A method and system for permanent magnet synchronous motor non-inductive control based on multi-continuous sampling delay and application thereof

Abstract

The application discloses a kind of permanent magnet synchronous motor non-inductive control method, system and application based on multiple continuous sampling delay, including monitoring motor, obtaining the three-phase current and voltage of the motor, and the three-phase current and voltage of the motor obtained are respectively carried out coordinate system transformation, obtain the three-phase current and voltage under αβ coordinate system, the control method will the three-phase current and voltage under αβ coordinate system as the input of flux linkage observer, output rotor flux linkage under αβ coordinate system, and through stator current cycle estimation module, the stator current under αβ coordinate system obtained is carried out cycle estimation, obtain the adaptive time constant τ based on stator current cycle, while using multiple continuous sampling delay module, the stator current cycle and rotor flux linkage obtained are calculated and handled, obtain the rotation angular velocity of motor rotor, so that the speed of motor can be obtained, feedback to PI regulator, constitute the speed closed loop of vector control.

Description

Technical Field

[0001] This invention relates to the field of motor control technology, and in particular to a sensorless control method, system and application of a permanent magnet synchronous motor based on multiple continuous sampling delay. Background Technology

[0002] In recent years, high-speed permanent magnet synchronous motors have been increasingly widely used in modern industry and daily life due to their numerous advantages. However, installing mechanical sensors increases the system's size, weight, and cost. Furthermore, sensors are susceptible to environmental influences such as temperature, humidity, and vibration, which reduce system reliability. Therefore, sensorless control technology is gradually becoming a research hotspot.

[0003] Currently, commonly used sensorless control algorithms mainly include: back EMF method, state observer method, and model reference adaptive method. Each of these methods has its own advantages and disadvantages and is suitable for different scenarios. Model-based control schemes have attracted much attention due to their simple structure and high flexibility. Classical methods mainly include: model-based adaptive full-order observer, model reference adaptive system, sliding mode observer, and extended Kalman filter. These methods, to varying degrees, suffer from problems such as weak adaptability to changes in motor parameters, high-frequency chattering, phase lag, and high computational cost.

[0004] Among various sensorless motor control schemes (hereinafter referred to as sensorless motor control), the sensorless motor control scheme based on synchronization technology stands out. Schemes based on phase-locked loops (PLLs) and frequency-locked loops (LLLs) show significant effects, but their ability to suppress interference is a problem. To address this issue, several solutions have been proposed, such as combining PLLs with adaptive filters based on adaptive linear neural networks, and using SOGI-FLL speed estimation to remove the influence of DC bias. However, these schemes, by adding modules that affect the system's dynamic process, such as filters, to the speed estimation system, lead to longer dynamic response times, estimation degradation, and low stability margins during dynamic processes. This makes it difficult to accurately estimate the motor's speed and position under sensorless conditions, making them unsuitable for practical applications. Summary of the Invention

[0005] The purpose of this invention is to provide a sensorless motor control system and method that enables the motor to operate stably without sensors and to accurately estimate the motor speed.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The first aspect of this invention provides a sensorless control method for a permanent magnet synchronous motor based on multiple continuous sampling delays, the control method comprising:

[0008] Step S1: Monitor the motor to obtain the three-phase current and voltage of the motor;

[0009] Step S2: Perform coordinate system transformation on the three-phase current and voltage of the motor obtained in step S1 to obtain the three-phase current and voltage based on the αβ coordinate system.

[0010] Step S3: Use the three-phase current and voltage obtained in step S2 based on the αβ coordinate system as the input of the flux linkage observer, and output the rotor flux linkage based on the αβ coordinate system.

[0011] Step S4: Obtain the stator current based on the αβ coordinate system. Through the stator current period estimation module, estimate the period of the obtained stator current based on the αβ coordinate system to obtain the adaptive time constant τ based on the electronic current period.

[0012] Step S5: Based on the stator current period obtained in step S4 and the rotor flux obtained in step S3, the rotational angular velocity of the motor rotor is obtained by calculation through a multi-continuous sampling delay module.

[0013] Step S6: Convert the rotational angular velocity of the motor rotor obtained in step S5 into the motor speed and feed it back to the PI controller to form a speed closed loop for vector control.

