U α represents the first voltage of the target motor on the first motor shaft, U β Indicates a second voltage of the target motor on the second motor shaft.

[0095] In step 103 of some embodiments, the change analysis of the initial flux observer model is performed according to the current state space function, which may be to analyze the relationship between the change of the flux of the target motor and the rotor position.

[0096] In step 104 of some embodiments, the flux observation error model may reflect the error between the initial observed flux and the initial real flux of the target motor; wherein the initial observed flux is the measured value of the motor flux, and the initial real flux is the actual value of the motor flux.

[0097] In step 105 of some embodiments, the initial rotor position of the target motor may be an electrical angle, and the motor speed may be an electrical angular velocity. Specifically, the electrical angle may be derived to obtain the motor angular velocity. The motor speed of the target motor may also be calculated by other methods, without limitation.

[0098] In some embodiments, the initial rotor position of the target motor is defined as shown in formula (3):

[0099]

[0100] in, Indicates the initial rotor position of the target motor; represents the first observed flux linkage, represents the second observed flux; L represents the inductance of the target motor; I α represents the first current of the target motor on the first motor shaft, I β Indicates a second current of the target motor on the second motor shaft.

[0101] In step 106 of some embodiments, it can be understood that both the flux observation error model and the initial flux observation change model have initial model parameters. Stability analysis is performed on the flux observation error model to calculate updated initial model parameters, and then the updated initial model parameters are substituted into the initial flux observation change model to obtain the target flux observation change model.

[0102] In step 107 of some embodiments, the observed flux (such as the initial observed flux and the target observed flux) and the two-phase current (such as the initial two-phase current and the target two-phase current) of the target motor can be reacquired at intervals of a preset unit time period. It can be understood that the difference between the initial observed flux and the target observed flux is that the acquisition time of the two is different. In some embodiments, the initial observed flux and the initial two-phase current are acquired at the same time, and the target observed flux and the target two-phase current are acquired at the same time. Specifically, the unit time period can be the time required for each step of the target motor to run, and the length of the unit time period can also be set according to demand.

[0103] In step 108 of some embodiments, the target flux observation change model is stable. Specifically, the target flux observation change model can converge, thereby ensuring the accuracy of the target rotor position calculated by the model.

[0104] See also Figure 2 In some embodiments, step 103 may include but is not limited to steps 201 to 203:

[0105] Step 201, substituting the current state space function into the initial flux observer model to obtain a target flux derivative model;

[0106] Step 202, constructing an update model according to a preset update excitation value, an initial observed flux linkage and an initial two-phase current to obtain a flux linkage update model;

[0107] Step 203: Substitute the target flux derivative model into the flux update model to obtain an initial flux observation change model.

[0108] The advantage of this embodiment is that the target flux derivative model is determined according to the current state space function, and the target flux derivative model is substituted into the flux update model to obtain the initial flux observation change model, so that the initial model parameters of the initial flux observation change model can be subsequently updated according to the motor speed to obtain a stable target flux observation change model, thereby ensuring the accuracy of the calculated target rotor position and avoiding the accuracy of the target rotor position being affected by the speed or operation stage changes of the target motor.

[0109] In step 201 of some embodiments, the target flux derivative model is defined as shown in formula (4):

[0110]

[0111] in, Represents the first real flux x α The derivative of Represents the second real magnetic flux x β The derivative of; R represents the stator resistance of the target motor; I α represents the first current of the target motor on the first motor shaft, I β represents the second current of the target motor on the second motor shaft; U α represents the first voltage of the target motor on the first motor shaft, U β Indicates a second voltage of the target motor on the second motor shaft.

[0112] In step 202 of some embodiments, the definition of the magnetic link update model is as shown in formula (5):

[0113]

[0114] in, represents the first observed flux The derivative of Represents the second observed flux The derivative of Represents the first real flux x α The derivative of Represents the second real magnetic flux x β The derivative of ;γ represents the updated incentive value; represents the first observed flux The gradient of Represents the second observed flux The gradient of represents the initial observed magnetic flux The gradient of represents the initial real magnetic flux x αβ The derivative of , and the initial real magnetic flux x αβ Including the first real magnetic link x α and the second real magnetic link x β .

