Harmonic and torque ripple suppression method for permanent magnet synchronous motor model-free predictive control

Abstract

The present invention discloses a method for suppressing harmonics and torque ripple in model-free predictive control of a permanent magnet synchronous motor. The method comprises the following steps: sampling physical information of the permanent magnet synchronous motor; performing a Clarke transform on the obtained three-phase current, and then performing a Park transform on the sampled rotor position to obtain the actual current along the dq axes; updating an ESO-based hyperlocal model after forward Euler method discrete transformation based on the obtained actual current along the dq axes and the motor winding voltage; calculating a control voltage using a traditional deadbeat current control method based on the calculated disturbance update value; and performing an inverse Park transform on the calculated deadbeat control voltage, followed by traditional SVPWM modulation, to obtain a three-phase PWM waveform, which is input into a driver to control the permanent magnet synchronous motor. The method can significantly reduce current ripple and torque ripple in the model-free predictive control of the permanent magnet synchronous motor, significantly reduce high-frequency harmonics during motor operation, and reduce the computational burden.

Description

Technical Field

[0001] The present invention relates to a model-free predictive control method for a permanent magnet synchronous motor, and in particular to a model-free predictive control method for a permanent magnet synchronous motor for suppressing harmonics and torque pulsation. Background Art

[0002] The existing resonator-based model-free predictive control permanent magnet synchronous control scheme requires manual adjustment of gain and frequency parameters, making it difficult to adapt to dynamic motor operating conditions (such as speed changes and load fluctuations). In addition, parameter coupling issues are prominent when multiple resonators are connected in parallel. The specific problems are as follows:

[0003] 1. Insufficient high-frequency harmonic suppression capability. Due to bandwidth limitations, traditional extended state observers (ESOs) are unable to effectively suppress high-frequency harmonics, resulting in significant increases in total harmonic distortion (THD) and torque ripple when the motor runs at high speeds.

[0004] Second, parameter tuning is complex and lacks adaptability. Existing resonators require manual adjustment of gain and frequency parameters, making it difficult to adapt to dynamic motor operating conditions (such as speed changes and load fluctuations). Furthermore, parameter coupling issues are prominent when multiple resonators are connected in parallel.

[0005] 3. High computational complexity. Traditional complex resonator structures require complex operations, and the amount of computation increases dramatically when multiple resonators are connected in parallel, making it difficult to implement in a real-time control system. Summary of the Invention

[0006] The object of the present invention is to provide a method for suppressing harmonics and torque pulsation in model-free predictive control of a permanent magnet synchronous motor, which at least to a certain extent solves one of the technical problems in the related art.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0008] A method for suppressing harmonics and torque ripple in model-free predictive control of a permanent magnet synchronous motor includes the following steps:

[0009] 1. Sample the physical information of the permanent magnet synchronous motor, including three-phase current, rotor position and speed;

[0010] 2. Perform Clarke transform on the three-phase current obtained in step 1, and then perform Park transform on the rotor position sampled in step 1 to obtain the actual current in the dq axis;

[0011] 3. Update the ESO-based hyperlocal model after the forward Euler method discrete transformation based on the actual dq-axis currents and motor winding voltages obtained in step 2. In the hyperlocal model, the feedback can be expressed as the sum of the traditional current error term and the oscillator model term with real parameters.

[0012] 4. Using the disturbance update value calculated in step 3, calculate the control voltage using the traditional deadbeat current control method.

[0013] 5. Perform inverse Park transformation on the deadbeat control voltage calculated in step 4 and then perform traditional SVPWM modulation to obtain a three-phase PWM waveform, which is input into the driver to control the permanent magnet synchronous motor.

[0014] Furthermore, the process of obtaining the oscillator model with real number parameters in step 3 is as follows:

[0015] First, the conjugate transfer function of the traditional oscillator model with complex parameters is calculated;

[0016] Then, the obtained conjugate transfer function is added to the traditional oscillator model with complex parameters to obtain an oscillator model with real parameters.

[0017] Then, a pre-distortion correction bilinear transformation is performed on the disturbance frequency to obtain an oscillator model with real number parameters in the discrete domain.

