Method for increasing torque of dual three-phase permanent magnet synchronous motor based on multi-harmonic injection

Abstract

The invention discloses a multi-harmonic injection-based dual three-phase permanent magnet synchronous motor torque increasing method, which comprises the following steps of: establishing a mathematical model of a dual three-phase permanent magnet synchronous motor in a six-dimensional natural coordinate system, and decoupling the six-dimensional natural coordinate system into three orthogonal subspaces; in the subspace, the fifth harmonic current and the seventh harmonic current are mapped into sixth harmonic current, and a phase current model containing fundamental waves, fifth harmonic waves and seventh harmonic waves is constructed; taking a phase current peak value as a constraint, carrying out collaborative optimization on fifth and seventh harmonics by adopting a genetic algorithm, and obtaining an optimal harmonic gain coefficient by taking maximization of a fundamental current as a target; generating a harmonic current reference sequence of the future step based on the rotor position, the angular velocity, the sampling period, the rated current and the optimal harmonic gain coefficient; and establishing a discrete prediction model of the dual three-phase permanent magnet synchronous motor, and carrying out multi-step tracking on the harmonic current reference sequence by adopting generalized prediction control. According to the invention, harmonic collaborative optimization can be realized, and the dynamic tracking performance is improved.

Description

Technical Field

[0001] This invention relates to a control method for a dual three-phase permanent magnet synchronous motor, specifically to a method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) are widely used in electric vehicles, ship propulsion, and wind power generation due to their high efficiency, fast dynamic response, and low operating noise. As these fields demand higher output torque and operational stability, increasing output torque under rated current limitations has become a research hotspot. Dual three-phase PMSMs, with their phase redundancy, offer advantages such as higher power / torque density, stronger fault tolerance, and lower stress on power devices. While existing multi-harmonic injection technologies have achieved basic torque enhancement, they have shortcomings in harmonic co-optimization and dynamic tracking performance.

[0003] (1) Existing multi-harmonic injection technology lacks systematic optimization of the amplitude combination of each harmonic and fails to make full use of the synergistic effect between harmonics to maximize torque output.

[0004] (2) When implementing multi-harmonic injection, the existing technology recognizes the complex coupling between the amplitudes of each harmonic current, but its collaborative optimization process mostly relies on empirical trial and error or local search algorithms, making it difficult to find the globally optimal harmonic combination quickly and accurately under the premise of satisfying multiple constraints (such as current peak value and torque pulsation).

[0005] (3) When existing predictive control methods are applied to multi-harmonic current tracking, they usually only perform single-step prediction or the cost function is not well considered. They fail to make full use of the reference information of future multiple steps for global optimization, resulting in limited dynamic tracking accuracy and anti-disturbance capability. Summary of the Invention

[0006] Purpose of the invention: The purpose of this invention is to provide a method for improving the torque of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection, which features harmonic collaborative optimization and better dynamic tracking performance.

[0007] Technical solution: The present invention provides a method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection, comprising:

[0008] (1) Establish the dual three-phase permanent magnet synchronous motor in a six-dimensional natural coordinate system The mathematical model below, through the vector space decomposition method, transforms the six-dimensional natural coordinate system Decoupling , and Three orthogonal subspaces;

[0009] (2) In In the subspace, the fifth and seventh harmonic currents are mapped to the sixth harmonic current, and a phase current model containing the fundamental, fifth and seventh harmonics is constructed.

[0010] (3) Using the peak phase current as a constraint, the genetic algorithm is used to optimize the fifth and seventh harmonics in a coordinated manner, with the goal of maximizing the fundamental current, to obtain the optimal harmonic gain coefficient;

[0011] (4) Based on rotor position, angular velocity, sampling period, rated current and optimal harmonic gain coefficient, generate future The harmonic current reference sequence of the step;

[0012] (5) Establish a discrete prediction model for a dual three-phase permanent magnet synchronous motor, use generalized predictive control to track the harmonic current reference sequence in multiple steps, and output the calculated control quantity to the space vector pulse width modulation module to generate the switching signal required to drive the inverter.

[0013] Furthermore, in step (1), the six-dimensional natural coordinate system Transformation matrix using 6×6 Decomposed into three orthogonal subspaces:

[0014]

[0015]

[0016] in, These are the phase voltages, phase currents, or stator flux linkages for each phase. .

[0017] Furthermore, in step (2), the fundamental frequency is mapped to Subspace; fifth and seventh harmonics mapped to The mapping relationship of subspaces is achieved through a specific mapping matrix, ensuring the accurate mapping of harmonic currents in a specified subspace.

