Dual three-phase motor control method, system, device and medium based on virtual vectors

Abstract

The present invention relates to the technical field of motor control, and provides a dual three-phase motor control method, system, device and medium based on virtual vectors, including determining the level output state and space voltage vector of a target motor; obtaining a first space voltage vector distribution diagram and a second space voltage vector distribution diagram, fitting to obtain a first voltage vector loop system and a second voltage vector loop system, thereby obtaining virtual vectors, and synthesizing a reference voltage vector through the virtual vectors; sampling to obtain motor operation parameters, obtaining a continuous model of the target motor, discretizing to obtain the voltage expectation value of the target motor, and determining the target reference voltage vector; constructing a cost function, obtaining a state matrix, constructing a quadratic programming equation, determining the initial parameters of the quadratic programming equation, extracting the initial input from the quadratic programming equation, and iteratively solving the quadratic programming equation to obtain the vector action time; controlling the target motor. The present invention effectively improves the efficiency of motor control.

Description

Technical Field

[0001] The present invention relates to the technical field of motor control, and particularly to a control method, system, device and medium for a dual-three-phase motor based on virtual vectors. Background Art

[0002] Compared with traditional three-phase motors, multiphase motors have the advantages of low-voltage high-power output, small torque ripple amplitude, strong fault tolerance, etc. The dual-three-phase motor has received more attention due to its close connection with traditional three-phase motors. For the inverter in a dual-three-phase motor, the three-level voltage source inverter has the advantages of low voltage stress of switching devices, small voltage change rate, small harmonic content of output voltage, etc., and is particularly suitable for medium-voltage high-power application scenarios. The three-level six-phase voltage source inverter outputs 3 level states for each phase, so the whole inverter has 3 6 state combinations, that is, 729 space voltage vectors, which is very complex for designing a space vector modulation strategy.

[0003] For the decoupling model, the vector space decoupling modeling method is usually adopted to map the variables of the motor into the α-β subspace related to electromechanical energy conversion and other subspaces unrelated to electromechanical energy conversion respectively. Only the current in the α-β subspace participates in torque generation, while the components in the x-y subspace increase harmonic disturbances. Therefore, selecting a suitable vector is the key to eliminating harmonics in a dual-three-phase permanent magnet synchronous motor. For the control method of a dual-three-phase motor, traditional control methods include field-oriented control and direct torque control. However, the PI parameter tuning process of field-oriented control is relatively cumbersome, involving fine adjustment of multiple variables. Although direct torque control has certain advantages in torque response, its steady-state performance is poor, especially in the precise control of torque and current. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the related art. For this purpose, the present invention provides a control method, system, device and medium for a dual-three-phase motor based on virtual vectors to achieve efficient control of the dual-three-phase motor.

[0005] The present invention provides a control method for a dual-three-phase motor based on virtual vectors, including:

[0006] S1: Determine a target motor, and determine the space voltage vector of the target motor according to the level output state of the target motor;

[0007] S2: Obtain the first spatial voltage vector distribution map and the second spatial voltage vector distribution map through the space voltage vector. Conduct discrete point fitting in the first spatial voltage vector distribution map and the second spatial voltage vector distribution map, and sequentially obtain the first voltage vector loop system and the second voltage vector loop system. Obtain the virtual vector through the first voltage vector loop system and the second voltage vector loop system, and synthesize the reference voltage vector through the virtual vector on the first spatial voltage vector distribution map;

[0008] S3: Sample the target motor to obtain the motor operation parameters. Obtain the continuous model through the motor operation parameters, discretize the continuous model to obtain the voltage expectation value, and determine the target reference voltage vector through the voltage expectation value and the reference voltage vector;

[0009] S4: Construct the cost function. Obtain the state matrix of the target motor through the discretized continuous model, and construct the quadratic programming equation through the state matrix and the cost function;

[0010] S5: Determine the initial parameters of the quadratic programming equation, extract the initial input from the quadratic programming equation, and use the quasi-Newton method to iteratively solve the quadratic programming equation through the initial parameters and the initial input to obtain the vector action time;

[0011] S6: Control the target motor through the vector action time and the target reference voltage vector.

[0012] According to the dual three-phase motor control method based on virtual vector provided by the present invention, in step S1, the target motor is a dual three-phase motor, and the target motor has six bridge arms, and each bridge arm has three level output states.

[0013] According to the dual three-phase motor control method based on virtual vector provided by the present invention, step S2 specifically includes:

[0014] S21: Project the space voltage vector onto the α-β space to obtain the first spatial voltage vector distribution map, and project the space voltage vector onto the x-y space to obtain the second spatial voltage vector distribution map;

[0015] S22: Conduct discrete point fitting in the second spatial voltage vector distribution map according to the distribution of the space voltage vector to obtain a plurality of closed curves as the second voltage vector loop system, and project the second voltage vector loop system into the first spatial voltage vector distribution map to obtain the first voltage vector loop system;

[0016] S23: Select a first voltage vector set in the first voltage vector loop system, select a second voltage vector set in the second voltage vector loop system according to the first voltage vector set, use the second voltage vector set as the virtual vector, and synthesize a reference voltage vector according to the volt-second balance principle and through the virtual vector.

[0017] According to the virtual-vector-based dual-three-phase motor control method provided by the present invention, in step S23, when synthesizing the reference voltage vector, divide the first spatial voltage vector distribution diagram into large sectors, medium sectors, and small sectors, and after projecting the virtual vector into the first spatial voltage vector distribution diagram, divide the projected virtual vector into large virtual vectors, medium virtual vectors, and small virtual vectors. In the small sector, synthesize a small voltage vector through two of the small virtual vectors; in the medium sector, synthesize a medium voltage vector through two of the medium virtual vectors and one of the small virtual vectors; in the large sector, synthesize a large voltage vector through two of the large virtual vectors and one of the medium virtual vectors. Use the small voltage vector, the medium voltage vector, and the large voltage vector as the reference voltage vector.