[0018] Finally, a plurality of oscillator models with real number parameters for different disturbance frequencies are summed to obtain an oscillator model with real number parameters for a plurality of disturbance frequencies.

[0019] Furthermore, in the process of acquiring the oscillator model with real number parameters, the number of the multiple different disturbance frequencies is a natural number greater than or equal to 1, and the disturbance frequencies are arbitrarily selected.

[0020] Furthermore, the disturbance frequency is determined using the acquired motor speed.

[0021] Furthermore, the parameters of the oscillator model with real number parameters are adjusted online in real time by using an online gain adjustment method. The online gain adjustment method includes:

[0022] Calculate the complex gain of the transfer function denominator of the traditional hyperlocal model-based observer under a given disturbance;

[0023] The gain phase of the oscillator model with real number parameters is taken as the phase of the above complex gain, and the gain assignment value of the oscillator model with real number parameters is taken as the product of the square of the traditional observer bandwidth and a given constant; the above phase and gain calculation method uniquely determines the gain of the oscillator model with real number parameters.

[0024] Furthermore, in step 3, the ESO-based hyperlocal model after the forward Euler method discrete transformation is updated based on formula (1):

[0025] (1)

[0026] in, is the proposed oscillator model with real parameters; is the frequency of the disturbance;

[0027] Among them, ESO is the extended state observer;

[0028] in,( k ) represents the value of the current control cycle, ( k +1) represents the updated value;

[0029] in, is the predicted current value of the permanent magnet synchronous motor dq axis, is the dq axis motor winding voltage, is the control gain, is the disturbance prediction value, is the actual current obtained according to step 1 and predicted current The calculated current estimation error is, β 1 ，β 2 is the ESO gain, is the control period.

[0030] The beneficial effects of the present invention are:

[0031] 1. The present invention can significantly reduce the current ripple and torque pulsation of the permanent magnet synchronous motor model-free predictive control (MFPCC).

[0032] 2. The present invention can significantly reduce high-frequency harmonics during motor operation.

[0033] 3. The present invention introduces a single or multiple parallel oscillator models with real parameters in the model-free predictive control process, simplifies the traditional oscillator model with complex parameters into an oscillator model with real parameters, and reduces the computational burden.

[0034] 4. The present invention uses an online gain tuning method to perform real-time online tuning of the parameters of an oscillator model with real number parameters (using the time-varying disturbance frequency under different motor speed conditions to automatically tune the oscillator parameters online), avoiding the manual parameter tuning required by traditional solutions (traditional manual tuning methods require offline, manual parameter debugging), thereby improving the deployment efficiency and convenience of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a control block diagram of the present invention;

[0036] Figure 2This is a three-phase current waveform diagram of a permanent magnet synchronous motor in the prior art;

[0037] Figure 3 The three-phase current waveform diagram of the permanent magnet synchronous motor of the present invention;

[0038] Figure 4 A comparison chart of the current harmonic content between the present invention and the traditional method.

[0039] The accompanying drawings are for illustrative purposes only and are not to be construed as limitations on this patent. To better illustrate this embodiment, some components of the accompanying drawings may be omitted, enlarged, or reduced in size, and do not represent the actual dimensions of the product. For those skilled in the art, it is understandable that some well-known structures and their descriptions may be omitted from the accompanying drawings. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0041] like Figure 1 As shown, this embodiment discloses a method for suppressing harmonics and torque ripples in a permanent magnet synchronous motor using model-free predictive control, comprising the following steps:

[0042] 1. Sample the physical information of the permanent magnet synchronous motor, including: three-phase current, rotor position, and speed.

[0043] 2. Perform Park transform and Clarke transform on the three-phase current obtained in step 1 to obtain the actual current under the dq axis .

[0044] 3. Update the ESO-based Ultra-local model after the forward Euler method discrete transformation:

[0045] (1)

[0046] in, is the proposed oscillator model with real parameters; is the frequency of the disturbance;

[0047] Among them, Ultra-local model is the traditional ultra-local model, and ESO is the extended state observer;

[0048] in,( k ) represents the value of the current control cycle, ( k +1) represents the updated value;

[0049] in, is the predicted current value of the permanent magnet synchronous motor dq axis, is the dq axis motor winding voltage, is the control gain, is the disturbance prediction value, is the actual current obtained according to step 1 and predicted current The calculated current estimation error is, β 1 ，β 2 is the ESO gain, is the control period.

