A gain self-adjusting discrete current regulation method for permanent magnet synchronous motor

Abstract

The embodiment of the application discloses a gain self-adjusting discrete current regulation method of a permanent magnet synchronous motor, relates to the technical field of motor control, and can reduce the calculation amount of high-performance vector control of the permanent magnet synchronous motor while guaranteeing robustness. In the application, a discrete time domain permanent magnet synchronous motor complex vector mathematical model is established, a complex vector current regulator is designed through zero-pole configuration and internal model principle, and a multi-gain parameter online identification and self-adjusting method is provided. The current control method can realize high-performance vector control of the permanent magnet synchronous motor, and has the advantages of small calculation amount, strong robustness and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of motor control, and particularly relates to a gain self-tuning discrete current regulation method of a permanent magnet synchronous motor. BACKGROUND

[0002] The permanent magnet synchronous motor is widely used in aerospace, transportation and other fields due to its high efficiency, high power density and high torque density. During the operation of the motor, the current control performance of the motor is very important. Modern control methods are usually implemented in a digital processor, and the design of a current regulator in a discrete time domain can ensure the performance in the digitalization process. The discrete time domain current regulator can be divided into two categories: proportional (P) control and proportional-integral (PI) control. In the P control method, the commonly used method is a model-based method, but the model-based current regulator is relatively sensitive to motor parameters, and the PI control method is a good alternative. The traditional discrete time domain current regulator has superior performance compared with the traditional continuous time domain designed current regulator, but introduces complex matrix coefficients. The introduction of the complex vector principle to construct a discrete time domain complex vector PI current regulator can reduce the complexity of the regulator.

[0003] In some application occasions, the motor is required to have the characteristics of high speed, high power and high power density, and the resistance and inductance parameters of the motor are small. In this regard, although the discrete time domain current regulator provides higher robustness, small parameter errors can still significantly deteriorate the performance of the current regulator. Parameter identification and self-tuning technology is an effective measure to improve the performance of the motor drive system. Three main online estimation methods: the first is an artificial intelligence theory-based method, which requires high-performance hardware to execute. The second is a numerical method, in which the recursive least squares method is widely studied. However, this method is complex to calculate, cannot guarantee convergence, and is difficult to apply to a discretized model. The third method is an observer method. The sliding mode observer can solve the problems caused by the nonlinearity of the inverter and the uncertainty of the system parameters, but the sliding mode observer can cause severe chattering. The disturbance observer can suppress external disturbances in servo and drive systems, but it is difficult to extract individual parameters from the concentrated disturbance signal. Although the adaptive observer has a complex design process, it can flexibly select the parameters that need to be adaptively adjusted, and the calculation efficiency is greatly improved compared with the recursive least squares method.

[0004] Therefore, how to reduce the calculation amount of the high-performance vector control of the permanent magnet synchronous motor while guaranteeing the robustness has become a research topic. SUMMARY

[0005] Embodiments of the present application provide a gain self-tuning discrete current regulation method of a permanent magnet synchronous motor, which can reduce the calculation amount of the high-performance vector control of the permanent magnet synchronous motor while guaranteeing the robustness.

[0006] To achieve the above object, embodiments of the present application adopt the following technical solutions:

[0007] A gain self-adapting discrete current regulation method for a permanent magnet synchronous motor, comprising:

[0008] S1, a fully-discretized double-vector model of the permanent magnet synchronous motor is established;

[0009] S2, a discrete time-domain current regulator is obtained according to the fully-discretized double-vector model of the permanent magnet synchronous motor;

[0010] S3, a gain self-adapting observer corresponding to the discrete time-domain current regulator is established, and the gain self-adapting observer is used for gain self-adapting of the discrete current of the permanent magnet synchronous motor.

[0011] In S1, the following steps are included: S11, a voltage model of the permanent magnet synchronous motor is established; S12, a double-vector model is established according to the voltage model; and S13, the double-vector model is discretized to obtain the fully-discretized double-vector model.

