CN114584040B - Permanent magnet synchronous motor predicted torque control method based on discrete space vector modulation - Google Patents

Permanent magnet synchronous motor predicted torque control method based on discrete space vector modulation Download PDF

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CN114584040B
CN114584040B CN202210258167.2A CN202210258167A CN114584040B CN 114584040 B CN114584040 B CN 114584040B CN 202210258167 A CN202210258167 A CN 202210258167A CN 114584040 B CN114584040 B CN 114584040B
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cost function
voltage vector
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virtual voltage
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CN114584040A (en
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杨勇
顾明星
孙俊
樊明迪
谢门喜
肖扬
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Suzhou University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P27/00—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage
    • H02P27/04—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage
    • H02P27/06—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters
    • H02P27/08—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters with pulse width modulation
    • H02P27/12—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters with pulse width modulation pulsing by guiding the flux vector, current vector or voltage vector on a circle or a closed curve, e.g. for direct torque control
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H02P21/20—Estimation of torque
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/022—Synchronous motors
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P2207/00—Indexing scheme relating to controlling arrangements characterised by the type of motor
    • H02P2207/05—Synchronous machines, e.g. with permanent magnets or DC excitation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
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    • Y02T10/64—Electric machine technologies in electromobility

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Abstract

The application discloses a method, a system, a device and a computer readable storage medium for controlling the predicted torque of a permanent magnet synchronous motor based on discrete space vector modulation.

Description

Permanent magnet synchronous motor predicted torque control method based on discrete space vector modulation
Technical Field
The invention relates to the field of automation control, in particular to a method, a system and a device for controlling the predicted torque of a permanent magnet synchronous motor based on discrete space vector modulation and a computer readable storage medium.
Background
Compared with asynchronous motors, the permanent magnet synchronous motor has the unique advantages of small size, light weight, high power factor and high efficiency. This makes permanent magnet synchronous machines popular in various fields. The pursuit of high performance control of permanent magnet synchronous motors has been a research hotspot and difficulty. At present, the high-performance control method applied to the permanent magnet synchronous motor is not limited to the following methods: direct torque control, vector control, and deadbeat control. Direct torque control based on hysteretic comparators cannot select more accurate voltage vectors, resulting in high torque ripple and high current harmonics. The vector control based on the PI controller needs parameter setting, the dynamic regulation performance is weak, and the dynamic response is slow. The dead beat control is a method based on system parameters, and the robustness of the parameters is weak.
The model prediction control can realize the real-time prediction of the performance of the system at the future time, select the optimal control action and perform the rolling optimization. Moreover, the cost function can contain a plurality of constraint conditions, and a plurality of targets can be controlled simultaneously. Model predictive control can be divided into finite set model predictive control and continuum model predictive control. Compared with the continuous set model predictive control, the finite set model predictive control can better utilize the discrete characteristic of the inverter, does not need to calculate space vector modulation, and is convenient to realize. The method applies the finite set model prediction control to the permanent magnet synchronous motor, has quick dynamic response and strong parameter robustness, and greatly improves the control performance. Conventional finite set model predictive control only obtains the optimal voltage vector in discrete switching states of the inverter, which results in large torque ripple and flux ripple of the motor accompanied by large current harmonics. Improving steady-state performance becomes a big problem of the traditional finite set model prediction control.
The concept of virtual voltage vectors, i.e. voltage vectors with different phase angles of different magnitude, synthesized from real voltage vectors, began to appear. The experimental result shows that the virtual voltage vector can improve the steady-state performance of model predictive control: and the torque ripple and the current harmonic of the three-phase permanent magnet synchronous motor are reduced. The proposed idea of discrete space vector modulation gives a good explanation for the virtual voltage vector. Discrete space vector modulation is similar to space vector modulation, and in a control period, a plurality of discrete voltage vectors are arranged and combined by the discrete space vectors to obtain discrete virtual voltage vectors located in an inverter control area. The number of the virtual voltage vectors is limited, and as in the traditional model predictive control, the optimal voltage vector in the control set is obtained by enumerating all candidate voltage vector minimization cost functions. The model predictive control based on discrete space vector modulation not only contributes to the improvement of steady-state performance, but also solves another disadvantage that the switching frequency is not fixed. However, discrete space vector modulation is not without drawbacks, and the large number of virtual voltage vectors imposes a significant computational burden on the implementation of the prediction equation and cost function minimization.