[0050] 4. Update the perturbation value calculated in step 3 Perform deadbeat control voltage calculation

[0051] (2)

[0052] in is the current control instruction.

[0053] 5. The deadbeat control voltage obtained by step 4 is Perform inverse Park transform and then traditional SVPWM modulation to obtain a three-phase PWM waveform, which is input into the driver to control the permanent magnet synchronous motor.

[0054] The oscillator model with real parameters in step 3 The acquisition process is as follows: first, the conjugate transfer function of the traditional oscillator model with complex parameters is calculated; then the obtained conjugate transfer function is added to the traditional oscillator model with complex parameters itself to obtain an oscillator model with real parameters; then, a pre-distortion correction bilinear transformation is performed on it according to the disturbance frequency to obtain an oscillator model with real parameters in the discrete domain; finally, multiple oscillator models with real parameters for different disturbance frequencies are summed to obtain oscillator models with real parameters for multiple disturbance frequencies.

[0055] The specific steps are as follows:

[0056] (1) The traditional oscillator model with complex parameters is as follows

[0057] (3)

[0058] in, is a complex parameter, is the perturbation frequency, is an imaginary unit, is the Laplace transform operator.

[0059] (2) Simplifying the traditional oscillator model (3) with complex parameters to the real domain includes the following steps:

[0060] First, the conjugate transfer function of the complex transfer function in formula (3) is as follows

[0061] (4)

[0062] Then, the oscillator model with real parameters is expressed as the sum of (3) and (4) above as follows:

[0063] (5)

[0064] in, and Represents complex parameters The real and imaginary parts of ; thus all parameters in the proposed oscillator model with real parameters are real.

[0065] (3) Performing a bilinear transformation of the pre-distortion correction on the oscillator model in formula (5) above yields:

[0066] (6)

[0067] in, is the complex variable symbol;

[0068] in, and Transfer two parameters of the function for the discretized oscillator model:

[0069]

[0070] (4) Converting the above discretized model formula (6) into the time domain can obtain the proposed single oscillator model with real parameters .

[0071] (5) Multiple oscillator models with real number parameters at different perturbation frequencies By performing the sum calculation, we can get the proposed oscillator model with real number parameters ;in, Represents the addition operation.

[0072] In step (5), the number of the multiple different disturbance frequencies can be a natural number greater than or equal to 1, and the disturbance frequencies can be selected arbitrarily.

[0073] For example, in this embodiment, the 6nth harmonic is generated under the dq axis when the motor is running, where n represents the harmonic number. The disturbance frequency is determined using the collected motor speed, and the specific calculation formula is: .

[0074] in, is the frequency corresponding to the motor speed, and its calculation formula is ,in is the collected motor speed, is the number of pole pairs of the motor.

[0075] In other embodiments, the disturbance frequency can be selected arbitrarily and is not limited to the above frequency calculation formula.

[0076] This embodiment also proposes to use the gain online tuning method to adjust the oscillator model with real number parameters. Parameters and Parameters can be adjusted online in real time, eliminating the need for offline debugging based on traditional manual adjustment methods.

[0077] The online gain tuning method includes: calculating the complex gain of the denominator of the transfer function of a traditional hyperlocal model observer under a given disturbance; taking the gain phase of the oscillator model with real parameters as the phase of the above complex gain, and taking the gain assignment of the oscillator model with real parameters as the product of the square of the traditional observer bandwidth and a given constant; the above phase and gain calculation method uniquely determines the gain of the oscillator model with real parameters.

[0078] The specific steps include:

[0079] 1) Ultra-local model-free predictive control of classical ESO differential equations:

[0080] (7)

[0081] in, is a differential operator, is the predicted current value of the permanent magnet synchronous motor dq axis, is the dq axis motor winding voltage, is the control gain, is the disturbance prediction value, is the actual current obtained according to step 1 and predicted current The calculated current estimation error is, β 1 ，β 2 It is the gain of ESO;

[0082] Among them, the Ultra-local model is the traditional ultra-local model, and ESO is the extended state observer.