[0012] Specifically, in S11, the voltage model of the permanent magnet synchronous motor is as follows:

[0013] wherein u d is a d-axis stator voltage of the permanent magnet synchronous motor, u q is a q-axis stator voltage, i d is a d-axis stator current, i q is a q-axis stator current, R s is a motor stator resistance, L d is a d-axis stator inductance, L q is a q-axis stator inductance, ω e is a motor electrical angular velocity, is a permanent magnet flux linkage;

[0014] In S12, the double-vector model is as follows: wherein u vd , u vq are voltage vectors of d-axis and q-axis respectively, i vd , i vq are current vectors of d-axis and q-axis respectively, and j represents an imaginary number.

[0015] The fully-discretized double-vector model is as follows: wherein i vd is a d-axis vector current, and i vd = i d + j0, i d is a d-axis stator current in a two-phase rotating coordinate system, and i vqis the q-axis vector current, and i vq = 0 + ji q , i q is the motor q-axis stator current in two-phase rotating coordinate system, k represents the sampling time, k+1 represents the next time of k, T s is the sampling period, E vd is the motor d-axis back EMF vector, and is the motor stator flux linkage, E vq is the motor d-axis back EMF vector, and

[0016] In S2, the method comprises: establishing a frequency domain model of the permanent magnet synchronous motor by using the fully-discretized double-vector model; and establishing the discrete-time current regulator according to the frequency domain model of the permanent magnet synchronous motor.

[0017] The current regulator is directly designed in the discrete-time domain, and can reduce the error in the algorithm digital implementation process. The discrete-time permanent magnet synchronous motor frequency domain model derived from the fully-discretized double-vector model of the permanent magnet synchronous motor is: G vd (z) is a transfer function of the d-axis discrete-time current vector and the voltage vector, G vq (z) is a transfer function of the q-axis discrete-time current vector and the voltage vector, z -1 represents a single-tap delay, k dex , k qex , k dbl , k qbl is a coefficient related to the motor stator resistance, the motor d-axis inductance and the q-axis inductance, and the specific expression is:

[0018]

[0019] On the basis of the permanent magnet synchronous motor frequency domain model, a nominal discrete complex vector current regulator with a bandwidth factor K bw is designed based on the zero-pole cancellation principle and the internal model principle. The discrete-time current regulator comprises: wherein K bw is a bandwidth factor, is a transfer function of the d-axis discrete-time complex vector current regulator, is a transfer function of the q-axis discrete-time complex vector current regulator, and are estimated values of k dex , k dbl , k qex , k qbl .

[0020] The current regulator combines gain online self-tuning technology to further improve the dynamic performance of the current control system.

[0021] wherein k dex0 , k dbl0 , k qex0 and k qbl0 are initial values of k dex , k dbl , k qex and k qbl , a dex , a dbl , a qex and a qbl are first type coefficients set respectively for k dex , k dbl , k qex and k qbl , b dex , b dbl , b qex and b qbl are second type coefficients set respectively for k dex , k dbl , k qex and k qbl , x dex , x dbl , x qex and x qbl represent the four state variables, a dex , a dbl , a qex and a qbl represent the cumulative term coefficients of the state variables, b dex , b dbl , b qex and b qbl represent the first term coefficients of the state variables, and α dex , α dbl , α qex , α qbl > 0,

[0022] The gain self-tuning permanent magnet synchronous motor discrete current regulation method provided by the embodiment of the application establishes a discrete time domain permanent magnet synchronous motor complex vector mathematical model, designs a complex vector current regulator through zero-pole configuration and internal model principle, and simultaneously proposes a multi-gain parameter online identification and self-tuning method. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0024] Figure 1 The structure diagram of the current control system provided by the embodiment of the present application.

[0025] Figure 2 The principle diagram of the q-axis current control system provided by the embodiment of the present application, wherein: i vqref = 0 + ji qref is the current reference vector; e vq = i vqref - i vq is the current error vector.

[0026] Figure 3 The derivation process of du vq in the q-axis current control system provided by the embodiment of the present application.

[0027] Figure 4 The structure diagram of the nonlinear negative feedback system provided by the embodiment of the present application.

[0028] Figure 5 The block diagram of the q-axis current control system under the gain online self-tuning technology provided by the embodiment of the present application.