[0018] According to the virtual-vector-based dual-three-phase motor control method provided by the present invention, step S3 specifically includes:

[0019] S31: Sample the target motor to obtain motor operating parameters, where the motor operating parameters include motor phase current, motor phase voltage, and electrical angle;

[0020] S32: Perform coordinate transformation on the motor phase current and the motor phase voltage to obtain plane-axis current and plane-axis voltage, construct an initial operating matrix of the target motor, and obtain a continuous model of the target motor through the initial operating matrix, the plane-axis current, and the plane-axis voltage;

[0021] S33: Discretize the continuous model to obtain a discretized prediction model, obtain the voltage expectation value of the target motor through the discretized prediction model, calculate the target position of the voltage expectation value in the first spatial voltage vector distribution diagram, and select a target reference voltage vector through the reference voltage vector and the target position.

[0022] According to the virtual-vector-based dual-three-phase motor control method provided by the present invention, step S4 specifically includes:

[0023] S41: Construct a cost function, extract the state matrix of the target motor from the discretized prediction model, and the cost function in the kth operating cycle The expression of is:

[0024]

[0025] Among them, is the actual value of the dq-axis current in the (k + 1)-th operating cycle, is the theoretical value of the dq-axis current in the (k + 1)-th operating cycle, represents taking the Euclidean norm;

[0026] S42: Rewrite the cost function through the state matrix, and construct the quadratic programming equation through the rewritten cost function.

[0027] According to the dual three-phase motor control method based on virtual vectors provided by the present invention, step S5 specifically includes:

[0028] S51: Set an initial solution, a similarity inverse matrix, constraint conditions, and Lagrange multipliers through the target reference voltage vector, and use the initial solution, the similarity inverse matrix, the constraint conditions, and the Lagrange multipliers as the initial parameters. Extract an initial input matrix and an initial input vector from the quadratic programming equation, and use the initial input matrix and the initial input vector as the initial input;

[0029] S52: Calculate the gradient through the Lagrange multiplier, the initial input, and the initial parameters, calculate the search direction through the similarity inverse matrix and the gradient, and calculate the step size through the search direction;

[0030] S53: Iterate the initial solution through the step size under the constraint of the constraint conditions, and iterate the Lagrange multiplier, the gradient, and the similarity inverse matrix until the iteration end condition is reached, and obtain the vector action time through the iterated initial solution.

[0031] The present invention also provides a dual three-phase motor control system based on virtual vectors, including:

[0032] Space voltage vector module: used to determine the target motor, and determine the space voltage vector of the target motor through the level output state of the target motor;

[0033] Reference voltage vector module: used to obtain a first space voltage vector distribution diagram and a second space voltage vector distribution diagram through the space voltage vector, perform discrete point fitting in the first space voltage vector distribution diagram and the second space voltage vector distribution diagram, sequentially obtain a first voltage vector ring system and a second voltage vector ring system, obtain a virtual vector through the first voltage vector ring system and the second voltage vector ring system, and synthesize a reference voltage vector through the virtual vector on the first space voltage vector distribution diagram;

[0034] Target reference voltage vector module: used to sample the target motor to obtain motor operating parameters, obtain a continuous model through the motor operating parameters, discretize the continuous model to obtain the voltage expectation value, and determine the target reference voltage vector through the voltage expectation value and the reference voltage vector;

[0035] Loss function module: used to construct a cost function, obtain the state matrix of the target motor through the discretized continuous model, and construct a quadratic programming equation through the state matrix and the cost function;

[0036] Vector action time module: used to determine the initial parameters of the quadratic programming equation, extract the initial input from the quadratic programming equation, and iteratively solve the quadratic programming equation using the quasi-Newton method through the initial parameters and the initial input to obtain the vector action time;

[0037] Motor control module: used to control the target motor through the vector action time and the target reference voltage vector.

[0038] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the virtual vector-based dual three-phase motor control method described in any one of the above are implemented.

[0039] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the virtual vector-based dual three-phase motor control method described in any one of the above are implemented.

[0040] One or more of the above technical solutions in the embodiments of the present invention have at least one of the following technical effects:

[0041] The virtual vector-based dual three-phase motor control method, system, device, and medium provided by the present invention obtain a virtual vector through the first voltage vector loop system and the second voltage vector loop system, and re-divide the first space voltage vector distribution diagram to obtain a reference voltage vector, effectively considering the characteristics of different positions in the space voltage vector distribution diagram. Then, a target reference voltage vector is selected from the reference voltage vectors, and the action time of each vector in the control period is predicted by solving a quadratic programming problem. Two or three virtual vectors are selected to act on the dual three-phase motor within one control period, effectively suppressing harmonic current and improving the control effect on the motor. Thus, efficient and simple control of the dual three-phase motor is achieved.

[0042] The additional aspects and advantages of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present invention. Description of the Drawings

[0043] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0044] Figure 1 It is a schematic flowchart of a dual three-phase motor control method based on virtual vectors provided by the present invention.

[0045] Figure 2 It is a topological diagram of the target motor of the dual three-phase motor control method based on virtual vectors provided by the present invention.

[0046] Figure 3 It is a schematic diagram of the first voltage vector loop system and the second voltage vector loop system of the dual three-phase motor control method based on virtual vectors provided by the present invention.

[0047] Figure 4 It is a schematic diagram of sector division of the dual three-phase motor control method based on virtual vectors provided by the present invention.