[0083] 2) Perform Laplace transform and find its transfer function, and we can get

[0084] (8)

[0085] For the denominator of the above transfer function at a specific interference frequency, calculate its gain value

[0086] (9)

[0087] 3) For the required gain , and calculate its phase using formula (9) (the phase angle of the oscillator gain is set to the phase of the gain of the denominator of the extended state observer transfer function of the model-free predictive control at a specific disturbance frequency):

[0088] (10)

[0089] in, Refers to the phase angle of a complex number.

[0090] 4) Calculate the required gain Amplitude:

[0091] (11)

[0092] in, δ is a positive real number much smaller than unity, and can be in the range of 0.001-0.1. For example, in this embodiment, δ Take 0.01. is the bandwidth of the classical ESO described in (8).

[0093] 5) Then, the above steps 3)-4) obtained Decompose into real and non-real parts:

[0094] (12)

[0095] The above formula (12) calculates and This is an oscillator model with real parameters Parameters.

[0096] This invention introduces single or multiple parallel oscillator models with real parameters into the model-free predictive control process, simplifying the traditional oscillator with complex parameters to an oscillator model with real parameters, reducing the computational burden. Furthermore, this invention uses an online gain tuning method to perform real-time online parameter tuning on the oscillator model with real parameters, eliminating the manual parameter tuning required by traditional solutions and improving the deployment efficiency and convenience of this invention.

[0097] The permanent magnet synchronous motor control platform used in the permanent magnet synchronous motor model-free predictive control harmonic and torque ripple suppression method proposed in this embodiment includes a permanent magnet synchronous motor controller, a permanent magnet synchronous motor, and other accompanying test servo systems.

[0098] The present invention can significantly reduce the current ripple and torque pulsation of the permanent magnet synchronous motor MFPCC control.

[0099] like Figure 2 As shown in the figure, the three-phase current waveform / torque ripple waveform diagram of the permanent magnet synchronous motor controlled at 1000 rpm and 0.127 Nm load is shown using the oscillator principle but not the real gain oscillator, and the method of manually adjusting the oscillator parameters. Channels 1-3 are the three-phase currents, and channel 4 is the torque fluctuation.

[0100] Figure 2 Middle: The vertical scale of the three-phase current waveform is 200mA / div, the vertical scale of the torque ripple waveform is 5ms / div, and the horizontal scale of both is 5ms / div. Figure 2 The effective value of the three-phase current is 233.6mA (RMS), and the torque ripple value is 1.74%.

[0101] like Figure 3 As shown, it is a schematic diagram of the three-phase current waveform / torque ripple waveform of the permanent magnet synchronous motor controlled by the method proposed in the present invention, where channels 1-3 are the three-phase currents and channel 4 is the torque ripple.

[0102] Figure 3 Middle: The vertical scale of the three-phase current waveform is 200mA / div, the vertical scale of the torque ripple waveform is 5ms / div, and the horizontal scale of both is 5ms / div. Figure 3 The effective value of the three-phase current is 232.6mA (RMS), and the torque ripple value is 0.63%.

[0103] pass Figure 3 and Figure 2 By comparison, it can be seen that the method proposed in the present invention significantly reduces current ripple and torque fluctuation.

[0104] The present invention can also significantly reduce the 6k±1 harmonics during the operation of the motor, where k=1, 2, 3... The current harmonic content of the method proposed by the present invention under different working conditions of the motor is compared with that of the traditional method. Figure 4 shown.

[0105] Figure 4Among them, method 1 is a traditional model-free predictive control method that does not use an oscillator, method 2 uses the oscillator principle but does not use a real-gain oscillator and uses manual tuning of the oscillator parameters, and method 3 is the method of the present invention. Compared with methods 1 and 2, the method of the present invention significantly reduces the harmonic components of each current.

[0106] The above embodiments are only used to illustrate rather than limit the technical solutions of the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the present invention can still be modified or replaced by equivalents. Any modification or partial replacement that does not depart from the spirit and scope of the present invention should be included in the scope of the claims of the present invention.