[0018] Furthermore, The mapping formula in the subspace is:

[0019]

[0020] in, for Each group in the coordinate system shaft and The sixth harmonic on the axis, by It is formed by the conversion of the fifth and seventh current harmonics in the subspace; A specific mapping matrix from the fifth and seventh harmonics to the sixth harmonic; The rotor position angle;

[0021] Construct a phase current model that includes the fundamental frequency, fifth harmonic, and seventh harmonic:

[0022]

[0023] in, , and This refers to the harmonic gain coefficient; It is the phase angle of the fundamental wave; and These are the phase offset angles of the fifth and seventh current harmonics, respectively.

[0024] Furthermore, in step (3), a genetic algorithm is used to adjust the harmonic gain coefficient. , and Collaborative optimization is performed; using the phase current peak constraint value and harmonic order as fixed input parameters, the general parameters of the genetic algorithm are configured, and the optimal combination of harmonic gain coefficients is output with the goal of "phase current peak value ≤ constraint value and fundamental current amplitude maximized".

[0025] Furthermore, in step (4), the future is generated. The harmonic current reference sequence for the step is given by the following formula:

[0026]

[0027] in, Indicates the current time; and They represent the future number of... Each sampling time at coordinate system shaft and Reference value for harmonic current of the shaft; and They represent the future number of... Each sampling time at On the subspace shaft and Reference value for harmonic current of the shaft; This is the effective value of the rated current; The rotor position angle; , To predict the step size; The sampling period; Electric angular velocity; and The harmonic gain coefficient is obtained through optimization using a genetic algorithm.

[0028] Furthermore, in step (5), the method for achieving harmonic tracking using generalized predictive control is as follows:

[0029] The discrete prediction model for the dual three-phase permanent magnet synchronous motor is established as follows:

[0030]

[0031] in, This represents the current state of the motor. for coordinate system in Current components on the shaft; for coordinate system in Current components on the shaft; and They are respectively in On the subspace shaft and Harmonic current components of the shaft; To control the quantity, and They are respectively coordinate system in shaft and Voltage components of the axis; and They are respectively in On the subspace shaft and Voltage components of the axis; and For motors with known parameters The discrete matrix, where For stator winding resistance, For inductance related to the fundamental frequency and the main magnetic field, For inductance related to harmonics and leakage magnetic fields, Magnetic flux generated by permanent magnets; This is a disturbance term.

[0032] Furthermore, to facilitate the implementation of generalized predictive control, the discrete predictive model of the dual three-phase permanent magnet synchronous motor is further extended with incremental variables as follows: disturbance term It is treated as a constant and ignored over several sampling periods:

[0033]

[0034] in, In order to be in The state increment at time step is defined as follows: ; In order to be in The state increment at any given moment; , is the augmented state vector; It is a 4×4 identity matrix; , for in Incremental control input at any given time; , for in The system output at that moment; This is the state transition matrix; The input matrix; For the output matrix, ;

[0035] Based on the aforementioned discrete prediction model, a method for predicting the future is derived. The prediction model output by the step system is expressed as:

[0036]

[0037] in, To predict the future The output of the step; To control the incremental sequence; , And construct a quadratic cost function aimed at minimizing tracking error and control increment. ;

[0038] By solving the quadratic cost function The optimization problem, to obtain the future The optimal solution is obtained by summing the first four elements of the optimal solution. shaft and Axis voltage commands are provided to the space vector pulse width modulation module.

[0039] Furthermore, the quadratic cost function ,in The harmonic current reference sequence generated in step (4); and This is the weight matrix.

[0040] Furthermore, in the future optimal solution of step .

[0041] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0042] (1) This invention uses a genetic algorithm to synchronously and collaboratively optimize the amplitude combination of the fifth and seventh harmonic currents. This method uses the peak value of the phase current as a constraint and aims to maximize the fundamental current for global optimization. It overcomes the limitations of traditional empirical trial and error or local search algorithms, and can fully explore the torque contribution of each harmonic, thereby significantly improving the torque density of the motor within the safe operating range.

[0043] (2) Within the optimization framework of the genetic algorithm, the cost function and constraints of this invention implicitly filter harmonic combinations. While pursuing the maximum fundamental current, this optimization process can automatically avoid harmonic combinations that will cause severe torque pulsation, thereby improving the average torque and suppressing torque fluctuations at the source, achieving stable torque output.