[0048] Figure 5 It is a schematic diagram of the experimental verification results of the dual three-phase motor control method based on virtual vectors provided by the present invention.

[0049] Figure 6 It is a schematic structural diagram of a dual three-phase motor control system based on virtual vectors provided by the present invention.

[0050] Figure 7 It is a schematic structural diagram of a dual three-phase motor control device based on virtual vectors provided by the present invention.

[0051] Reference numerals:

[0052] 100, space voltage vector module; 200, reference voltage vector module; 300, target reference voltage vector module; 400, loss function module; 500, vector action time module; 600, motor control module; 1, large sector; 2, medium sector; 3, small sector; 810, processor; 820, communication interface; 830, memory; 840, communication bus. Detailed implementation manners

[0053] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention. The following embodiments are used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0054] In the description of the embodiments of the present invention, it should be noted that the terms "first", "second", and "third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0055] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of the present invention. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0056] The following Figures 1 to 7 describes the specific implementation of the present invention:

[0057] Figure 1 is a schematic flow chart of a dual-three-phase motor control method based on a virtual vector provided by the present invention, including first determining a target motor and determining the space voltage vector of the target motor; then obtaining a first space voltage vector distribution schematic diagram and a second space voltage vector distribution schematic diagram, thereby synthesizing a reference voltage vector, and then obtaining a continuous operation model and a discretized voltage expectation value, thereby determining a target reference voltage vector; then constructing a cost function, obtaining a state matrix, thereby obtaining a quadratic programming equation; then determining initial parameters and an initial input, using the quasi-Newton method to iteratively solve the quadratic programming equation to obtain the vector action time; finally, controlling the target motor through the vector action time and the target reference voltage vector.

[0058] The dual-three-phase motor control method based on a virtual vector provided by the present invention includes:

[0059] S1: Determine the target motor, and determine the space voltage vector of the target motor through the level output state of the target motor;

[0060] Further, the purpose of this stage is to obtain the space voltage vector of the target motor. Specifically, in step S1, the target motor is a dual three-phase motor, and the target motor has six bridge arms, and each bridge arm has three level output states. For the above steps, the specific implementation method in this embodiment is as follows:

[0061] First, select a dual three-phase motor as the target motor, Figure 2 As shown in the topology diagram of the dual three-phase motor, it can be seen that the dual three-phase motor has a total of six bridge arms, namely A phase, B phase, C phase, U phase, V phase, and W phase. Each bridge arm corresponds to one phase and can output three output states: positive level, 0 level, and negative level. Therefore, there are a total of kinds of level output states, and each kind of level output state can correspond to an output vector of a voltage. Therefore, the target motor has 729 kinds of space voltage vectors.

[0062] S2: Obtain the first space voltage vector distribution diagram and the second space voltage vector distribution diagram through the space voltage vector. Perform discrete point fitting in the first space voltage vector distribution diagram and the second space voltage vector distribution diagram, and sequentially obtain the first voltage vector loop system and the second voltage vector loop system. Obtain the virtual vector through the first voltage vector loop system and the second voltage vector loop system, and synthesize the reference voltage vector through the virtual vector on the first space voltage vector distribution diagram;

[0063] Further, the purpose of this stage is to fit and obtain the first voltage vector loop system and the second voltage vector loop system, then obtain the virtual vector, and finally synthesize the reference voltage vector through the virtual vector. Specifically, step S2 specifically includes:

[0064] S21: Project the space voltage vector onto the α-β space to obtain the first space voltage vector distribution diagram, and project the space voltage vector onto the x-y space to obtain the second space voltage vector distribution diagram;

[0065] S22: Perform discrete point fitting according to the distribution of the space voltage vector in the second space voltage vector distribution diagram to obtain a plurality of closed curves as the second voltage vector loop system, and project the second voltage vector loop system onto the first space voltage vector distribution diagram to obtain the first voltage vector loop system;

[0066] S23: Select the first voltage vector set in the first voltage vector loop system, select the second voltage vector set in the second voltage vector loop system according to the first voltage vector set, use the second voltage vector set as the virtual vector, and synthesize the reference voltage vector according to the volt-second balance principle and through the virtual vector.

[0067] In step S23, when synthesizing the reference voltage vector, the first spatial voltage vector distribution diagram is divided into large sectors, medium sectors, and small sectors. After projecting the virtual vector onto the first spatial voltage vector distribution diagram, the projected virtual vector is divided into large virtual vectors, medium virtual vectors, and small virtual vectors. In the small sectors, small voltage vectors are synthesized by two of the small virtual vectors; in the medium sectors, medium voltage vectors are synthesized by two of the medium virtual vectors and one of the small virtual vectors; in the large sectors, large voltage vectors are synthesized by two of the large virtual vectors and one of the medium virtual vectors. The small voltage vectors, the medium voltage vectors, and the large voltage vectors are used as the reference voltage vector.

[0068] For the above steps, the specific implementation in this embodiment is as follows:

[0069] First, project the spatial voltage vector onto the α-β plane to obtain the distribution of the spatial voltage vector in the α-β plane, that is, the first spatial voltage vector distribution diagram, and project the spatial voltage vector onto the x-y plane to obtain the distribution of the spatial voltage vector in the x-y plane, that is, the second spatial voltage vector distribution diagram.

[0070] Subsequently, select several groups of spatial voltage vectors with the smallest amplitudes in the second spatial voltage vector distribution diagram for discrete point fitting. Here, the least squares fitting algorithm is used for fitting to obtain multiple closed curves as the second voltage vector loop system. In this embodiment, there are a total of five closed curves, namely , , , , . Project the second voltage vector loop system onto the first spatial voltage vector distribution diagram to obtain the first voltage vector loop system, namely , , , , , Figure 3 (a) of which is a schematic diagram of the first voltage vector loop system, Figure 3 (b) of which is a schematic diagram of the second voltage vector loop system.