[0107] If words such as "first" and "second" are used in this document to limit components, those skilled in the art should know that the use of "first" and "second" is only for the convenience of describing the present invention and simplifying the description. Unless otherwise stated, the above words have no special meaning.

[0108] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0109] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

Claims

1. A method for suppressing harmonics and torque ripples in model-free predictive control of permanent magnet synchronous motors, characterized in that The following steps are involved: (1) Sampling the physical information of the permanent magnet synchronous motor, including three-phase current, rotor position and speed; (2) Perform Clarke transformation on the three-phase current obtained in step 1, and then perform Park transformation on the rotor position sampled in step 1 to obtain the actual current under the dq axis; (3) Based on the actual dq axis currents obtained in step 2 and the motor winding voltage, the ESO-based hyperlocal model after the forward Euler method discrete transformation is updated; in the hyperlocal model, its feedback quantity is expressed as the sum of the traditional current error term and the oscillator model term with real number parameters; wherein the traditional current error term is the current estimation error calculated based on the actual current obtained in step 1 and the predicted current, and the predicted current is calculated based on the ESO-based hyperlocal model; wherein the feedback quantity is the feedback quantity of the disturbance prediction value; (4) Calculate the control voltage using the traditional deadbeat current control method using the disturbance update value calculated in step 3; (5) Performing an inverse Park transform on the deadbeat control voltage obtained after calculation in step 4 and then performing conventional SVPWM modulation to obtain a three-phase PWM waveform, which is input into the driver to control the permanent magnet synchronous motor; The process of obtaining the oscillator model with real number parameters in step 3 is as follows: First, the conjugate transfer function of the traditional oscillator model with complex parameters is calculated; Then, the obtained conjugate transfer function is added to the traditional oscillator model with complex parameters to obtain an oscillator model with real parameters. Then, a pre-distortion correction bilinear transformation is performed on the disturbance frequency to obtain an oscillator model with real number parameters in the discrete domain. Finally, a plurality of oscillator models with real number parameters for different disturbance frequencies are summed to obtain an oscillator model with real number parameters for a plurality of disturbance frequencies.

2. The method for suppressing harmonics and torque ripple in model-free predictive control of a permanent magnet synchronous motor according to claim 1, characterized in that: In the process of obtaining the oscillator model with real number parameters, the number of the multiple different disturbance frequencies is a natural number greater than or equal to 1, and the disturbance frequencies are arbitrarily selected.

3. The method for suppressing harmonics and torque ripple in model-free predictive control of a permanent magnet synchronous motor according to claim 2, characterized in that: The disturbance frequency is determined using the acquired motor speed.

4. The method for suppressing harmonics and torque ripple in model-free predictive control of a permanent magnet synchronous motor according to claim 1, characterized in that: The parameters of the oscillator model with real number parameters are tuned online in real time using the online gain tuning method. The online gain tuning method includes: Calculate the complex gain of the transfer function denominator of the traditional hyperlocal model-based observer under a given disturbance; The gain phase of the oscillator model with real number parameters is taken as the phase of the above complex gain, and the gain assignment value of the oscillator model with real number parameters is taken as the product of the square of the traditional observer bandwidth and a given constant; the above phase and gain calculation method uniquely determines the gain of the oscillator model with real number parameters.

5. The method for suppressing harmonics and torque ripple in model-free predictive control of a permanent magnet synchronous motor according to any one of claims 1 to 4, characterized in that: In step 3, the ESO-based hyperlocal model after the forward Euler method discrete transformation is updated based on formula (1): （1） in, is an oscillator model with real parameters; is the frequency of the disturbance; Among them, ESO is the extended state observer; in,( k ) represents the value of the current control cycle, ( k +1) represents the updated value; in, is the predicted current value of the permanent magnet synchronous motor dq axis, is the dq axis motor winding voltage, is the control gain, is the disturbance prediction value, is the actual current obtained according to step 1 of claim 1 and predicted current The calculated current estimation error is, β 1 ，β 2 is the ESO gain, is the control period.

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