[0029] Figure 6 The comparison diagram of the experimental control effect results of the proposed current regulator and the traditional current regulator provided by the embodiment of the present application. DETAILED DESCRIPTION

[0030] For those skilled in the art to better understand the technical solutions of the present application, the present application will be further described in detail below in combination with the drawings and specific embodiments. In the following, the embodiments of the present application will be described in detail, and the examples of the embodiments are shown in the drawings, wherein the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present application, but cannot be interpreted as a limitation on the present application. Those skilled in the art can understand that, unless specifically stated, the singular forms "a", "an" and "the" used herein can also include the plural forms. It should be further understood that the phrase "comprising" used in the specification of the present application means that the features, integers, steps, operations, elements and / or components exist, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we say an element is "connected" or "coupled" to another element, it can be directly connected or coupled to the other element, or there can be an intermediate element. In addition, "connected" or "coupled" used herein can include wireless connection or coupling. The phrase "and / or" used herein includes any one of the associated listed items and all combinations thereof. Those skilled in the art can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as that generally understood by those skilled in the art in the field to which the present application belongs. It should also be understood that terms such as those defined in a general dictionary should be understood to have meanings consistent with those in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as such.

[0031] The embodiment of the present application provides a gain self-adjusting discrete current regulation method for permanent magnet synchronous motor, specifically a method based on adaptive observer, which can flexibly select the parameters that need to be adaptively adjusted and has high calculation efficiency. The method of the embodiment can be applied on a controller for controlling the permanent magnet synchronous motor through a computer program. Specifically, in the control process of the permanent magnet synchronous motor, the measured motor operates in the mode of the current control method as shown in Figure 1 The real-time three-phase current i a , i b , i c is obtained through Clarke transformation and Park transformation to obtain the current i d , i q in the two-phase rotating coordinate system. i dref is given as the d-axis current loop, i qref is given as 0, the dq-axis reference current i dref , i qref is given as 0, and the feedback current i d , i qOutput voltage u after difference through multi-gain online self-tuning current regulator d 、 q , u α , u β Space vector modulation (SVPWM) is performed to drive the motor to rotate. The design of the multi-gain online self-tuning current regulator specifically includes the following steps:

[0032] Step 1: Establish a fully discrete model of a permanent magnet synchronous motor.

[0033] A fully discrete double vector model of the permanent magnet synchronous motor is established as formula (1):

[0034]

[0035] In the formula: u d is the d-axis stator voltage of the permanent magnet synchronous motor, u q is the q-axis stator voltage, i d is the d-axis stator current, i q is the q-axis stator current, R s is the stator resistance, L d is the d-axis stator inductance, L q is the q-axis stator inductance, ω e is the motor electrical angular velocity, is the permanent magnet flux linkage.

[0036] Based on the complex vector principle, the model can be rewritten as two voltage vectors and two current vectors, thereby deriving the double vector model as:

[0037]

[0038] In the formula: u vd , u vq are the d-axis and q-axis voltage vectors respectively, i vd , i vq are the d-axis and q-axis current vectors respectively, i vd =i d +j0 and i vq =i d +j0. Discretize formula (2) as:

[0039]

[0040] In the formula: k represents the sampling time, E vd , E vq are the d-axis and q-axis back electromotive force vectors respectively. Its expression is as formula (4):

[0041]

[0042] The discretization permanent magnet synchronous motor frequency domain model is derived from equation (3) as equation (5):

[0043]

[0044] where the parameters are respectively:

[0045]

[0046] Step 2: Based on the zero-pole cancellation principle and the internal model principle, a nominal discrete complex vector current regulator (CR) with a bandwidth factor of K bw is designed based on the frequency domain model (5) as equation (6):

[0047]

[0048] where and are the estimated values of k dex , k dbl , k qex , k qbl . Take the q-axis as an example, the current closed-loop control system is shown in Figure 2 , where i vqref = 0+ji qref is the current reference vector, and e vq = i vqref -i vq is the current error vector. The control system structure of the d-axis is the same as that of the q-axis.

[0049] Step 3: Design an adaptive observer.