For this reason, a motor control method with a smaller amount of calculation and higher calculation efficiency is required.
Disclosure of Invention
In view of the above, the present invention provides a method, a system, a device and a computer readable storage medium for controlling a predicted torque of a permanent magnet synchronous motor based on discrete space vector modulation, so as to improve the calculation efficiency. The specific scheme is as follows:
a permanent magnet synchronous motor predicted torque control method based on discrete space vector modulation comprises the following steps:
selecting all small virtual voltage vectors closest to a zero voltage vector from 8 real voltage vectors output from an inverter and a plurality of virtual voltage vectors synthesized from the real voltage vectors according to a torque prediction model based on discrete space vector modulation;
respectively substituting each small virtual voltage vector into a cost function generated by a torque prediction model based on discrete space vector modulation, and selecting a target small virtual voltage vector with the minimum cost function value;
respectively substituting two middle virtual voltage vectors which are adjacent to the target small virtual voltage vector and are not in the same vector direction into the cost function, and selecting the target middle virtual voltage vector with the minimum cost function value;
and with the zero voltage vector as an origin, substituting voltage vectors which are not calculated with cost function values and are within an included angle formed by the vector direction of the target small virtual voltage vector and the direction of the virtual voltage vector in the target into the cost function respectively, and selecting the target voltage vector with the minimum cost function value.
Optionally, the cost function is:
Figure BDA0003549556260000021
wherein λ represents a predetermined weight coefficient, T e Which is indicative of an electromagnetic torque, is,
Figure BDA0003549556260000022
representing a reference electromagnetic torque, # s Represents a stator flux linkage, <' > in combination>
Figure BDA0003549556260000023
Indicating the reference stator flux linkage and k indicating time k.
Optionally, the selecting, according to the discrete space vector modulation-based torque prediction model, all small virtual voltage vectors closest to the zero voltage vector from among 8 real voltage vectors output from the inverter and a plurality of virtual voltage vectors synthesized from the real voltage vectors includes:
according to a torque prediction model based on discrete space vector modulation, 6 small virtual voltage vectors closest to a zero voltage vector are selected from 8 real voltage vectors output from an inverter and 30 virtual voltage vectors synthesized from the real voltage vectors.
Optionally, the step of respectively substituting each small virtual voltage vector into a cost function generated by a torque prediction model based on discrete space vector modulation, and selecting a target small virtual voltage vector with a minimum cost function value includes:
and respectively substituting the 6 small virtual voltage vectors into a cost function generated by a torque prediction model based on discrete space vector modulation, and selecting a target small virtual voltage vector with the minimum cost function value.
Optionally, the process of selecting the target voltage vector with the minimum cost function value by respectively substituting the voltage vectors, which are not calculated with the cost function value, within an included angle range formed by the vector direction of the target small virtual voltage vector and the virtual voltage vector direction in the target with the zero voltage vector as an origin to the cost function includes:
taking the zero voltage vector as an origin, the vector direction of the target small virtual voltage vector as a hypotenuse, the real voltage vector as a terminal point of the hypotenuse, and the virtual voltage vector direction in the target as a right-angle side to construct a right-angled triangle;
and substituting the voltage vectors which are included in the right-angle triangle and are not calculated with the cost function values into the cost function respectively, and selecting the target voltage vector with the minimum cost function value.
The invention also discloses a system for controlling the predicted torque of the permanent magnet synchronous motor based on discrete space vector modulation, which comprises the following components:
the first virtual voltage selection module is used for selecting all small virtual voltage vectors closest to a zero voltage vector from 8 real voltage vectors output by the inverter and a plurality of virtual voltage vectors synthesized according to the real voltage vectors according to a torque prediction model based on discrete space vector modulation;
the cost function calculation module is used for respectively substituting each small virtual voltage vector into a cost function generated by a torque prediction model based on discrete space vector modulation, and selecting a target small virtual voltage vector with the minimum cost function value;
the second virtual voltage selection module is used for respectively substituting two middle virtual voltage vectors which are adjacent to the target small virtual voltage vector and are not in the same vector direction into the cost function, and selecting the target middle virtual voltage vector with the minimum cost function value;
and the target voltage vector selection module is used for taking the zero voltage vector as an origin, respectively substituting the voltage vectors which are not calculated with the cost function values and are within an included angle formed by the vector direction of the target small virtual voltage vector and the direction of the target medium virtual voltage vector into the cost function, and selecting the target voltage vector with the minimum cost function value.