[0115] The definitions of the intermediate variables in formula (5) are shown in formula (6):

[0116]

[0117] Where h(x,t) represents the first intermediate variable related to the initial real flux x, Represents the initial observed magnetic flux The second intermediate variable is Represents the second intermediate variable to the initial observed flux linkage The gradient of represents the difference between the first intermediate variable and the second intermediate variable. t represents time t.

[0118] It should be noted that the initial real magnetic flux is defined as: And, the initial observed flux is defined as:

[0119] In some embodiments, the initial observed flux includes a first observed flux and a second observed flux, the initial two-phase current includes a first current and a second current, and the initial two-phase voltage includes a first voltage and a second voltage. The initial flux observation change model is shown in formula (7):

[0120]

[0121] in, represents the first observed flux The derivative of Represents the second observed flux The derivative of α represents the first current of the target motor on the first motor shaft, I β represents the second current of the target motor on the second motor shaft; R represents the stator resistance of the target motor; L represents the inductance of the target motor; U α represents the first voltage of the target motor on the first motor shaft, U β represents the second voltage of the target motor on the second motor shaft; γ represents the updated excitation value; k1 represents the initial model parameter; ψ f Indicates the rotor flux of the target motor.

[0122] See also Figure 3 In some embodiments, the initial flux observation change model includes at least two candidate sub-formulas; step 104 may include but is not limited to steps 301 to 302:

[0123] Step 301, screening candidate sub-formulas according to the initial observed magnetic flux, and determining the candidate sub-formula containing the initial observed magnetic flux as the magnetic flux error formula;

[0124] Step 302: Substitute the flux error formula to obtain a flux observation error model.

[0125] The advantage of this embodiment is that the initial flux observation change model is converted into a flux observation error model, so that the initial model parameters in the initial flux observation change model can be subsequently updated through the flux observation error model to obtain a stable target flux observation change model, thereby ensuring the accuracy of the calculated target rotor position and avoiding the accuracy of the target rotor position being affected by changes in the speed or operating stage of the target motor.

[0126] In step 301 of some embodiments, the definition of the flux linkage error formula is as shown in formula (8):

[0127]

[0128] in, Represents the first observed magnetic flux The corresponding first observed flux error is, represents the first observed flux error The derivative of Represents the magnetic flux linkage with the second observation The corresponding second observed flux error is, Represents the second observed flux error The derivative of; γ represents the updated excitation value; L represents the inductance of the target motor; k1 represents the initial model parameter; ψ f Indicates the rotor flux of the target motor.

[0129] In step 302 of some embodiments, the definition of the flux observation error model is as shown in formula (9):

[0130]

[0131] in, represents the first observed flux error The derivative of Represents the second observed flux error The meanings of other parameters can be referred to the above formula and will not be repeated here.

[0132] See also Figure 4 In some embodiments, step 106 may include but is not limited to steps 401 to 402:

[0133] Step 401, determining a stability factor according to a flux observation error model, an initial observed flux, a rotor position and a motor speed, and obtaining a model stability factor;

[0134] Step 402: Update the initial model parameters according to the model stability factor to obtain the target model parameters, and update the initial flux observation change model according to the target model parameters to obtain the target flux observation change model.

[0135] The advantage of this embodiment is that the model stability factor is calculated by the flux observation error model, and the initial model parameters are updated according to the model stability factor to obtain a stable target flux observation change model corresponding to the target model parameters, thereby ensuring the accuracy of the calculated target rotor position and avoiding the accuracy of the target rotor position being affected by changes in the speed or operating stage of the target motor.

[0136] In step 401 of some embodiments, the model stability factor is used to characterize the influence of the motor speed on the stability of the initial flux observation change model, and the model stability factor is related to the initial model parameters.

[0137] In step 402 of some embodiments, the initial model parameters may be updated so that the model stability factor is less than or equal to a preset value. For example, when the model stability factor corresponding to the target model parameter is less than or equal to 0, it indicates that the target flux observation change model corresponding to the target model parameter is converged.