[0071] Then, select the first voltage vector set in the first voltage vector loop system, that is, select several groups of closed curves in the first voltage vector loop system, and ensure that the spatial voltage vectors on each group of closed curves can be connected to form the first voltage vector set. In this embodiment, there should be one other closed curve between a group of closed curves, so select and , and and and The connection lines of the space voltage vectors on these three sets of closed curves form the first voltage vector set. The connection line between two space voltage vectors is called a first voltage vector, and each first voltage vector does not pass through the origin of the first space voltage vector distribution diagram, but its reverse extension line passes through the origin of the first space voltage vector distribution diagram. Correspondingly, several sets of closed curves are selected in the second voltage vector loop system, and the space voltage vectors on each set of closed curves can be connected to form the second voltage vector set. The closed curves selected in the second voltage vector loop system need to correspond to the closed curves selected in the first voltage vector loop system, so the selection is and 、 and as well as and The connection lines of the space voltage vectors on these three sets of closed curves form the second voltage vector set. The connection line between two space voltage vectors is called a second voltage vector, and each second voltage vector passes through the origin of the second space voltage vector distribution diagram. The second voltage vector set is used as the virtual vector.

[0072] In the virtual vector, according to the volt-second balance principle, each second voltage vector in the virtual vector needs to follow the following relationship:

[0073]

[0074] where Q is the space voltage vector corresponding to one end of the second voltage vector, P is the space voltage vector corresponding to the other end of the second voltage vector, is the action time of Q, is the action time of P, is the time length of one operating cycle of the target motor.

[0075] When synthesizing the reference voltage vector, the first space voltage vector distribution diagram is divided into large sector 1, medium sector 2 and small sector 3. After projecting the virtual vector into the first space voltage vector distribution diagram, the projected virtual vector is divided into large virtual vector, medium virtual vector and small virtual vector, Figure 4 is the schematic diagram of sector division. Here, and The connection line of the space voltage vectors between them is called the large virtual vector, and The connection line of the space voltage vectors between them is called the medium virtual vector, and The space voltage vector connections between them are called small virtual vectors. In small sector 3, small voltage vectors are synthesized through two small virtual vectors. In medium sector 2, medium voltage vectors are synthesized through two medium virtual vectors and one small virtual vector. In large sector 1, large voltage vectors are synthesized through two large virtual vectors and one medium virtual vector. The small voltage vectors, medium voltage vectors, and large voltage vectors are used as the reference voltage vectors.

[0076] S3: Sample the target motor to obtain motor operating parameters, obtain a continuous model through the motor operating parameters, discretize the continuous model to obtain the voltage expectation value, and determine the target reference voltage vector through the voltage expectation value and the reference voltage vector;

[0077] Furthermore, the purpose of this stage is to calculate the voltage expectation value of the target motor and determine the target reference voltage vector through the voltage expectation value and the reference voltage vector. Specifically, step S3 specifically includes:

[0078] S31: Sample the target motor to obtain motor operating parameters, where the motor operating parameters include motor phase current, motor phase voltage, and electrical angle;

[0079] S32: Perform coordinate transformation on the motor phase current and the motor phase voltage to obtain plane-axis current and plane-axis voltage, construct the initial operating matrix of the target motor, and obtain the continuous model of the target motor through the initial operating matrix, the plane-axis current, and the plane-axis voltage;

[0080] S33: Discretize the continuous model to obtain a discretized prediction model, obtain the voltage expectation value of the target motor through the discretized prediction model, calculate the target position of the voltage expectation value in the first space voltage vector distribution diagram, and select the target reference voltage vector through the reference voltage vector and the target position.

[0081] For the above steps, the specific implementation methods in this embodiment are as follows:

[0082] First, sample the operating data of the target motor to obtain motor operating parameters. The motor operating parameters include the current of each phase of the target motor, that is, the motor phase current, the voltage of each phase of the target motor, that is, the motor phase voltage, and also include the electrical angle. Subsequently, perform coordinate transformation on the motor phase current and the motor phase voltage. Here, Clarke transformation and Park transformation are performed to decouple them to the d-q plane and the x-y plane, and obtain the component of the motor phase current on the d-axis and the component of the motor phase current on the q-axis and the component of the motor phase current on the x-axis and the component of the motor phase current on the y-axis The planar axis current; the component of the motor phase voltage on the d-axis can also be obtained 、the component of the motor phase voltage on the q-axis 、the component of the motor phase voltage on the x-axis and the component of the motor phase voltage on the y-axis of the planar axis voltage. Subsequently, an initial operation matrix including the first initial operation matrix F, the second initial operation matrix G, and the third initial operation matrix W is obtained, and the continuous model of the target motor can be constructed:

[0083]

[0084]

[0085] Among them, is the derivative of, is the derivative of, is the derivative of, is the derivative of, is the resistance of the stator of the target motor, is the component of the winding inductance on the d-axis, is the component of the winding inductance on the q-axis, is the electrical angle of the target motor, is the component of the winding inductance on the x-y plane, is the amplitude of the magnetic flux generated by the permanent magnet.