Optionally, the cost function is:
Figure BDA0003549556260000041
wherein λ represents a predetermined weight coefficient, T e Which is indicative of an electromagnetic torque, is,
Figure BDA0003549556260000042
representing a reference electromagnetic torque, # s Represents the stator flux linkage, and/or is present in the stator>
Figure BDA0003549556260000043
Indicating the reference stator flux linkage and k indicating time k.
Optionally, the target voltage vector selecting module includes:
the range determining unit is used for constructing a right triangle by taking the zero voltage vector as an origin, the vector direction of the target small virtual voltage vector as a hypotenuse, the real voltage vector as the terminal point of the hypotenuse and the virtual voltage vector direction in the target as a right-angle side;
and the target voltage vector selecting unit is used for respectively substituting the voltage vectors which are included in the right-angle triangle and have no cost function value calculated into the cost function, and selecting the target voltage vector with the minimum cost function value.
The invention also discloses a permanent magnet synchronous motor predicted torque control device based on discrete space vector modulation, which comprises the following steps:
a memory for storing a computer program;
a processor for executing the computer program to implement the method for controlling the predicted torque of the permanent magnet synchronous motor based on discrete space vector modulation as described above.
The invention also discloses a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the method for controlling the predicted torque of the permanent magnet synchronous motor based on the discrete space vector modulation.
The invention discloses a permanent magnet synchronous motor predicted torque control method based on discrete space vector modulation, which comprises the following steps: selecting all small virtual voltage vectors closest to a zero voltage vector from 8 real voltage vectors output from an inverter and a plurality of virtual voltage vectors synthesized from the real voltage vectors according to a torque prediction model based on discrete space vector modulation; respectively substituting each small virtual voltage vector into a cost function generated by a torque prediction model based on discrete space vector modulation, and selecting a target small virtual voltage vector with the minimum cost function value; respectively substituting two middle virtual voltage vectors which are adjacent to the target small virtual voltage vector and are not in the same vector direction into the cost function, and selecting the target middle virtual voltage vector with the minimum cost function value; and with the zero voltage vector as an origin, substituting voltage vectors which are not calculated with cost function values and are within an included angle formed by the vector direction of the target small virtual voltage vector and the direction of the virtual voltage vector in the target into the cost function respectively, and selecting the target voltage vector with the minimum cost function value.
According to the method, the target small virtual voltage vector with the lowest cost function value is selected from all the small virtual voltage vectors, the target medium virtual voltage vector is selected according to the target small virtual voltage vector, the final target voltage vector selection range is limited, and the target voltage vector with the lowest cost function value in the range is selected from the range limited by the target small virtual voltage vector and the target medium virtual voltage vector, so that the calculation times of calculating the target voltage vector are greatly reduced, each voltage vector does not need to be calculated, and the time for realizing the model prediction torque control method based on space vector modulation is greatly reduced.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for controlling a predicted torque of a permanent magnet synchronous motor based on discrete space vector modulation according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a topology of a two-level voltage source power inverter according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a switching state and a corresponding voltage vector of a two-level voltage source power inverter according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a spatial distribution of virtual voltage vectors according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a small virtual voltage vector selection according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of selecting a medium virtual voltage vector according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of selecting a target virtual voltage vector according to an embodiment of the present invention;
FIG. 8 is a block diagram of a discrete space vector modulation model predictive torque control system according to an embodiment of the present invention;
fig. 9 is a schematic structural diagram of a system for predicting torque control of a permanent magnet synchronous motor based on discrete space vector modulation according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention discloses a method for controlling the predicted torque of a permanent magnet synchronous motor based on discrete space vector modulation, which is shown in figure 1 and comprises the following steps:
s11: according to a torque prediction model based on discrete space vector modulation, all small virtual voltage vectors closest to a zero voltage vector are selected from 8 real voltage vectors output from an inverter and a plurality of virtual voltage vectors synthesized from the real voltage vectors.