[0138] See also Figure 5 In some embodiments, step 401 may include but is not limited to steps 501 to 506:

[0139] Step 501, constructing a flux-rotor mapping factor according to the initial observed flux and rotor position to obtain the flux-rotor mapping factor;

[0140] Step 502, constructing a speed mapping factor according to the motor speed to obtain a speed mapping factor;

[0141] Step 503, substituting the flux rotor mapping factor into the flux observation error model to obtain an initial chaotic flux observer model;

[0142] Step 504, constructing a factor state space function according to the flux rotor mapping factor to obtain a factor state space function;

[0143] Step 505, substituting the factor state space function and the speed mapping factor into the initial chaotic flux observer model to obtain the target chaotic flux observer model;

[0144] Step 506: Substitute the target chaotic flux observer model into a preset stability function to obtain a model stability factor.

[0145] The advantage of this embodiment is that the model stability factor is calculated by the flux observation error model, and the initial model parameters are updated according to the model stability factor to obtain a stable target flux observation change model, thereby ensuring the accuracy of the calculated target rotor position and avoiding the accuracy of the target rotor position being affected by changes in the speed or operating stage of the target motor.

[0146] In some embodiments, the flux rotor mapping factor is defined as shown in formula (10):

[0147]

[0148] Where X represents the flux rotor mapping factor; X1 represents the first flux rotor mapping factor, X2 represents the second flux rotor mapping factor; ψ f represents the rotor flux of the target motor; θ represents the rotor position of the target motor; Represents the first observed magnetic flux The corresponding first observed flux error is, Represents the magnetic flux linkage with the second observation The corresponding second observed flux error.

[0149] In step 502 of some embodiments, the speed mapping factor is defined as shown in formula (11):

[0150]

[0151] Where, Ω(s) represents the speed mapping factor; n p represents the preset intermediate parameter, and its specific value can be set according to the requirements; γ represents the updated excitation value; ω represents the motor speed of the target motor; ψ f Indicates the rotor flux of the target motor.

[0152] In step 503 of some embodiments, the definition of the initial chaotic flux observer model is as shown in formula (12):

[0153]

[0154] in, represents the first observed flux error The derivative of Represents the second observed flux error The meaning of other parameters can be found in the parameter description of the above formula and will not be repeated here.

[0155] The definition of the first mapping factor intermediate parameter σ(X) is shown in formula (13):

[0156]

[0157] The intermediate parameters of the above formula (such as J, e Jθ The definition of (etc.) is shown in formula (14):

[0158]

[0159] The meanings of the parameters can be found in the parameter descriptions of the above formulas and will not be repeated here.

[0160] In step 504 of some embodiments, the definition of the factor state space function is as shown in formula (15):

[0161]

[0162] in, represents the derivative of the flux rotor mapping factor X, represents the derivative of the rotor position θ of the target motor; n p Represents the preset state space function parameters, and its initial value can be set according to the requirements. The meaning of other parameters can refer to the parameter description of the above formula, which will not be repeated here.

[0163] In step 505 of some embodiments, the definition of the target chaotic flux observer model is as shown in formula (16):

[0164]

[0165] in, Indicates the time scaling parameter; the meanings of other parameters can be found in the parameter description of the above formula, which will not be repeated here. The definition of is shown in formula (17):

[0166]

[0167] In some embodiments, the model stability factor is defined as shown in formula (18):

[0168]

[0169] in, represents the model stability factor; X1 represents the first flux rotor mapping factor, X2 represents the second flux rotor mapping factor; k1 represents the initial model parameter; the definition of the flux rotor mapping factor can refer to formula (10).

[0170] In some embodiments, the model stability factor can be adjusted by adjusting the initial model parameter k1, thereby adjusting the size of the stable domain of the initial flux observation change model to update it to a suitable target flux observation change model. For example, when the initial model parameter k1 is small (such as k1=0.2), the self-starting performance of the target motor is better; when the initial model parameter k1 is large (such as k1=5), the load resistance performance of the target motor is very good. It can be seen that the embodiment of the present application can update the initial model parameters of the initial flux observation change model, so as to calculate the accurate rotor position through the target flux observation change model, and then effectively control the target motor according to the rotor position, so that the target motor can adapt to various working conditions.