[0086] Then, the continuous model is discretized to obtain a discretized prediction model:

[0087]

[0088]

[0089]

[0090] Among them, is the discretized first initial operation matrix, is the discretized initial second operation matrix, is the discretized initial third operation matrix, I is the identity matrix, is the of the target motor in the kth operation cycle, that is, in this operation cycle, is the of the target motor in the kth operation cycle, is the in the k-th operating cycle of the target motor is the in the k-th operating cycle of the target motor is the in the k-th operating cycle of the target motor is the in the k-th operating cycle of the target motor is the in the k-th operating cycle of the target motor is the in the k-th operating cycle of the target motor is the in the (k + 1)-th operating cycle, i.e., the next operating cycle of the target motor is the in the (k + 1)-th operating cycle of the target motor is the in the (k + 1)-th operating cycle of the target motor is the in the (k + 1)-th operating cycle of the target motor

[0091] The expected voltage value can be solved through the discretized prediction model. The expected voltage value includes , , and :

[0092]

[0093]

[0094] wherein, is the in the (k + 1)-th operating cycle, i.e., the next operating cycle of the target motor is the in the (k + 1)-th operating cycle of the target motor is the in the (k + 1)-th operating cycle of the target motor the in the (k + 1)-th operating cycle of the target motor. M is the target initial first operating matrix, N is the target initial second operating matrix, P is the target initial third operating matrix, is the inverse matrix of the discretized initial second operating matrix.

[0095] Then, performing the Park inverse transform on the expected voltage value can obtain the position of the expected voltage value in the α-β plane:

[0096]

[0097]

[0098]

[0099] Among them, is the Park inverse transformation matrix, is the component of the motor phase voltage on the α-axis in the (k + 1)-th operating cycle of the target motor, is the component of the motor phase voltage on the β-axis in the (k + 1)-th operating cycle of the target motor, is the amplitude of the target reference voltage vector in the first spatial voltage vector distribution diagram, is the angle of the target reference voltage vector in the first spatial voltage vector distribution diagram. The target position can be obtained through the foregoing amplitude and angle. According to the sector where the target position is located in the first spatial voltage vector distribution diagram, the target reference voltage vector can be synthesized through the reference voltage vector. For example, when the target position is located in the middle sector, the reference voltage vector is the middle voltage vector, and the middle voltage vector obtained by synthesizing two middle virtual vectors and one small virtual vector in the projected virtual vectors can be selected as the target reference voltage vector.

[0100] S4: Construct a cost function, obtain the state matrix of the target motor through the discretized continuous model, and construct a quadratic programming equation through the state matrix and the cost function;

[0101] Furthermore, the purpose of this stage is to construct a quadratic programming equation through the cost function after determining the target reference voltage vector, so as to obtain the action time of the projected virtual vector participating in the synthesis of the target reference voltage vector. Specifically, step S4 specifically includes:

[0102] S41: Construct a cost function, extract the state matrix of the target motor from the discretized prediction model, and the cost function in the k-th operating cycle The expression of

[0103]

[0104] Among them, is the actual value of the dq-axis current in the (k + 1)-th operating cycle, is the theoretical value of the dq-axis current in the (k + 1)-th operating cycle, represents taking the Euclidean norm;

[0105] S42: Rewrite the cost function through the state matrix, and construct the quadratic programming equation through the rewritten cost function.

[0106] For the above steps, the specific implementation in this embodiment is as follows:

[0107] First, construct a cost function. The cost function in the k-th operating cycle has the following expression:

[0108]

[0109] where is the actual value of the dq-axis current in the (k + 1)-th operating cycle, is the theoretical value of the dq-axis current in the (k + 1)-th operating cycle, which includes the components of the current on the d-axis and q-axis, represents taking the Euclidean norm;

[0110] Subsequently, for and , extract the state matrix of the target motor from the discretized prediction model, which includes the first state matrix , the second state matrix and the third state matrix :

[0111]

[0112] , ,

[0113] Then the cost function can be rewritten as:

[0114]

[0115] where is the Park transformation matrix, is the vector amplitude matrix, is the dq-axis current value in the k-th operating cycle, is the vector action time in the k-th operating cycle, including the action times of the projected virtual vectors participating in the synthesis in the target reference voltage vector. For example, when the target position is in the middle sector, the two middle virtual vectors and one small virtual vector in the projected virtual vectors participating in the synthesis of the target reference voltage vector each have their own action times.

[0116] Construct the first auxiliary variable r, and , construct the second auxiliary variable , and , then:

[0117]

[0118] where is the transpose of r, is the transpose of , is the transpose of . Here, since r is a 2×1 matrix, is a 2×3 matrix, is a 3×1 matrix. Therefore, is a 1×1 matrix, i.e., a scalar, is also a 1×1 matrix, i.e., a scalar. Therefore, the two scalars can be combined to obtain . At this time, the solution of the cost function can be transformed into a quadratic programming problem, and the quadratic programming equation is constructed:

[0119]

[0120] where H is the initial input matrix, and , f is the initial input vector, is the transpose of f, and , min() represents finding the minimum value within the parentheses, b represents the linear constraint value of the quadratic programming equation. Taking the case where the target position is in the middle sector as an example, is the first action time, is the second action time, is the third action time, , and represent the action times of the virtual vectors after projection that participate in synthesizing the target reference voltage vector in the target reference voltage vector to be solved. For example, when the target position is in the middle sector, the action time of the small virtual vector in the reference voltage vector that participates in synthesizing the target reference voltage vector is . Among the two middle virtual vectors, the action time of one middle virtual vector is , and the action time of the other is .

[0121] S5: Determine the initial parameters of the quadratic programming equation, extract the initial input from the quadratic programming equation, and use the initial parameters and the initial input to iteratively solve the quadratic programming equation using the quasi-Newton method to obtain the vector action time;

[0122] Furthermore, the purpose of this stage is to iteratively solve the quadratic programming equation using the quasi-Newton method to obtain the vector action time. Specifically, step S5 specifically includes:

[0123] S51: Set the initial solution, the similar inverse matrix, the constraint conditions, and the Lagrange multiplier through the target reference voltage vector, and use the initial solution, the similar inverse matrix, the constraint conditions, and the Lagrange multiplier as the initial parameters. Extract the initial input matrix and the initial input vector from the quadratic programming equation, and use the initial input matrix and the initial input vector as the initial input.