Specifically, a mathematical model of the three-phase permanent magnet synchronous motor in the rotating coordinate system (d-q) can be represented by the following equations (1) and (2):
Figure BDA0003549556260000061
Figure BDA0003549556260000062
in the formula u d And u q Stator voltage component being d-q axis, i d And i q Stator current component of d-q axis,. Psi d And psi q Is the flux linkage component of the d-q axis,. Psi f Is a permanent magnet flux linkage, R s Is stator resistance, ω e Is the electrical angular velocity, p is the number of pole pairs of the motor, T e Is an electromagnetic torque.
For surface-mounted permanent magnet synchronous motors, L is d ＝L q ＝L s ，L d Is the component of the motor stator inductance in the d-axis, L q Is the component of the motor stator inductance in the q-axis, L s Is the motor stator inductance, then flux linkage equation (3) is:
Figure BDA0003549556260000063
specifically, when the prediction model equation is established, the mathematical model in the continuous state needs to be discretized, and the forward euler method is adopted to discretize the equation (1), which can be expressed as the following equation (4):
Figure BDA0003549556260000071
equation (4) above is a discrete equation for the stator current. In the formula, T s Is the sampling period, u d (k+1),u q (k + 1) is the d-q axis voltage at time k +1, i d (k+1),i q (k + 1) is the d-q axis current at time k + 1.
Specifically, it is natural after obtaining the current of d-q axisThe electromagnetic torque T at the moment k +1 can be obtained e And stator flux linkage Ψ s ：
Figure BDA0003549556260000072
Figure BDA0003549556260000073
Specifically, a torque prediction model based on discrete space vector modulation is obtained based on the formula (5) and the formula (6), and in the finite set model prediction control, the cost function is a judgment standard for selecting the optimal action of the next control period. The constraint condition of reasonably selecting the cost function is extremely important for model prediction control. Torque and flux linkage are two variables that are most closely related to motor performance, and torque ripple and flux linkage ripple are important indicators for measuring motor performance. Therefore, the constraints of choosing torque and flux linkage as cost functions are most suitable, and considering the ability to ensure following the reference, the cost function g of the present application can be defined as:
Figure BDA0003549556260000074
wherein λ represents a predetermined weight coefficient, T e Which is indicative of an electromagnetic torque, is,
Figure BDA0003549556260000075
representing a reference electromagnetic torque, # s Represents the stator flux linkage, and/or is present in the stator>
Figure BDA0003549556260000076
Indicating the reference stator flux linkage and k indicating time k.
Specifically, the inverter driving the three-phase pmsm to operate affects the distribution of the real voltage vector, for example, in the embodiment of the present application, a two-level voltage source power inverter is used to drive a three-phase pmsm, wherein the topology of the inverter is as shown in fig. 2.
Specifically, in a two-level voltage source inverter topology, each group of bridge arms has two switching states, and three groups of bridge arms have 8 switching states in total. One switching state generates one voltage vector, and the voltage vector output by the two-level inverter can be given by the following expressions (8) and (9):
V j ＝U dc (S a +e j2π/3 S b +e j4π/3 S c ) (8)
Figure BDA0003549556260000081
in the formula of U dc Is the DC bus voltage, S j (j = a, b, c) represents the switch state. The correspondence between the switching state and the voltage vector is shown in FIG. 3, V j (S a ,S b ,S c ) Representing voltage vectors corresponding to the switch states of the two-level voltage source inverter.
Specifically, the core idea of discrete space vector modulation is to utilize the control region of the inverter more, and synthesize an additional voltage vector in the control region through the existing actual voltage vector, and the synthesized voltage vector is called as a virtual voltage vector. Specifically, a sampling period is artificially divided into N sections, each of which only applies one true voltage vector. Any one of the virtual voltage vectors can be expressed as shown in equation (10):
Figure BDA0003549556260000082
t 1 +t 2 +…+t N ＝T s (11)；
V real ∈{V 0 ,V 1 ,V 2 ,V 3 ,V 4 ,V 5 ,V 6 ,V 7 } (12)；
in the formula, V vir Representing a virtual voltage vector, V real Representing the true voltage vector.