[0171] See also Figure 6 The embodiment of the present application further provides a position sensorless control device for a permanent magnet synchronous motor, which can implement the above-mentioned position sensorless control method for a permanent magnet synchronous motor. The device includes:

[0172] The initial flux observer model construction module 601 is used to construct a flux mathematical model according to the initial observed flux and initial two-phase current of the target motor to obtain an initial flux observer model; wherein the initial flux observer model has initial model parameters;

[0173] A current state space function construction module 602 is used to construct a current state space function according to the initial two-phase voltage and the initial two-phase current of the target motor to obtain a current state space function;

[0174] The variation analysis module 603 is used to perform variation analysis on the initial flux observer model according to the current state space function to obtain an initial flux observation variation model; wherein the initial flux observation variation model has initial model parameters;

[0175] An error determination module 604 is used to perform error determination on the initial flux observation change model to obtain a flux observation error model;

[0176] The motor speed calculation module 605 is used to calculate the rotor position through the initial flux observation change model to obtain the initial rotor position of the target motor, and to analyze the change amount of the initial rotor position to obtain the motor speed of the target motor;

[0177] The initial model parameter updating module 606 is used to update the initial model parameters in the initial flux observation change model through the flux observation error model to obtain the target flux observation change model;

[0178] A flux current acquisition module 607 is used to acquire a target observed flux and a target two-phase current of a target motor;

[0179] The rotor position calculation module 608 is used to calculate the rotor position of the target observed flux and the target two-phase current through the target flux observation change model to obtain the target rotor position.

[0180] The specific implementation of the position sensorless control device for a permanent magnet synchronous motor is basically the same as the specific implementation of the position sensorless control method for a permanent magnet synchronous motor described above, and will not be repeated here.

[0181] Understandably, Figure 6 The order of the serial numbers of the modules in the example does not represent the order in which the modules are executed, and the embodiments of the present application do not impose any restrictions on this.

[0182] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned position sensorless control method for a permanent magnet synchronous motor when executing the computer program. The electronic device may include any intelligent terminal such as a tablet computer and a vehicle-mounted computer.

[0183] See also Figure 7 , Figure 7 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0184] The processor 701 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0185] The memory 702 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 702 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 702, and the processor 701 calls and executes the position sensorless control method for a permanent magnet synchronous motor in the embodiment of the present application;

[0186] Input / output interface 703, used to implement information input and output;

[0187] Communication interface 704, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0188] A bus 705 that transmits information between the various components of the device (e.g., the processor 701, the memory 702, the input / output interface 703, and the communication interface 704);

[0189] The processor 701 , the memory 702 , the input / output interface 703 and the communication interface 704 are connected to each other in communication within the device via a bus 705 .

[0190] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned position sensorless control method for a permanent magnet synchronous motor is implemented.

[0191] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0192] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0193] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0194] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0195] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0196] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0197] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0198] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units 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. The mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0199] The units described above 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.

[0200] 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.

[0201] 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 storage medium. 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, and the computer software product is stored in a storage medium, including multiple 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 methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0202] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A position sensorless control method for a permanent magnet synchronous motor, characterized in that: The method comprises: A flux mathematical model is constructed according to the initial observed flux and initial two-phase current of the target motor to obtain an initial flux observer model; wherein the initial flux observer model has initial model parameters; Constructing a current state space function according to the initial two-phase voltage and the initial two-phase current of the target motor to obtain a current state space function; Performing a variation analysis on the initial flux observer model according to the current state space function to obtain an initial flux observation variation model; wherein the initial flux observation variation model has the initial model parameters; Performing error determination on the initial flux observation change model to obtain a flux observation error model; Calculating the rotor position through the initial flux observation change model to obtain the initial rotor position of the target motor, and analyzing the change of the initial rotor position to obtain the motor speed of the target motor; By using the flux observation error model, the initial model parameters in the initial flux observation change model are updated to obtain a target flux observation change model; Obtaining a target observed flux and a target two-phase current of the target motor; The target rotor position is calculated by using the target flux observation change model for the target observed flux and the target two-phase current to obtain the target rotor position.

2. The method according to claim 1, characterized in that: The method of updating the initial model parameters in the initial flux observation change model by using the flux observation error model to obtain a target flux observation change model includes: Determine the stability factor according to the flux observation error model, the initial observed flux, the rotor position and the motor speed to obtain a model stability factor; The initial model parameters are updated according to the model stability factor to obtain target model parameters, and the initial flux observation change model is updated according to the target model parameters to obtain a target flux observation change model.