[0050] As shown in Figure 3 , the q-axis is extended to the qex-axis and the qbl-axis. The voltage vector du vq is decomposed into components on the qex-axis and the qbl-axis. Module 1 and Module 2 illustrate the development process from the error vector e vq to the voltage vector du vq . Module 3 and Module 4 illustrate the development process from the current vector i vq to the voltage vector du vq .

[0051] The two synthesis methods of du vd and du vq in Module 2 and Module 3 are represented as equation (7):

[0052] U(z) = K(z)I(z) (7)

[0053] where:

[0054]

[0055]

[0056] K(z) = diag(k dex ,k dbl ,k qex ,k qbl )

[0057] where U(z) is the voltage vector matrix, I(z) is the current matrix, K(z) is the coefficient matrix, e d is the d-axis current error, i.e. e d = i dref - i d , e q is the q-axis current error, i.e. e q = i qref - i q . K bw represents the bandwidth factor.

[0058] The gain adaptive observer is designed as (8):

[0059]

[0060] where: is the adaptive matrix tuned by the adaptive rate , is the voltage matrix obtained by observation, and is the voltage vector error matrix.

[0061] The nonlinear negative feedback system as shown in FIG. 1 is established as: Figure 4

[0062]

[0063] where A = diag(a dex , a dbl , a qex , a qbl ), diag represents a diagonal matrix, J is a unit matrix, a dex represents the state variable cumulative term coefficient corresponding to the gain k dex , a dbl represents the state variable cumulative term coefficient corresponding to the gain k dbl , a qex represents the state variable cumulative term coefficient corresponding to the gain k qex , a qbl represents the state variable cumulative term coefficient corresponding to the gain k qbl .

[0064] To make the forward path a strictly positive real number, the parameters in the coefficient matrix A need to satisfy:​

[0065]

[0066] α dex ,α dbl ,α qex ,α qbl α dex ,α dbl ,α qex ,α qbl ∈(0,1)

[0067] According to the theorem of asymptotic hyperstability, the adaptive law is designed by solving the following inequality:

[0068]

[0069] η represents the input-output product, k1 is an integer representing a certain time, V T (k) represents the feedback at a certain time, represents the voltage vector error at a certain time, γ0 represents a set coefficient, which is set according to the initial conditions of the system.

[0070] Equation (11) can be expanded into four functions:

[0071]

[0072] Among them:

[0073] represents the dex-axis error voltage vector, represents the dbl-axis error voltage vector, represents the qex-axis error voltage vector, represents the qbl-axis error voltage vector,

[0074] Finally, the adaptive law is:

[0075]

[0076] Among them: k dex0 , k dbl0 , k qex0 , k qbl0 is the initial value of k dex , k dbl , k qex , k qbl ,

[0077] α dex , α dbl , α qex , α qbl > 0,

[0078] b dex > -0.5a dex

[0079] b qex > -0.5a qex

[0080] b dbl > -0.5a dbl

[0081] b qbl > -0.5a qbl .

[0082] In order to make (11) hold, there are

[0083]

[0084] According to the designed adaptive rate, the q-axis current discrete time domain control scheme based on the multi-gain online self-tuning technology is constructed as shown in Figure 5 The control system of the d-axis is the same as that of the q-axis. In order to automatically adjust the gain simultaneously and continuously, a high-frequency square wave signal is injected.

[0085] In order to verify the advantages of the current regulator, an experiment is conducted on the current regulator based on the disturbance observer, and the calculation time in actual operation is compared. The experimental results show that the code execution time of the proposed gain self-tuning method is only 0.9 μs, while the traditional method based on the disturbance observer needs 2.3 μs.

[0086] Figure 6 The comparison chart of the actual control effect of the traditional current regulator of the permanent magnet synchronous motor and the proposed gain self-tuning discrete current regulator. Under the condition that other experimental conditions are consistent, it can be known from the comparison results in the chart that the q-axis current overshoot under the control of the proposed current regulator is smaller, the d-axis current deviation extreme value is smaller, and the d-axis and q-axis current ripple is smaller. Therefore, the current regulation performance of the proposed current regulator is better.