[0014] Preferably, in step S2, performing coordinate system transformation on the obtained three-phase currents and voltages includes:

[0015] Voltage and current in the αβ coordinate system can be obtained by one or more combinations of Park transform and Clarke transform.

[0016] Preferably, step S3 specifically comprises:

[0017] Based on the dynamic model of the permanent magnet synchronous motor in the αβ coordinate system, a nonlinear flux linkage observer model is established.

[0018] In the αβ coordinate system, the dynamic model of the permanent magnet synchronous motor is shown in the following equation:

[0019]

[0020]

[0021] Among them, i αβ =[i α i β ] T It is the stator current, v αβ =[v α v β] T It is the motor terminal voltage, R s L is the stator resistance, and ψ is the stator inductance. m It is a permanent magnet flux linkage, T e It is electromagnetic torque, and P is the number of pole pairs.

[0022] First, define a new state variable x:

[0023]

[0024] Let the variable y be:

[0025] y = -R s i αβ +v αβ (4)

[0026] Combining equations (1), (3), and (4), we get:

[0027]

[0028] Define a vector function η: As shown in the following formula:

[0029] η(x)=x-Li αβ (6)

[0030] Combining equations (3) and (6), we obtain the Euclidean norm of the vector function η(x) as:

[0031]

[0032] Therefore, the model of the nonlinear flux observer is as follows:

[0033]

[0034] in, γ is the observer's state variable, and γ > 0 is the observer's gain. yes With ψ m The square of the distance between them.

[0035] Next, the angle θ output by the magnetic flux observer is reconstructed, and the following is derived using equation (3):

[0036]

[0037] Then we define:

[0038]

[0039] The final result is:

[0040]

[0041] in, This is an estimate of the angle θ output by the flux linkage observer.

[0042] Preferably, the rotor flux linkage output by the nonlinear flux linkage observer model in the αβ coordinate system is:

[0043]

[0044] Among them, |ψ rα | represents the amplitude of the rotor flux linkage component on the α-axis, |ψ rβ | represents the magnitude of the rotor flux linkage component on the β-axis, and ω represents the angular velocity of the motor rotor. The phase of the rotor flux linkage component on the α-axis, represents the phase of the rotor flux component on the β-axis.

[0045] Preferably, the specific steps of step S5 are as follows:

[0046] The rotor flux obtained in step S3 is used as the input to the multi-sampling delay module. Variables α and β are replaced with the symbol K. At this time, the rotor flux is:

[0047]

[0048] Preferably, equation (13) is rewritten as follows:

[0049]

[0050] Where, ψ f Represents the fundamental component, λ DC ψ is the DC bias component. h These are harmonic components.

[0051] At this point, the rotor flux linkage is obtained after four delay processes at different time intervals:

[0052]

[0053] In equation (15), τ is the adaptive time constant, obtained from the stator current period estimation module, where:

[0054]

[0055] Among them, T sk The period of the stator current along the α-axis or β-axis.

[0056] Preferably, the initial sampling signal ψ rk0 (t) and the sampled signal ψ after a delay of 2τ rk2Expanding (t) and adding them together, we get:

[0057]

[0058] The sampled signal ψ after a delay of 2τ rk2 (t) and the sampled signal ψ after a delay of 4τ rk4 Expanding (t) and adding them together, we get:

[0059]

[0060] Define the parameter γ = cos(ωτ),

[0061] Simplifying equations (17) and (18) respectively, we can obtain:

[0062]

[0063]

[0064] Subtracting equation (20) from equation (19) yields:

[0065]

[0066] γ satisfies the following formula:

[0067]

[0068] According to equation (19), the rotational angular velocity of the motor rotor can be obtained as follows:

[0069]

[0070] Preferably, the method for converting the rotational angular velocity of the motor rotor obtained in step S5 into the motor speed is as follows:

[0071] According to equation (23), Defined as an estimate of parameter γ, then the parameter... The estimation process is as follows:

[0072]

[0073] The motor speed e is:

[0074]

[0075] In a second aspect, the present invention provides a sensorless control system for a permanent magnet synchronous motor based on multiple consecutive sampling delays, employing the sensorless control method for a permanent magnet synchronous motor based on multiple consecutive sampling delays as described in any one of the first aspects. The control system includes:

[0076] A flux linkage observer module, which is used to construct a rotor flux linkage that includes motor speed information;

[0077] The stator current period module, wherein the electronic current period estimation module is used to estimate the period of the stator current to obtain an adaptive time constant τ based on the stator current period;

[0078] The multi-continuous sampling delay module is used to estimate the frequency of the rotor flux output by the flux observer module, extract the speed information of the permanent magnet synchronous motor and feed it back to the PI regulator to form a speed closed loop for vector control.