[0124] S52: Calculate the gradient through the Lagrange multiplier, the initial input, and the initial parameters, calculate the search direction through the similar inverse matrix and the gradient, and calculate the step size through the search direction.

[0125] S53: Iterate the initial solution through the step size under the constraint of the constraint conditions, and iterate the Lagrange multiplier, the gradient, and the similar inverse matrix until the iteration end condition is reached. Obtain the vector action time through the iterated initial solution.

[0126] For the above steps, the specific implementation in this embodiment is as follows:

[0127] First, set the initial solution through the target reference voltage vector. Here, when the target position corresponding to the target reference voltage vector is in the small sector, since only two small virtual vectors are involved in synthesizing the target reference voltage vector, the initial solution is set to , otherwise the initial solution is set to . Then set the linear constraint value b, and b = , set the similar inverse matrix and set the Lagrange multiplier according to experience. Here, let the similar inverse matrix be the identity matrix with the same matrix dimension as H, and the constraint condition is that when the target position is in the small sector, the third value of the initial solution is always 0. Use the initial solution, the similar inverse matrix, the constraint conditions, and the Lagrange multiplier as the initial parameters, extract the initial input matrix H and the initial input vector f from the quadratic programming equation, and use the initial input matrix and the initial input vector as the initial input.

[0128] Then calculate the gradient through the Lagrange multiplier, the initial input, and the initial parameters :

[0129]

[0130] where T represents the transpose. Calculate the search direction through the similar inverse matrix and the gradient :

[0131]

[0132] Calculate the step size through the search direction :

[0133]

[0134] wherein, is the transpose of and is the transpose of .

[0135] The initial solution is iterated by a step size under the constraint of the constraint condition to obtain an iterative solution :

[0136]

[0137] In this embodiment, the implementation manner of the constraint condition may be that when the third value of the iterative solution is not 0, after dividing the third value of the iterative solution by 2, the obtained results are respectively added to the first value and the second value of the iterative solution, and the third value of the iterative solution is made 0. The Lagrange multiplier is iterated to obtain an iterative Lagrange multiplier :

[0138]

[0139] wherein, is a scale factor constant set according to experience, which is taken as 0.1 in this embodiment, is the first value of the initial solution, is the second value of the initial solution, is the third value of the initial solution.

[0140] The gradient is iterated to obtain an iterative gradient :

[0141]

[0142] Then the first update value and the second update value are calculated, and the similar inverse matrix is iterated through the first update value and the second update value to obtain an iterative similar inverse matrix :

[0143]

[0144]

[0145]

[0146] Finally, let , , , , and recalculate for iteration until the iteration end condition is reached, that is, the gradient is less than the iteration threshold set empirically, or the number of iterations reaches the upper limit of the number of iterations. Then, the initial solution at this time is taken as the target solution, and the vector action time is obtained from the target solution, that is, the first value, the second value, and the third value in the target solution are used as the action times of the three projected virtual vectors participating in the synthesis of the target reference voltage vector in sequence. If only two projected virtual vectors participate in the synthesis of the target reference voltage vector, only the first value and the second value are taken as the vector action time.

[0147] S6: Control the target motor through the vector action time and the target reference voltage vector.

[0148] Furthermore, in this stage, after obtaining the vector action time, the action times of each projected virtual vector can be obtained, so as to complete the synthesis of the target reference voltage vector in combination with the target reference voltage vector and control the target motor.

[0149] To verify the effectiveness of the present invention, on a dual-three-phase motor drive experimental platform, an experimental verification was carried out on the dual-three-phase motor control method based on virtual vectors proposed by the present invention. In terms of phase current, taking the current of phase A as an example, as Figure 5 shown, Figure 5 Figure (a) is a schematic diagram of the phase current changing with time, the unit of the horizontal axis is second, is the phase current of phase A, is the phase current of phase B, is the phase current of phase C, is the phase current of phase U, is the phase current of phase V, is the phase current of phase W. Inputting the experimental data shown in Figure 5 Figure (a) into the MATLAB tool for analysis, it can be obtained that the THD (Total Harmonic Distortion) of the phase current of phase A is 6.11%. Figure 5 Figure (b) is a schematic diagram of the x-axis and y-axis currents changing with time. Inputting the experimental data shown in Figure 5 Figure (b) into the MATLAB tool for analysis, it can be obtained that the current ripple amplitude does not exceed 2.1 A. Figure 5 Figure (c) is a schematic diagram of the speed of the dual-three-phase motor changing with time. n is the actual speed value of the target motor, and n* is the theoretical speed value. It can be seen that in terms of speed following, the speed follows well in the steady state. The unit of speed is rpm, that is, revolutions per minute, and the unit of time is second. Figure 5The error in the experiment is mainly due to a certain delay between the control command for the target motor and the actual operating condition of the motor, resulting in fluctuations in the operating state of the target motor.

[0150] The following describes the dual-three-phase motor control device based on virtual vectors provided by the present invention. The dual-three-phase motor control device described below and the dual-three-phase motor control method based on virtual vectors described above can be referred to each other correspondingly.