[0044] (3) This invention employs generalized predictive control, which constructs a discrete model of the motor and predicts the future. The harmonic current reference sequence is used for real-time rolling optimization with a quadratic cost function that comprehensively considers tracking error and control increment, which realizes fast and accurate tracking of high-frequency harmonic current and ensures the dynamic response effect and control robustness of the torque enhancement strategy. Attached Figure Description

[0045] Figure 1 This is a flowchart of a method for improving the torque of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection, provided by an embodiment of the present invention. Detailed Implementation

[0046] The invention will now be further described with reference to the accompanying drawings.

[0047] like Figure 1 As shown, this embodiment of the invention provides a method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection, comprising the following steps:

[0048] (1) Establish the dual three-phase permanent magnet synchronous motor in a six-dimensional natural coordinate system The mathematical model below, through the vector space decomposition method, decouples the six-dimensional natural coordinate system into three independent two-dimensional subspaces: subspace subspace and Subspaces. These three subspaces are mathematically orthogonal and each corresponds to a different physical meaning:

[0049] Subspace: compared to the traditional three-phase motor The coordinate system is equivalent to that used to describe the fundamental current component that generates the basic electromagnetic torque and magnetic field.

[0050] Subspace: usually corresponds to a specific harmonic magnetic field, and in this invention, it is used to map and control specific harmonic currents (such as the 5th and 7th harmonics).

[0051] Subspace: Usually associated with zero-sequence components, its current components are zero when the windings are star connected and there is no neutral line.

[0052] Six-dimensional natural coordinate system Transformation matrix using 6×6 Decomposed into three orthogonal subspaces:

[0053]

[0054]

[0055] in, These are the phase voltages, phase currents, or stator flux linkages for each phase. .

[0056] (2) In In the subspace, the fifth and seventh harmonic currents are mapped to the sixth harmonic current, and a phase current model containing the fundamental, fifth and seventh harmonics is constructed.

[0057] The fundamental frequency is mapped to Subspace; fifth and seventh harmonics mapped to The mapping relationship of subspaces is achieved through a specific mapping matrix, ensuring the accurate mapping of harmonic currents in a specified subspace.

[0058] The mapping formula in the subspace is:

[0059]

[0060] in, for Each group in the coordinate system shaft and The sixth harmonic on the axis, by It is formed by the conversion of the fifth and seventh current harmonics in the subspace; A specific mapping matrix from the fifth and seventh harmonics to the sixth harmonic; This refers to the rotor position angle. For example, assuming a six-dimensional natural coordinate system. middle The fifth and seventh harmonic currents in the phase current are expressed as follows: and :

[0061]

[0062]

[0063] in, and These are the amplitudes of the fifth and seventh harmonic currents, respectively. and These are the initial phase angles of the fifth and seventh harmonic currents, respectively. This is the rotor position angle.

[0064] By performing Clark and Park transformations on the currents in each single-phase and three-phase ABC and XYZ, they are mapped to a specified... The sixth harmonic current in the coordinate system is:

[0065]

[0066] in, and Representative at In the coordinate system, corresponding shaft and The sixth harmonic current on the axis.

[0067] The phase current model, which includes the fundamental frequency, fifth harmonic, and seventh harmonic, is constructed as follows:

[0068]

[0069] in, , and For harmonic gain coefficients, It is the phase angle (electric angle) of the fundamental wave. and These are the phase offset angles of the fifth and seventh current harmonics, respectively.

[0070] (3) Using the peak phase current as a constraint, the fifth and seventh harmonics are optimized in a coordinated manner using a genetic algorithm to maximize the fundamental current and obtain the optimal harmonic gain coefficient.

[0071] Specifically, this step uses a genetic algorithm to adjust the harmonic gain coefficients. , and Collaborative optimization is performed. The optimization process uses phase current peak constraint values ​​and harmonic orders (5th and 7th) as fixed input parameters. Those skilled in the art can configure general parameters of the genetic algorithm, such as population size, maximum number of iterations, and crossover ratio, according to the complexity of the problem and real-time requirements.

[0072] The core of the genetic algorithm in this invention lies in its set optimization objective, namely: to find a set of harmonic gain coefficients under the hard constraint that "the instantaneous value of the phase current ≤ the peak value". , and This maximizes the fundamental current component. The algorithm outputs the optimal combination of harmonic gain coefficients that satisfies the above conditions.

[0073] As an example, the following parameter settings can be used for iterative search in the simulation: population size of 100, maximum number of iterations of 200, and crossover ratio of 0.8. An optimal set of harmonic gain coefficients was found, and the results are as follows: , and .

[0074] (4) Based on rotor position, angular velocity, sampling period, rated current and optimal harmonic gain coefficient, generate future The harmonic current reference sequence of the step.