In particular, according toThe total number n of the synthesized virtual voltage vectors is shown in equation (13) vir (excluding 8 true voltage vectors) is determined by the number N.
n vir ＝3N 2 +3N-6 (13)
Specifically, in a specific implementation scenario, 8 true voltage vectors divide the control area into 6 sectors. In each sector, the virtual voltage vector may be composed of two effective voltage vectors and one zero voltage vector.
Specifically, fig. 4 shows the distribution of all virtual voltage vectors when N =3, and the synthesized 30 virtual voltage vectors can be divided into three categories: 6 small virtual voltage vectors (V) 8 ～V 13 ) (ii) a 12 medium virtual voltage vectors (V) 14 ～V 25 ) (ii) a 12 large virtual voltage vectors (V) 26 ～V 37 ). If the optimal voltage vector is selected by adopting an enumeration method, the prediction equation and the cost function minimization need to be calculated for 38 times respectively, which needs to consume a large amount of time.
Specifically, as shown in FIG. 5, the small virtual voltage vector is a relative distance zero voltage vector (V) 0 、V 7 ) The nearest circle of virtual voltage vector, the subsequent middle virtual voltage vector and the large virtual voltage vector are analogized in sequence, the absolute values of the middle virtual voltage vector and the large virtual voltage vector are respectively greater than the virtual voltage vector of the previous stage, the absolute value of the middle virtual voltage vector is greater than the small virtual voltage vector, the absolute value of the large virtual voltage vector is greater than the middle virtual voltage vector, and the specific relative position relationship between the large virtual voltage vector, the middle virtual voltage vector, the small virtual voltage vector and the medium virtual voltage vector can be seen in fig. 5.
S12: and respectively substituting each small virtual voltage vector into a cost function generated by a torque prediction model based on discrete space vector modulation, and selecting a target small virtual voltage vector with the minimum cost function value.
Specifically, each small virtual voltage vector is respectively substituted into a cost function generated by a torque prediction model based on discrete space vector modulation, a cost function value of each small virtual voltage vector is calculated, and the small virtual voltage vector with the smallest cost function value is selected as a target small virtual voltage vector to serve as one of the references.
For example, as shown in FIG. 5, 6 small virtual voltage vectors (V) 8 ,V 9 ,V 10 ,V 11 ,V 12 ,V 13 ) As a control set for the first step of the optimization. And evaluating the 6 small virtual voltage vectors by using a cost function (7) to obtain the target small virtual voltage vector with the minimum cost function value.
S13: and respectively substituting two middle virtual voltage vectors which are adjacent to the target small virtual voltage vector and are not in the same vector direction into the cost function, and selecting the target middle virtual voltage vector with the minimum cost function value.
Specifically, selecting two medium virtual voltage vectors whose vector directions are not the same as the vector direction of the target small virtual voltage vector in the dimension of the medium virtual vector corresponds to selecting two medium virtual voltage vectors adjacent to each other on the left and right of the target small virtual voltage vector, for example, as shown in fig. 6, assuming that the target small virtual voltage vector V is a target small virtual voltage vector V opt1 Is a V 8 Two middle virtual voltage vectors (V) adjacent to the middle virtual voltage vector 15 ,V 25 ) The virtual voltage vector V in the target with the minimum cost function value is selected by substituting the cost function (7) into the same way opt2 E.g. V 15 。
S14: and (3) taking the zero voltage vector as an original point, respectively substituting the voltage vectors which are not calculated with the cost function values and are within an included angle formed by the vector direction of the target small virtual voltage vector and the virtual voltage vector direction in the target into the cost function, and selecting the target voltage vector with the minimum cost function value.