[0079] The third aspect of the present invention provides a permanent magnet synchronous motor, which employs the sensorless control system for a permanent magnet synchronous motor based on multiple continuous sampling delay described in the second aspect.

[0080] Beneficial effects:

[0081] This invention obtains rotor flux containing motor speed information by detecting the three-phase current and voltage of the motor and using a flux linkage observer module, providing input for the subsequent speed estimation module. It also uses a stator current period estimation module to adaptively adjust the time constant, providing a parameter basis for wide-range motor speed estimation. Finally, it utilizes a multi-continuous sampling delay module, using the output of the stator current period estimation module as input to the multi-continuous sampling delay module, and extracting the fundamental signal ψ of the rotor flux. rk0 (t) After being delayed four times, the delayed signal ψ is obtained. rk1 (t), ψ rk2 (t), ψ rk3 (t) and ψ rk4 (t), and then through the fundamental signal ψ rk0 (t) and the delayed signal ψ rk1 (t), ψ rk2 (t), ψ rk3 (t), ψ rk4 The speed information of the permanent magnet synchronous motor is obtained by the trigonometric and arithmetic relationships between (t) and the speed loop, and fed back to the speed loop to form a motor control system with the motor vector control. Since the multi-continuous sampling method does not have modules such as filters that may cause dynamic response delay of the system, it has good fast dynamic response capability for motor speed estimation. Compared with the traditional four-continuous sampling method, this method can not only suppress the interference of DC bias and odd harmonics, but also suppress the interference of even harmonics. Attached Figure Description

[0082] Figure 1 This is a flowchart of a sensorless control method for a permanent magnet synchronous motor based on multiple continuous sampling delays, provided in an embodiment of the present invention.

[0083] Figure 2 This is a coordinate system transformation spatial position relationship diagram for a sensorless control method for a permanent magnet synchronous motor based on multiple continuous sampling delay provided in an embodiment of the present invention.

[0084] Figure 3 This is a control block diagram of a multi-continuous sampling delay module for a sensorless control method for a permanent magnet synchronous motor based on multi-continuous sampling delay, provided in an embodiment of the present invention.

[0085] Figure 4 This is a block diagram of a vector control system based on a sensorless control method for a permanent magnet synchronous motor with multiple continuous sampling delays, provided in an embodiment of the present invention.

[0086] Figure 5 This is a PWM control circuit diagram of a sensorless control method for a permanent magnet synchronous motor based on multiple continuous sampling delay provided in an embodiment of the present invention.

[0087] Figure 6 This is an overall system control block diagram of a sensorless control method for a permanent magnet synchronous motor based on multiple continuous sampling delays provided in an embodiment of the present invention.

[0088] Figure 7 The waveform simulation diagram shows the motor speed changing from 800 r / min to 1000 r / min under the condition of speed jump.

[0089] Figure 8 The waveform simulation diagram is shown for the motor speed change condition, with a speed of 1000 r / min-1200 r / min.

[0090] Figure 9 The waveform simulation diagram shows the estimated motor speed (800 r / min) under a DC offset of 0.25 pu.

[0091] Figure 10 The waveform simulation diagram shows the estimated motor speed (1000 r / min) under a DC offset of 0.25 pu.

[0092] Figure 11 The waveform simulation diagram shows the estimated motor speed (800 r / min) under the 2nd, 3rd, 4th and 5th harmonic conditions of 0.125 pu.