[0075] Generate the future based on collaborative optimization results The harmonic current reference sequence for the step is given by the following formula:

[0076]

[0077] in, Indicates the current time; and They represent the future number of... Each sampling time (i.e.) (moment) at coordinate system shaft and Reference value for harmonic current of the shaft; and They represent the future number of... Each sampling time (i.e.) (moment) at On the subspace shaft and Reference value for harmonic current of the shaft; This is the effective value of the rated current; The rotor position angle; , To predict the step size; The sampling period; Electric angular velocity; and The harmonic gain coefficient is obtained through optimization using a genetic algorithm.

[0078] (5) In order to better track Harmonic references in subspaces, and improvements The dynamic response in the coordinate system is used to establish a discrete prediction model for a dual three-phase permanent magnet synchronous motor. Generalized predictive control is used to track the harmonic current reference sequence in multiple steps, and the calculated control quantity (voltage command) is output to the space vector pulse width modulation module (which is existing) to generate the switching signal required to drive the inverter.

[0079] The method for achieving harmonic tracking using generalized predictive control is as follows: First, a discrete predictive model for a dual three-phase permanent magnet synchronous motor is established:

[0080]

[0081] in, This represents the current state of the motor. for coordinate system in The reference value of the current component on the shaft (straight shaft) is usually set to 0. The purpose is to enable the motor to generate maximum torque per unit current and avoid generating a demagnetizing or magnetizing magnetic field. for coordinate system in The current component on the shaft (cross-axis) has a reference value provided by the outer loop speed controller, which is used to control the motor speed and torque; and They are respectively in On the subspace shaft and The harmonic current components of the shaft, reference values ​​(see step (4) for future) The harmonic current reference sequence of the step is designed to include the 5th and 7th harmonics. By precisely controlling these harmonic currents, the phase current waveform of the motor can be changed from a sine wave to a "flat-top wave". This increases the amplitude of the fundamental current without exceeding the phase current amplitude limit, and ultimately improves the output torque capability of the motor.

[0082] To control the quantity. and They are respectively coordinate system in shaft and The voltage component of the axis is obtained by accumulating the optimal solution of the generalized predictive control as follows; and They are respectively in On the subspace shaft and The voltage component of the axis is obtained by accumulating the optimal solution of the generalized predictive control described below. and For motors with known parameters The discrete matrix, where For stator winding resistance, For inductance related to the fundamental frequency and the main magnetic field, For inductance related to harmonics and leakage magnetic fields, Magnetic flux generated by permanent magnets; This is a disturbance term.

[0083] To facilitate the implementation of generalized predictive control, the discrete predictive model of the dual three-phase permanent magnet synchronous motor is further extended with incremental variables as follows: disturbance term It can be considered a constant over several sampling periods and therefore can be ignored.

[0084]

[0085] in, In order to be in The state increment at time step is defined as follows: ; In order to be in The state increment at any given moment; An augmented state vector is a new state vector formed by vertically concatenating the state increment and the original state variables. ; It is a 4×4 identity matrix; In order to be in The control input increment at any given time, i.e. ; exist The system output at any given time is the state itself. ; The state transition matrix describes the augmented state vector. How to Evolving to time; The input matrix describes the control input increment. How does it affect the augmented state vector? ; For the output matrix, .

[0086] Based on the above discrete prediction model, a method for predicting the future can be derived. The prediction model output by the step system is expressed as:

[0087]

[0088] in, To predict the future The output of the step; To control the incremental sequence; , And construct a quadratic cost function aimed at minimizing tracking error and control increment. .

[0089] Quadratic cost function ,in The harmonic current reference sequence generated in step (4); and This is the weight matrix.

[0090] By solving the quadratic cost function The optimization problem, to obtain the future optimal solution of step :

[0091]

[0092] Based on the obtained optimal solution The optimal solution is obtained by summing the first four elements. shaft and Axis voltage commands are provided to the space vector pulse width modulation module.

Claims

1. A method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection, characterized in that, include: (1) Establish the dual three-phase permanent magnet synchronous motor in a six-dimensional natural coordinate system The mathematical model below, through the vector space decomposition method, transforms the six-dimensional natural coordinate system Decoupling , and Three orthogonal subspaces; (2) In In the subspace, the fifth and seventh harmonic currents are mapped to the sixth harmonic current, and a phase current model containing the fundamental, fifth and seventh harmonics is constructed. (3) Using the peak phase current as a constraint, the genetic algorithm is used to optimize the fifth and seventh harmonics in a coordinated manner, with the goal of maximizing the fundamental current, to obtain the optimal harmonic gain coefficient; (4) Based on rotor position, angular velocity, sampling period, rated current and optimal harmonic gain coefficient, generate future The harmonic current reference sequence of the step; (5) Establish a discrete prediction model for a dual three-phase permanent magnet synchronous motor, use generalized predictive control to track the harmonic current reference sequence in multiple steps, and output the calculated control quantity to the space vector pulse width modulation module to generate the switching signal required to drive the inverter.