Specifically, finally, the zero voltage vector is used as the origin, the voltage vectors with the cost function values not calculated within the included angle formed by the vector direction of the target small virtual voltage vector and the virtual voltage vector direction in the target are respectively substituted into the cost function, and the target voltage vector with the minimum cost function value is selected, for example, as shown in fig. 7, from all the voltage vectors (V) in an enumerated form 0 ,V 1 ,V 7 ,V 8 ,V 14 ,V 15 ,V 26 ) Meter for measuringAll voltage vectors with cost function values not calculated before are calculated, and taking fig. 5 and 6 as examples, the voltage vector required to be calculated at this time includes V 0 、V 1 、V 7 、V 14 And V 26 And the target voltage vector is selected and substituted into the next control period, so that the torque of the motor at the next moment is predicted, the calculation times are reduced, the virtual voltage vector distribution diagram shown in fig. 3 is taken as an example, the calculation times are reduced from 38 times to 13 times, and the calculation efficiency is greatly improved.
Therefore, the target small virtual voltage vector with the lowest cost function value is selected from all the small virtual voltage vectors, the target medium virtual voltage vector is selected according to the target small virtual voltage vector, the final target voltage vector selection range is limited, and the target voltage vector with the lowest cost function value in the range is selected from the range limited by the target small virtual voltage vector and the target medium virtual voltage vector, so that the calculation times of calculating the target voltage vector are greatly reduced, each voltage vector does not need to be calculated, and the time for realizing the model prediction torque control method based on space vector modulation is greatly reduced.
Further, in another specific embodiment, a right triangle may be constructed based on the zero voltage vector, the target small virtual voltage vector and the target medium virtual voltage vector, and further define the calculation range, for example, as shown in fig. 6 and 7, specifically, a right triangle is constructed by using the zero voltage vector as an origin, the vector direction of the target small virtual voltage vector as a hypotenuse, the real voltage vector as a hypotenuse end point, and the target medium virtual voltage vector direction as a right-angled side; and respectively substituting the voltage vectors which are included in the right-angle triangle and are not calculated with the cost function values into the cost function, and selecting the target voltage vector with the minimum cost function value.
Specifically, referring to fig. 5, the control area is divided into six sectors by the real voltage vector, and each sector can be further divided into two small right-angled triangle areas, that is, twelve right-angled triangles in total.
Specifically, a control block diagram of the proposed model predictive torque control method based on discrete space vector modulation is shown in fig. 8. The outer ring of the motor speed is controlled by a PI controller. And in the current control period, three-phase stator current is obtained by sampling, the current component of a rotating reference system is obtained through coordinate transformation, and the current component is substituted into a prediction equation to predict torque and flux linkage. By adopting the optimization method, the cost function is used as an evaluation criterion to select a more appropriate voltage vector to be applied to the next control period.
Correspondingly, the embodiment of the present invention further discloses a system for controlling a predicted torque of a permanent magnet synchronous motor based on discrete space vector modulation, as shown in fig. 9, the system includes:
a first virtual voltage selection module 11, configured to select, according to a torque prediction model based on discrete space vector modulation, all small virtual voltage vectors closest to a zero voltage vector from among 8 real voltage vectors output from an inverter and a plurality of virtual voltage vectors synthesized from the real voltage vectors;
the cost function calculation module 12 is configured to substitute each small virtual voltage vector into a cost function generated by a torque prediction model based on discrete space vector modulation, and select a target small virtual voltage vector with a minimum cost function value;
the second virtual voltage selecting module 13 is configured to substitute two middle virtual voltage vectors that are adjacent to the target small virtual voltage vector and are not in the same vector direction into the cost function, and select a target middle virtual voltage vector having a smallest cost function value;
and the target voltage vector selection module 14 is configured to use a zero voltage vector as an origin, and substitute voltage vectors, which are not calculated with cost function values, within an included angle range formed by a vector direction of the small target virtual voltage vector and a virtual voltage vector direction in the target into the cost function, respectively to select a target voltage vector with a minimum cost function value.
Therefore, the embodiment of the invention selects the target small virtual voltage vector with the lowest cost function value from all the small virtual voltage vectors, then selects the virtual voltage vector in the target according to the selection, limits the final target voltage vector selection range, and finally selects the target voltage vector with the lowest cost function value in the range defined by the target small virtual voltage vector and the virtual voltage vector in the target, so that the calculation times of calculating the target voltage vector are greatly reduced, calculation of each voltage vector is not needed, and the time for realizing the model predictive torque control method based on space vector modulation is greatly reduced.