[0093] Figure 12 The waveform simulation diagram shows the estimated motor speed (1000 r / min) under the 2nd, 3rd, 4th and 5th harmonic conditions of 0.125 pu. Detailed Implementation

[0094] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described in this application are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0095] like Figure 1 As shown in this embodiment, to enable the motor to operate stably without sensors, this invention provides a sensorless control method that can suppress DC bias and odd / even harmonics while maintaining both dynamic and steady-state performance. When the permanent magnet synchronous motor is under vector control, a multi-continuous sampling delay sensorless control is introduced to estimate the motor speed. This technical solution employs a sensorless motor control structure consisting of three parts: a flux linkage observer module, a stator current period estimation module, and a multi-continuous sampling delay module. By monitoring the motor, the three-phase current and voltage are obtained. After Park and Clarke transformations, voltage and current based on the αβ coordinate system are obtained and used as input to the flux linkage observer. After a series of calculations, the rotor flux linkage based on the αβ coordinate system is output. The rotor flux linkage is then input to the next-level multi-continuous sampling delay module for speed estimation. The stator current period is obtained by the stator current period estimation module (phase-locked loop, frequency-locked loop, etc.). The stator current period is used to perform speed range adaptive control on the multi-continuous sampling delay module, so that the scheme has a large speed estimation range. After obtaining the motor speed using the multi-continuous sampling module, it is combined with the PI regulator to form a closed-loop regulation of the speed, so that the motor can run stably.

[0096] Specifically, the control method is a sensorless control method for a permanent magnet synchronous motor based on multiple continuous sampling delays, including:

[0097] Step S1: Monitor the motor to obtain the three-phase current and voltage of the motor;

[0098] Step S2: Perform coordinate system transformation on the three-phase current and voltage of the motor obtained in step S1 to obtain the three-phase current and voltage based on the two-phase stationary coordinate system, i.e., the αβ coordinate system.

[0099] The obtained three-phase current and voltage are used to obtain voltage and current based on the αβ coordinate system through one or more combinations of Park transformation and Clarke transformation;

[0100] like Figure 2 As shown, the process of transforming the three-phase stationary coordinate system ABC to the two-phase stationary coordinate system αβ is called the Clarke transformation, while the process of transforming the αβ coordinate system to the two-phase rotating coordinate system dq is called the Park transformation.

[0101] Specifically,

[0102] Clarke transform:

[0103] In a two-phase stationary coordinate system, the α-axis coincides with the stator A-phase winding, and the β-axis leads the α-axis counterclockwise by 90° in spatial electrical angles. The transformation matrix is ​​then:

[0104]

[0105] According to equation (1), the physical quantities in the three-phase stationary coordinate system can be transformed into the two-phase stationary coordinate system. The transformation process can be expressed as follows:

[0106]

[0107] In equation (2), f can be represented as voltage, current and magnetic flux.

[0108] Park transform:

[0109] Define a two-phase coordinate system dq rotating synchronously in space, where the d-axis coincides with the rotor magnetic pole axis, the q-axis leads the d-axis counterclockwise by 90° electrical angle, and the angle between the d-axis and the A-phase stator winding is θ. The transformation matrix is ​​then:

[0110]

[0111] According to equation (3), physical quantities in a two-phase stationary coordinate system can be transformed into a two-phase rotating coordinate system. The transformation process can be expressed as follows:

[0112]

[0113] Step S3: Use the three-phase current and voltage obtained in step S2 based on the αβ coordinate system as the input of the flux linkage observer, and output the rotor flux linkage based on the αβ coordinate system.

[0114] To estimate the motor speed, the sensorless control method extracts motor speed information from the rotor flux linkage. To obtain the rotor flux linkage, this invention uses a flux linkage observer to estimate it. The three-phase current and voltage based on the αβ coordinate system are used as inputs to the flux linkage observer. After processing, the final output is the rotor flux linkage based on the αβ coordinate system. The specific steps are as follows:

[0115] Based on the dynamic model of the permanent magnet synchronous motor in the αβ coordinate system, a nonlinear flux linkage observer model is established.

[0116] In the αβ coordinate system, the dynamic model of the permanent magnet synchronous motor is shown in the following equation:

[0117]

[0118]

[0119] Among them, i αβ =[i α i β ] T It is the stator current, v αβ =[v α v β ] T It is the motor terminal voltage, R s L is the stator resistance, and ψ is the stator inductance. m It is a permanent magnet flux linkage, T e It is electromagnetic torque, and P is the number of pole pairs.