[0087] Each of the embodiments in the specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments. Especially, the device embodiment is described relatively simply because it is basically similar to the method embodiment, and the relevant part can be referred to the part of the method embodiment. The above is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A gain self-tuning discrete current regulation method for permanent magnet synchronous machines, characterized in that, The method comprises the steps of: S1, establishing a fully discretized double vector model of a permanent magnet synchronous motor; S2, obtaining a discrete time domain current regulator according to the fully discretized double vector model of the permanent magnet synchronous motor; S3, establishing a gain adaptive observer corresponding to the discrete time domain current regulator, the gain adaptive observer being used for gain self-tuning of discrete currents of the permanent magnet synchronous motor; The parameter adaptive law in the gain adaptive observer is: wherein, and are the estimated values of k dex , k dbl , k qex , k qbl , k dex , k qex , k dbl , k qbl is a parameter related to the motor stator resistance, the motor d-axis inductance and the q-axis inductance, k represents the sampling time, i is a loop variable, k dex0 , k dbl0 , k qex0 and k qbl0 are initial values of k dex , k dbl , k qex and k qbl , a dex , a dbl , a qex and a qbl are first-type coefficients respectively set for k dex , k dbl , k qex and k qbl , b dex , b dbl , b qex and b qbl are second-type coefficients respectively set for k dex , k dbl , k qex and k qbl , a dex , a dbl , a qex and a qbl represent 4 state variable cumulative term coefficients, b dex , b dbl , b qex and b qbl represent 4 state variable first-order term coefficients, x dex , x dbl , x qex and x qbl represent 4 state variables, and α dex , α dbl , α qex , α qbl > 0, 2. The method of claim 1, wherein, In S1, the method comprises the steps of: S11, establishing a voltage model of the permanent magnet synchronous motor; S12, establishing a double vector model according to the voltage model; S13, performing discretization processing on the double vector model to obtain the fully discretized double vector model.

3. The method of claim 2, wherein, In S11, the voltage model of the permanent magnet synchronous motor is: where u d is the d-axis stator voltage of the permanent magnet synchronous motor, u q is the q-axis stator voltage, i d is the d-axis stator current, i q is the q-axis stator current, R s is the motor stator resistance, L d is the d-axis stator inductance, L q is the q-axis stator inductance, ω e is the motor electrical angular velocity, is the permanent magnet flux linkage; In S12, the double vector model is: wherein u vd , u vq are voltage vectors of d-axis and q-axis respectively, i vd , i vq are current vectors of d-axis and q-axis respectively, and j represents imaginary number.

4. The method of claim 3, wherein, In S11, the fully discretized double vector model is: Among them, i vd Let i be the d-axis vector current, and i vd =i d +j0, i d Let i be the d-axis stator current in a two-phase rotating coordinate system. vq Let i be the q-axis vector current, and i vq =0+ji q i q Let T be the q-axis stator current of the motor in a two-phase rotating coordinate system, k represent the sampling time, k+1 represent the next time after k, and T s For the sampling period, E vd Let be the back EMF vector of the motor's d-axis, and E is the stator flux linkage of the motor. vq Let be the back EMF vector of the motor's d-axis, and 5. The method according to claim 1 or 4, characterized in that, In S2, the method comprises the steps of: establishing a frequency domain model of the permanent magnet synchronous motor by using the fully discretized double vector model; establishing the discrete time domain current regulator according to the frequency domain model of the permanent magnet synchronous motor.

6. The method of claim 5, wherein, The frequency domain model of the permanent magnet synchronous motor comprises: G vd (z) is the transfer function of the d-axis discrete-time current vector and voltage vector, G vq (z) is the transfer function of the q-axis discrete-time current vector and voltage vector, ω e is the electrical angular velocity of the machine, T s is the sampling period, z -1 denotes a single-tap delay.

7. The method of claim 6, wherein, The discrete time domain current regulator comprises: where K bw is a bandwidth factor, is a d-axis discrete-time complex vector current regulator transfer function, is a q-axis discrete-time complex vector current regulator transfer function, ω e is the electrical angular speed of the machine, T s is the sampling period.

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