Wherein the cost function is:
Figure BDA0003549556260000111
wherein λ represents a predetermined weight coefficient, T e Which is indicative of an electromagnetic torque, is,
Figure BDA0003549556260000112
representing a reference electromagnetic torque, # s Represents the stator flux linkage, and/or is present in the stator>
Figure BDA0003549556260000113
Indicating the reference stator flux linkage and k indicating time k.
Specifically, the first virtual voltage selection module 11 is specifically configured to select, according to a discrete space vector modulation-based torque prediction model, 6 small virtual voltage vectors closest to the zero voltage vector from among 8 real voltage vectors output from the inverter and 30 virtual voltage vectors synthesized from the real voltage vectors.
Specifically, the cost function calculating module 12 is specifically configured to substitute the 6 small virtual voltage vectors into a cost function generated by a torque prediction model based on discrete space vector modulation, and select a target small virtual voltage vector having a minimum cost function value.
Specifically, the target voltage vector selection module 14 may include a range determination unit and a target voltage vector selection unit; wherein the content of the first and second substances,
the range determining unit is used for constructing a right triangle by taking the zero voltage vector as an origin, the vector direction of the target small virtual voltage vector as a hypotenuse, the real voltage vector as a hypotenuse end point and the virtual voltage vector direction in the target as a right-angle side;
and the target voltage vector selecting unit is used for respectively substituting the voltage vectors which are included in the right-angled triangle and are not calculated with the cost function values into the cost function, and selecting the target voltage vector with the minimum cost function value.
In addition, the embodiment of the invention also discloses a permanent magnet synchronous motor predicted torque control device based on discrete space vector modulation, which comprises the following steps:
a memory for storing a computer program;
a processor for executing a computer program to implement the discrete space vector modulation based permanent magnet synchronous motor predicted torque control method as described above.
In addition, the embodiment of the invention also discloses a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the method for controlling the predicted torque of the permanent magnet synchronous motor based on the discrete space vector modulation is realized.
Finally, it should also be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The technical content provided by the present invention is described in detail above, and the principle and the implementation of the present invention are explained in this document by applying specific examples, and the above description of the examples is only used to help understanding the method of the present invention and the core idea thereof; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (10)

1. A permanent magnet synchronous motor predicted torque control method based on discrete space vector modulation is characterized by comprising the following steps:
selecting all small virtual voltage vectors closest to a zero voltage vector from 8 real voltage vectors output from an inverter and a plurality of virtual voltage vectors synthesized from the real voltage vectors according to a torque prediction model based on discrete space vector modulation;
respectively substituting each small virtual voltage vector into a cost function generated by a torque prediction model based on discrete space vector modulation, and selecting a target small virtual voltage vector with the minimum cost function value;
respectively substituting two middle virtual voltage vectors which are adjacent to the target small virtual voltage vector and are not in the same vector direction into the cost function, and selecting the target middle virtual voltage vector with the minimum cost function value;
and with the zero voltage vector as an origin, substituting voltage vectors which are not calculated with cost function values and are within an included angle formed by the vector direction of the target small virtual voltage vector and the direction of the virtual voltage vector in the target into the cost function respectively, and selecting the target voltage vector with the minimum cost function value.
2. The discrete space vector modulation-based permanent magnet synchronous motor predicted torque control method according to claim 1, wherein the cost function is:
Figure FDA0003549556250000011
wherein λ represents a predetermined weight coefficient, T e Which is indicative of an electromagnetic torque, is,
Figure FDA0003549556250000012
representing a reference electromagnetic torque, # s A flux linkage of the stator is shown,
Figure FDA0003549556250000013
indicating the reference stator flux linkage and k indicating time k.
3. The discrete space vector modulation-based permanent magnet synchronous motor predicted torque control method according to claim 1, wherein the process of selecting all small virtual voltage vectors closest to a zero voltage vector from among 8 real voltage vectors outputted from an inverter and a plurality of virtual voltage vectors synthesized from the real voltage vectors according to a discrete space vector modulation-based torque prediction model comprises:
according to a torque prediction model based on discrete space vector modulation, 6 small virtual voltage vectors closest to a zero voltage vector are selected from 8 real voltage vectors output from an inverter and 30 virtual voltage vectors synthesized from the real voltage vectors.