2. The method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection according to claim 1, characterized in that, In step (1), the six-dimensional natural coordinate system Transformation matrix using 6×6 Decomposed into three orthogonal subspaces: in, These are the phase voltages, phase currents, or stator flux linkages for each phase. .

3. The method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection according to claim 1, characterized in that, In step (2), the fundamental frequency is mapped to Subspace; fifth and seventh harmonics mapped to The mapping relationship of subspaces is achieved through a specific mapping matrix, ensuring the accurate mapping of harmonic currents in a specified subspace.

4. The method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection according to claim 3, characterized in that, The mapping formula in the subspace is: in, for Each group in the coordinate system shaft and The sixth harmonic on the axis, by It is formed by the conversion of the fifth and seventh current harmonics in the subspace; A specific mapping matrix from the fifth and seventh harmonics to the sixth harmonic; The rotor position angle; Construct a phase current model that includes the fundamental frequency, fifth harmonic, and seventh harmonic: in, , and This refers to the harmonic gain coefficient; It is the phase angle of the fundamental wave; and These are the phase offset angles of the fifth and seventh current harmonics, respectively.

5. The method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection according to claim 4, characterized in that, In step (3), a genetic algorithm is used to adjust the harmonic gain coefficients. , and Collaborative optimization is performed; using the phase current peak constraint value and harmonic order as fixed input parameters, the general parameters of the genetic algorithm are configured, and the optimal combination of harmonic gain coefficients is output with the goal of "phase current peak value ≤ constraint value and fundamental current amplitude maximized".

6. The method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection according to claim 5, characterized in that, In step (4), the future is generated. The harmonic current reference sequence for the step is given by the following formula: in, Indicates the current moment; and They represent the future number of... Each sampling time at coordinate system shaft and Reference value for harmonic current of the shaft; and They represent the future number of... Each sampling time at On the subspace shaft and Reference value for harmonic current of the shaft; This is the effective value of the rated current; The rotor position angle; , To predict the step size; The sampling period; Electric angular velocity; and The harmonic gain coefficient is obtained through optimization using a genetic algorithm.

7. The method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection according to claim 1, characterized in that, In step (5), the method for achieving harmonic tracking using generalized predictive control is as follows: The discrete prediction model for the dual three-phase permanent magnet synchronous motor is established as follows: in, This represents the current state of the motor. for coordinate system in Current components on the shaft; for coordinate system in Current components on the shaft; and They are respectively in On the subspace shaft and Harmonic current components of the shaft; To control the quantity, and They are respectively coordinate system in shaft and Voltage components of the axis; and They are respectively in On the subspace shaft and Voltage components of the axis; and For motors with known parameters The discrete matrix, where For stator winding resistance, For inductance related to the fundamental frequency and the main magnetic field, For inductance related to harmonics and leakage magnetic fields, Magnetic flux generated by permanent magnets; This is a disturbance term.

8. The method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection according to claim 7, characterized in that, To facilitate the implementation of generalized predictive control, the discrete predictive model of the dual three-phase permanent magnet synchronous motor is further extended with incremental variables as follows: disturbance term It is treated as a constant and ignored over several sampling periods: in, In order to be in The state increment at time step is defined as follows: ; In order to be in The state increment at any given moment; , is the augmented state vector; It is a 4×4 identity matrix; , for in Incremental control input at any given time; , for in The system output at that moment; This is the state transition matrix; The input matrix; For the output matrix, ; Based on the aforementioned discrete prediction model, a method for predicting the future is derived. The prediction model output by the step system is expressed as: in, To predict the future The output of the step; To control the incremental sequence; , And construct a quadratic cost function aimed at minimizing tracking error and control increment. ; By solving the quadratic cost function The optimization problem, to obtain the future The optimal solution is obtained by summing the first four elements of the optimal solution. shaft and Axis voltage commands are provided to the space vector pulse width modulation module.

9. The method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection according to claim 8, characterized in that, Quadratic cost function ,in The harmonic current reference sequence generated in step (4); and This is the weight matrix.

10. The method for torque enhancement of a dual three-phase permanent magnet synchronous motor based on multi-harmonic injection according to claim 9, characterized in that, future optimal solution of step .

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