3. The method according to claim 2, characterized in that The determining of the stability factor according to the flux observation error model, the initial observed flux, the rotor position and the motor speed to obtain the model stability factor includes: Constructing a flux rotor mapping factor according to the initial observed flux and the rotor position to obtain a flux rotor mapping factor; Constructing a speed mapping factor according to the motor speed to obtain a speed mapping factor; Substituting the flux rotor mapping factor into the flux observation error model to obtain an initial chaotic flux observer model; Constructing a factor state space function according to the flux rotor mapping factor to obtain a factor state space function; Substituting the factor state space function and the speed mapping factor into the initial chaotic flux observer model to obtain a target chaotic flux observer model; The target chaotic flux observer model is substituted into a preset stability function to obtain the model stability factor.

4. The method according to claim 1, characterized in that: The performing a variation analysis on the initial flux observer model according to the current state space function to obtain an initial flux observation variation model includes: Substituting the current state space function into the initial flux observer model to obtain a target flux derivative model; An update model is constructed according to a preset update excitation value, the initial observed flux linkage and the initial two-phase current to obtain a flux linkage update model; The target flux derivative model is substituted into the flux update model to obtain the initial flux observation change model.

5. The method according to claim 1, characterized in that The initial magnetic flux observation change model includes at least two candidate sub-formulas; The step of performing error determination on the initial flux observation change model to obtain a flux observation error model includes: Screening the candidate sub-formulas according to the initial observed magnetic flux, and determining the candidate sub-formulas containing the initial observed magnetic flux as magnetic flux error formulas; The flux linkage error formula is substituted to obtain the flux linkage observation error model.

6. The position sensorless control method for a permanent magnet synchronous motor according to claim 2, characterized in that: The initial observed flux linkage includes a first observed flux linkage and a second observed flux linkage, the initial two-phase current includes a first current and a second current, and the initial two-phase voltage includes a first voltage and a second voltage; The initial magnetic flux observation change model is shown in the following formula: in, Represents the first observed magnetic flux The derivative of The second observed flux is The derivative of α represents the first current, I β represents the second current; R represents the stator resistance of the target motor; L represents the inductance of the target motor; U α represents the first voltage corresponding to the first current, U β represents the second voltage corresponding to the second current; γ represents the updated excitation value; k1 represents the initial model parameter; ψ f represents the rotor flux of the target motor.

7. The position sensorless control method for a permanent magnet synchronous motor according to claim 6, characterized in that: The flux rotor mapping factor includes a first flux rotor mapping factor and a second flux rotor mapping factor; The model stability factor is defined as follows: in, represents the model stability factor; X1 represents the first flux rotor mapping factor, X2 represents the second flux rotor mapping factor; k1 represents the initial model parameter; The flux rotor mapping factor is defined as: Wherein, X represents the flux rotor mapping factor; ψ f represents the rotor flux of the target motor; θ represents the rotor position of the target motor; Represents the magnetic flux linkage with the first observation The corresponding first observed flux error is, Represents the magnetic linkage with the second observation The corresponding second observed flux error.

8. A position sensorless control device for a permanent magnet synchronous motor, characterized in that: The device comprises: An initial flux observer model construction module is used to construct a flux mathematical model according to the initial observed flux and initial two-phase current of the target motor to obtain an initial flux observer model; wherein the initial flux observer model has initial model parameters; A current state space function construction module, used to construct a current state space function according to the initial two-phase voltage and the initial two-phase current of the target motor to obtain a current state space function; a variation analysis module, configured to perform variation analysis on the initial flux observer model according to the current state space function to obtain an initial flux observation variation model; wherein the initial flux observation variation model has the initial model parameters; An error determination module, used for performing error determination on the initial flux observation change model to obtain a flux observation error model; A motor speed calculation module, used to calculate the rotor position through the initial flux observation change model to obtain the initial rotor position of the target motor, and to analyze the change amount of the initial rotor position to obtain the motor speed of the target motor; An initial model parameter updating module, used to update the initial model parameters in the initial flux observation change model through the flux observation error model to obtain a target flux observation change model; A flux current acquisition module, used to acquire a target observed flux and a target two-phase current of the target motor; The rotor position calculation module is used to calculate the rotor position of the target observed flux and the target two-phase current through the target flux observation change model to obtain the target rotor position.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the position sensorless control method for a permanent magnet synchronous motor as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the position sensorless control method for a permanent magnet synchronous motor according to any one of claims 1 to 7 is implemented.

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