[0120] The following establishes a nonlinear flux observer. First, a new state variable x is defined:

[0121]

[0122] Let the variable y be:

[0123] y = -R s i αβ +v αβ (8)

[0124] In equation (8), all variables can be obtained through measurement. Combining equations (5), (7), and (8), we get:

[0125]

[0126] Define a vector function η: As shown in the following formula:

[0127] η(x)=x-Li αβ (10)

[0128] Combining equations (7) and (10), we obtain the Euclidean norm of the vector function η(x) as:

[0129]

[0130] Therefore, the model of the nonlinear flux observer is as follows:

[0131]

[0132] in, γ is the observer's state variable, and γ > 0 is the observer's gain. yes With ψ m The square of the distance between them.

[0133] By observing the state variable x, θ can be reconstructed in the following way. First, it is derived from equation (7):

[0134]

[0135] Then we define:

[0136]

[0137] Finally, the estimated value of the angle θ output by the flux linkage observer is obtained. :

[0138]

[0139] In this embodiment, it is not difficult to notice from equation (15) that when the denominator is close to 0, tan -1 It is also not sensitive. At this point, the flux linkage observer part in this embodiment is completed. Angle closure is performed on the angle θ output by the flux linkage observer. The output rotor flux linkage of the flux linkage observer is used as the input of the multi-continuous sampling module to perform speed estimation, which is finally used for speed closure.

[0140] Step S4: Obtain the stator current based on the αβ coordinate system. Through the stator current period estimation module, estimate the period of the obtained stator current based on the αβ coordinate system to obtain the adaptive time constant τ based on the stator current period. The estimation of the stator current period can be achieved by phase-locked loop, frequency-locked loop, or zero-crossing detection module, etc.

[0141] Step S5: Based on the stator current period obtained in step S4 and the rotor flux obtained in step S3, the rotational angular velocity of the motor rotor is obtained by calculation through a multi-continuous sampling delay module.

[0142] First, after the flux linkage observer outputs the rotor flux linkage, the multi-continuous sampling delay module uses the rotor flux linkage output by the flux linkage observer as its input, which can be expressed mathematically as follows:

[0143]

[0144] Equation (16) is the expression for the rotor flux without DC bias, |ψ rα | represents the amplitude of the rotor flux linkage component on the α-axis, |ψ rβ | represents the magnitude of the rotor flux linkage component on the β-axis, and ω represents the angular velocity of the motor rotor. The phase of the rotor flux linkage component on the α-axis, Let K be the phase of the rotor flux linkage component on the β-axis. We represent the rotor flux linkage using a sine function. For ease of derivation, the symbol K will be used to replace variables α and β. Therefore, equation (16) will be simplified to:

[0145]

[0146] In sensorless control of permanent magnet synchronous motors, DC bias, odd harmonics, and even harmonics are unavoidable. To take all factors into account and make this method complete, we rewrite equation (17) as follows:

[0147]

[0148] In equation (18) ψ f The representative fundamental component, λ DC ψ is the DC bias component. h These are harmonic components.

[0149] After passing through the multi-continuous sampling delay module, the rotor flux linkage is obtained after four delay processes with different timing segments:

[0150]

[0151] In equation (19), τ is the adaptive time constant, obtained from the stator current period estimation module, where:

[0152]

[0153] Among them, T sk The period of the stator current along the α-axis or β-axis.

[0154] The initial sampled signal ψ is expanded and added together. rk0 (t) and the sampled signal ψ after a delay of 2τ rk2 (t), we can obtain:

[0155]

[0156] We can define the parameter γ = cos(ωτ) to simplify the formula, and we can obtain:

[0157]

[0158] Similarly, for the sampled signal ψ after a delay of 2τ... rk2 (t) and the sampled signal ψ after a delay of 4τ rk4 Expanding (t) and adding them together, we get:

[0159]

[0160] We can define the parameter γ = cos(ωτ) to simplify the formula, and we can obtain:

[0161]

[0162] Subtracting equation (24) from equation (22) yields:

[0163]

[0164] γ satisfies the following formula:

[0165]

[0166] According to equation (22), the rotational angular velocity of the motor rotor is:

[0167]

[0168] Step S6: Convert the angular velocity of the motor rotor into the motor speed and feed it back to the PI controller to form a speed closed loop for vector control; according to equation (27), it can be seen that γ contains information about the motor speed and can be used for speed estimation. This is an estimate of the parameter γ, and the estimation process is as follows:

[0169]

[0170] The motor speed e is:

[0171]

[0172] Thus, we obtained the mathematical model of the multi-continuous sampling delay module, which performs four delays on the rotor flux linkage in different time segments, and then uses basic trigonometric functions and arithmetic operations to obtain the parameter γ containing the rotational angular velocity of the motor rotor. The parameter is then processed by equations (28) and (29) to finally obtain the rotational angular velocity of the motor rotor, and then converted into the rotational speed for the motor speed closed loop.