[0151] Figure 6 The structural schematic diagram of the dual-three-phase motor control system based on virtual vectors is exemplified, as Figure 6 shown, for implementing the dual-three-phase motor control method based on virtual vectors as described above, including:

[0152] Space voltage vector module 100: used to determine the target motor, and determine the space voltage vector of the target motor through the level output state of the target motor;

[0153] Reference voltage vector module 200: used to obtain the first space voltage vector distribution map and the second space voltage vector distribution map through the space voltage vector, perform discrete point fitting in the first space voltage vector distribution map and the second space voltage vector distribution map, sequentially obtain the first voltage vector loop system and the second voltage vector loop system respectively, obtain the virtual vector through the first voltage vector loop system and the second voltage vector loop system, and synthesize the reference voltage vector through the virtual vector on the first space voltage vector distribution map;

[0154] Target reference voltage vector module 300: used to sample the target motor to obtain motor operation parameters, obtain a continuous model through the motor operation parameters, discretize the continuous model to obtain the voltage expectation value, and determine the target reference voltage vector through the voltage expectation value and the reference voltage vector;

[0155] Loss function module 400: used to construct a cost function, obtain the state matrix of the target motor through the discretized continuous model, and construct a quadratic programming equation through the state matrix and the cost function;

[0156] Vector action time module 500: used to determine the initial parameters of the quadratic programming equation, extract the initial input from the quadratic programming equation, and perform iterative solution of the quadratic programming equation using the initial parameters and the initial input with the quasi-Newton method to obtain the vector action time;

[0157] Motor control module 600: used to control the target motor through the vector action time and the target reference voltage vector.

[0158] On the other hand, Figure 7 The structural schematic diagram of an electronic device is exemplified, asFigure 7 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840. Among them, the processor 810, the communication interface 820, and the memory 830 complete mutual communication through the communication bus 840. The processor 810 may call logic instructions in the memory 830 to execute a dual three-phase motor control method based on a virtual vector. The method includes:

[0159] S1: Determine the target motor, and determine the space voltage vector of the target motor through the level output state of the target motor;

[0160] S2: Obtain a first space voltage vector distribution diagram and a second space voltage vector distribution diagram through the space voltage vector. Perform discrete point fitting on the first space voltage vector distribution diagram and the second space voltage vector distribution diagram to obtain a first voltage vector loop system and a second voltage vector loop system respectively. Obtain a virtual vector through the first voltage vector loop system and the second voltage vector loop system, and synthesize a reference voltage vector through the virtual vector on the first space voltage vector distribution diagram;

[0161] S3: Sample the target motor to obtain motor operation parameters. Obtain a continuous model through the motor operation parameters, discretize the continuous model to obtain an expected voltage value, and determine a target reference voltage vector through the expected voltage value and the reference voltage vector;

[0162] S4: Construct a cost function, obtain the state matrix of the target motor through the discretized continuous model, and construct a quadratic programming equation through the state matrix and the cost function;

[0163] S5: Determine the initial parameters of the quadratic programming equation, extract the initial input from the quadratic programming equation, and use the quasi-Newton method to iteratively solve the quadratic programming equation through the initial parameters and the initial input to obtain the vector action time;

[0164] S6: Control the target motor through the vector action time and the target reference voltage vector.

[0165] In addition, when the logical instructions in the above-mentioned memory 830 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0166] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is configured to execute the virtual vector-based dual three-phase motor control method provided by the above-mentioned various methods. The method includes:

[0167] S1: Determine a target motor, and determine the space voltage vector of the target motor according to the level output state of the target motor;

[0168] S2: Obtain a first space voltage vector distribution diagram and a second space voltage vector distribution diagram through the space voltage vector. Perform discrete point fitting on the first space voltage vector distribution diagram and the second space voltage vector distribution diagram, and sequentially obtain a first voltage vector loop system and a second voltage vector loop system. Obtain a virtual vector through the first voltage vector loop system and the second voltage vector loop system, and synthesize a reference voltage vector on the first space voltage vector distribution diagram through the virtual vector;

[0169] S3: Sample the target motor to obtain motor operation parameters. Obtain a continuous model through the motor operation parameters, discretize the continuous model to obtain an expected voltage value, and determine a target reference voltage vector through the expected voltage value and the reference voltage vector;

[0170] S4: Construct a cost function, obtain the state matrix of the target motor through the discretized continuous model, and construct a quadratic programming equation through the state matrix and the cost function;

[0171] S5: Determine the initial parameters of the quadratic programming equation, extract the initial input from the quadratic programming equation, and use the quasi-Newton method to iteratively solve the quadratic programming equation through the initial parameters and the initial input to obtain the vector action time;

[0172] S6: Controlling the target motor based on the vector action time and the target reference voltage vector.

[0173] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative effort.