4. The discrete space vector modulation-based permanent magnet synchronous motor predicted torque control method according to claim 3, wherein the process of respectively substituting each small virtual voltage vector into a cost function generated by a discrete space vector modulation-based torque prediction model and selecting a target small virtual voltage vector with a smallest cost function value comprises:
and respectively substituting the 6 small virtual voltage vectors into a cost function generated by a torque prediction model based on discrete space vector modulation, and selecting a target small virtual voltage vector with the minimum cost function value.
5. The method as claimed in any one of claims 1 to 4, wherein the step of selecting the target voltage vector with the smallest cost function value by substituting the voltage vectors with the zero voltage vector as the origin and within an included angle formed by the vector direction of the target small virtual voltage vector and the vector direction of the target medium virtual voltage vector, for which no cost function value is calculated, into the cost function respectively comprises:
taking the zero voltage vector as an origin, the vector direction of the target small virtual voltage vector as a hypotenuse, the real voltage vector as the terminal point of the hypotenuse, and the virtual voltage vector direction in the target as a right-angle side to construct a right-angled triangle;
and substituting the voltage vectors which are included in the right-angle triangle and are not calculated with the cost function values into the cost function respectively, and selecting the target voltage vector with the minimum cost function value.
6. A permanent magnet synchronous motor predicted torque control system based on discrete space vector modulation is characterized by comprising:
the first virtual voltage selection module is used for selecting all small virtual voltage vectors closest to a zero voltage vector from 8 real voltage vectors output by the inverter and a plurality of virtual voltage vectors synthesized according to the real voltage vectors according to a torque prediction model based on discrete space vector modulation;
the cost function calculation module is used for respectively substituting each small virtual voltage vector into a cost function generated by a torque prediction model based on discrete space vector modulation, and selecting a target small virtual voltage vector with the minimum cost function value;
the second virtual voltage selection module is used for respectively substituting two middle virtual voltage vectors which are adjacent to the target small virtual voltage vector and are not in the same vector direction into the cost function, and selecting the target middle virtual voltage vector with the minimum cost function value;
and the target voltage vector selection module is used for taking the zero voltage vector as an origin, respectively substituting the voltage vectors which are not calculated with the cost function values and are within an included angle formed by the vector direction of the target small virtual voltage vector and the direction of the target medium virtual voltage vector into the cost function, and selecting the target voltage vector with the minimum cost function value.
7. The discrete space vector modulation based permanent magnet synchronous motor predicted torque control system of claim 6, wherein the cost function is:
Figure FDA0003549556250000021
wherein λ represents a predetermined weight coefficient, T e Which is indicative of an electromagnetic torque, is,
Figure FDA0003549556250000031
representing a reference electromagnetic torque, # s The flux linkage of the stator is shown,
Figure FDA0003549556250000032
indicating the reference stator flux linkage and k indicating time k.
8. The discrete space vector modulation based permanent magnet synchronous motor predicted torque control system according to claim 6 or 7, wherein the target voltage vector selection module comprises:
the range determining unit is used for constructing a right triangle by taking the zero voltage vector as an origin, the vector direction of the target small virtual voltage vector as a hypotenuse, the real voltage vector as the terminal point of the hypotenuse and the virtual voltage vector direction in the target as a right-angle side;
and the target voltage vector selecting unit is used for respectively substituting the voltage vectors which are included in the right-angled triangle and are not calculated with the cost function values into the cost function, and selecting the target voltage vector with the minimum cost function value.
9. A permanent magnet synchronous motor predicted torque control device based on discrete space vector modulation is characterized by comprising the following components:
a memory for storing a computer program;
a processor for executing the computer program to implement the discrete space vector modulation based permanent magnet synchronous motor predicted torque control method according to any one of claims 1 to 5.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, implements the discrete space vector modulation-based permanent magnet synchronous motor predicted torque control method according to any one of claims 1 to 5.
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