[0173] A second aspect of the present invention provides a sensorless control system for a permanent magnet synchronous motor based on multiple continuous sampling delays, employing the sensorless control method for a permanent magnet synchronous motor based on multiple continuous sampling delays as described in any one of the first aspects, wherein the control system further includes:

[0174] The flux linkage observer module is used to construct and generate rotor flux linkage containing motor speed information. In order to estimate the motor speed, this sensorless control system selects to extract the motor speed information from the rotor flux linkage. Therefore, in order to obtain the rotor flux linkage, this invention uses a flux linkage observer to estimate the rotor flux linkage. The flux linkage observer module takes three-phase current and voltage based on the αβ coordinate system as input, and after processing, finally outputs the rotor flux linkage based on the αβ coordinate system.

[0175] The stator current period module, specifically the electronic current period estimation module, is used to estimate the period of the stator current in the αβ coordinate system. This estimation can be achieved through a phase-locked loop (PLL), a frequency-locked loop (FLL), or a zero-crossing detection module. In this embodiment, the stator current period is estimated using a zero-crossing detection module. The stator current exhibits a sinusoidal waveform in this coordinate system, and this sinusoidal signal is symmetrical about the x-axis, meaning it has both positive and negative values ​​and zero-crossing points. The zero-crossing detection module calculates the time length between these adjacent zero-crossing points and then calculates the period of the sinusoidal signal (here, the stator current) based on the length between adjacent zero-crossing points. Furthermore, in this embodiment, the stator current period estimation module is crucial for improving the overall system's adaptive capability. One-quarter of the stator current period is used as the time constant for the multi-continuous sampling delay module. As the rotational speed changes, the time constant also changes, enabling the multi-sampling method to adapt to different speed ranges.

[0176] A multi-continuous sampling delay module is used to estimate the frequency of the rotor flux output from the flux observer of the previous stage, extract the speed information of the permanent magnet synchronous motor, and feed it back to the PI controller to form a speed closed loop for vector control. The control block diagram of the multi-continuous sampling delay module is shown below. Figure 3 As shown.

[0177] Figure 4 This is the basic control block diagram for vector control. Vector control technology draws inspiration from the idea that the armature current and excitation current of a DC motor are perpendicular, uncoupled, and can be controlled independently. Based on coordinate transformation theory, it achieves decoupling of the direct axis (d-axis) and quadrature axis (q-axis) components by controlling the magnitude and direction of the stator current in a synchronous rotating coordinate system (dq-axis). This decouples the magnetic field and torque, giving the AC motor control performance similar to that of a DC motor. For three-phase PMSM vector control technology, it typically includes three parts: a speed control loop, a current control loop, and a PWM control algorithm. The speed control loop controls the motor speed, enabling both speed regulation and speed stabilization; while the current control loop accelerates the system adjustment process, allowing the motor stator to better approach the given current vector.

[0178] Figure 5 The circuit uses a PWM control loop. PWM is used for DC chopping to boost or buck DC power. In this system, the PWM module takes the voltage, controlled by the speed loop and current loop and based on the αβ coordinate system, as its input, and then uses its output modulated wave to control the inverter circuit. The current control loop enables the motor current to follow the changes in the given current (output of the speed control loop). The speed control loop can be considered as a component of the speed control system. The current control loop is a second-order oscillating element. Since the cutoff frequency of the speed loop is low, the higher-order terms of the current control loop can be ignored, and the closed-loop transfer function of the current control loop can be reduced in order.