[0174] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0175] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A control method for a dual three-phase motor based on virtual vectors, characterized in that, Including: S1: Determine the target motor, and determine the space voltage vector of the target motor according to the level output state of the target motor; S2: Obtain the first space voltage vector distribution map and the second space voltage vector distribution map through the space voltage vector, perform discrete point fitting on the first space voltage vector distribution map and the second space voltage vector distribution map, and sequentially obtain the first voltage vector loop system and the second voltage vector loop system respectively. Obtain a virtual vector through the first voltage vector loop system and the second voltage vector loop system, and synthesize a reference voltage vector through the virtual vector on the first space voltage vector distribution map; wherein, step S2 specifically includes: S21: Project the space voltage vector onto the α-β space to obtain the first space voltage vector distribution map, and project the space voltage vector onto the x-y space to obtain the second space voltage vector distribution map; S22: Perform discrete point fitting according to the distribution of the space voltage vector in the second space voltage vector distribution map to obtain a plurality of closed curves as the second voltage vector loop system, and project the second voltage vector loop system into the first space voltage vector distribution map to obtain the first voltage vector loop system; S23: Select a first voltage vector set in the first voltage vector loop system, select a second voltage vector set in the second voltage vector loop system according to the first voltage vector set, use the second voltage vector set as the virtual vector, and synthesize a reference voltage vector according to the volt-second balance principle and through the virtual vector; In step S23, when synthesizing the reference voltage vector, divide the first space voltage vector distribution map into large sectors, medium sectors and small sectors, and after projecting the virtual vector into the first space voltage vector distribution map, divide the projected virtual vector into large virtual vectors, medium virtual vectors and small virtual vectors. In the small sector, synthesize small voltage vectors through two small virtual vectors. In the medium sector, synthesize medium voltage vectors through two medium virtual vectors and one small virtual vector. In the large sector, synthesize large voltage vectors through two large virtual vectors and one medium virtual vector. Use the small voltage vector, the medium voltage vector and the large voltage vector as the reference voltage vector; S3: Sample the target motor to obtain motor operation parameters, obtain a continuous model through the motor operation parameters, discretize the continuous model to obtain a voltage expected value, and determine a target reference voltage vector through the voltage expected value and the reference voltage vector; S4: Construct a cost function, obtain the state matrix of the target motor through the discretized continuous model, and construct a quadratic programming equation through the state matrix and the cost function; S5: Determine the initial parameters of the quadratic programming equation, extract the initial input from the quadratic programming equation, and use the initial parameters and the initial input and the quasi-Newton method to iteratively solve the quadratic programming equation to obtain the vector action time; S6: Control the target motor through the vector action time and the target reference voltage vector.

2. The method for controlling a dual three-phase motor based on a virtual vector according to claim 1, wherein In step S1, the target motor is a dual three-phase motor, and the target motor has six bridge arms, and each of the bridge arms has three level output states.

3. The virtual vector-based dual three-phase motor control method according to claim 1, characterized in that Step S3 specifically includes: S31: Sampling the target motor to obtain motor operation parameters, where the motor operation parameters include motor phase current, motor phase voltage, and electrical angle; S32: Performing coordinate transformation on the motor phase current and the motor phase voltage to obtain plane-axis current and plane-axis voltage, constructing an initial operation matrix of the target motor, and obtaining a continuous model of the target motor through the initial operation matrix, the plane-axis current, and the plane-axis voltage; S33: Discretizing the continuous model to obtain a discretized prediction model, obtaining the voltage expected value of the target motor through the discretized prediction model, calculating the target position of the voltage expected value in the first space voltage vector distribution diagram, and selecting a target reference voltage vector through the reference voltage vector and the target position.

4. The method for controlling a dual three-phase motor based on a virtual vector according to claim 1, characterized in that Step S4 specifically includes: S41: Construct a cost function, extract the state matrix of the target motor from the discretized prediction model, and the cost function in the k-th operating cycle is expressed as: Among them, is the actual value of the dq-axis current in the (k + 1)-th operating cycle, is the theoretical value of the dq-axis current in the (k + 1)-th operating cycle, represents taking the Euclidean norm; S42: Rewriting the cost function through the state matrix, and constructing the quadratic programming equation through the rewritten cost function.

5. The control method of the dual three-phase motor based on virtual vectors according to claim 1, wherein Step S5 specifically includes: S51: Setting an initial solution, a similarity inverse matrix, constraint conditions, and Lagrange multipliers through the target reference voltage vector, and using the initial solution, the similarity inverse matrix, the constraint conditions, and the Lagrange multipliers as the initial parameters, extracting an initial input matrix and an initial input vector from the quadratic programming equation, and using the initial input matrix and the initial input vector as the initial input; S52: Calculating a gradient through the Lagrange multiplier, the initial input, and the initial parameters, calculating a search direction through the similarity inverse matrix and the gradient, and calculating a step size through the search direction; S53: Iterating the initial solution through the step size under the constraint of the constraint conditions, and iterating the Lagrange multiplier, the gradient, and the similarity inverse matrix until the iteration end condition is reached, and obtaining the vector action time through the iterated initial solution.

6. A dual three-phase motor control system based on virtual vectors, which is used to execute the dual three-phase motor control method based on virtual vectors according to any one of claims 1 to 5, characterized in that, Including: Space voltage vector module: Used to determine the target motor, and determine the space voltage vector of the target motor through the level output state of the target motor; Reference voltage vector module: Used to obtain a first space voltage vector distribution diagram and a second space voltage vector distribution diagram through the space voltage vector, performing discrete point fitting in the first space voltage vector distribution diagram and the second space voltage vector distribution diagram, sequentially obtaining a first voltage vector loop system and a second voltage vector loop system, obtaining a virtual vector through the first voltage vector loop system and the second voltage vector loop system, and synthesizing a reference voltage vector through the virtual vector on the first space voltage vector distribution diagram; Target reference voltage vector module: Used to sample the target motor to obtain motor operation parameters, obtain a continuous model through the motor operation parameters, discretize the continuous model to obtain a voltage expected value, and determine a target reference voltage vector through the voltage expected value and the reference voltage vector; Loss function module: used to construct a cost function, obtain the state matrix of the target motor through the discretized continuous model, and construct a quadratic programming equation through the state matrix and the cost function; Vector action time module: used to determine the initial parameters of the quadratic programming equation, extract the initial input from the quadratic programming equation, and perform iterative solution of the quadratic programming equation using the quasi-Newton method through the initial parameters and the initial input to obtain the vector action time; Motor control module: used to control the target motor through the vector action time and the target reference voltage vector.

7. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, When the processor executes the computer program, it implements the steps of the virtual vector-based dual three-phase motor control method according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the virtual vector-based dual three-phase motor control method according to any one of claims 1 to 5.

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