[0179] Figure 6 This is the overall block diagram of the sensorless motor control with multi-continuous sampling delay. As can be seen from the control block diagram, the overall motor control is based on vector control (FOC), plus three parts: a flux linkage observer (NFO), a multi-continuous sampling delay module (AMCS-FE), and a stator current period estimation module (ZCD). This completes the sensorless control of the permanent magnet synchronous motor based on vector control. The flux linkage observer estimates the rotor flux linkage and the motor's electrical angle, providing flux linkage input and angle input for coordinate transformation to the multi-continuous sampling delay module, respectively. The stator current period estimation module mainly estimates the stator current period, which is the foundation and a crucial component for achieving wide-range speed estimation. The multi-continuous sampling delay module mainly estimates the flux linkage frequency, extracts the speed information, and feeds it back to the speed loop. Through this system structure, this invention achieves sensorless control of the permanent magnet synchronous motor based on vector control and realizes wide-range speed estimation. It can effectively suppress odd and even harmonics, remove DC bias in the flux linkage, and has fast dynamic response and high steady-state accuracy.

[0180] See also Figures 1 to 6 The third aspect of the present invention also provides a permanent magnet synchronous motor, which adopts the sensorless control system for a permanent magnet synchronous motor based on multiple continuous sampling delay described in the second aspect.

[0181] Furthermore, in order to more clearly highlight the technical content and beneficial effects of the present invention, the following simulation waveform data are provided along with relevant analysis to support the explanation:

[0182] I. Motor speed jump test:

[0183] Figure 7 and Figure 8 The simulated waveforms are those under conditions of sudden changes in motor speed. These waveforms are simulation results of the AMCS-FE scheme under varying motor speed conditions. Figure 7 It can be seen that the motor speed jumps from 800 r / min to 1000 r / min, while Figure 8 During the process, the motor speed jumps from 1000 r / min to 1200 r / min. The resulting motor speed change waveform demonstrates that the proposed method exhibits good dynamic performance and high steady-state accuracy during these speed jumps. The NFO module provides a high-precision rotor flux linkage, and its observation performance has been verified, ensuring the accuracy of the speed estimation performed by the AMCS-FE module.

[0184] II. DC Bias Interference Experiment:

[0185] Figure 9 and Figure 10 The results are simulations of the AMCS-FE scheme under DC bias disturbance. Figure 9 The waveform of a permanent magnet synchronous motor with a DC bias interference of 0.25 times the amplitude of the fundamental signal added at a speed of 800 r / min. Figure 10 The waveform of a permanent magnet synchronous motor with a DC bias interference of 0.25 times the amplitude of the fundamental signal is shown in the figure at a speed of 1000 r / min. As can be seen from the motor speed waveform, the proposed method still achieves accurate speed estimation under a certain DC bias disturbance.

[0186] III. Odd and Even Harmonic Interference Experiments:

[0187] Figure 11 and Figure 12 The simulation results of the AMCS-FE scheme under odd and even harmonic interference are shown. Figure 11 The waveforms of the 2nd, 3rd, 4th, and 5th harmonic interferences of 0.125 times the fundamental frequency signal are shown for a permanent magnet synchronous motor at a speed of 800 r / min. Figure 12 The waveforms of the permanent magnet synchronous motor at a speed of 1000 r / min with the 2nd, 3rd, 4th, and 5th harmonics of the fundamental frequency signal (0.125 times the original frequency) added are shown. The motor speed waveforms demonstrate that the proposed method still achieves accurate speed estimation even under certain odd and even harmonic interference conditions.

Claims

1. A sensorless control method for a permanent magnet synchronous motor based on multiple continuous sampling delay, characterized in that, The control method includes the following steps: Step S1: Monitor the motor to obtain the three-phase current and voltage of the motor; Step S2: Perform coordinate transformation on the three-phase current and voltage of the motor obtained in step S1 to obtain the coordinate system based on... Three-phase currents and voltages in a coordinate system; Step S3: The data obtained in step S2 based on... The three-phase currents and voltages in the coordinate system are used as inputs to the flux linkage observer, and the output is based on... Rotor flux linkage in coordinate system; The rotor flux linkage is: （12） in, For rotor flux in Amplitude of on-axis components For rotor flux in The amplitude of the on-axis component The rotational angular velocity of the motor rotor, For rotor flux in Phase of on-axis components For rotor flux in Phase of the on-axis component; Step S4, obtain based on The stator current in the coordinate system is obtained by the stator current period estimation module. The period of the stator current in the coordinate system is estimated to obtain an adaptive time constant based on the stator current period. ; Step S5: Based on the stator current period obtained in step S4 and the rotor flux obtained in step S3, the rotational angular velocity of the motor rotor is calculated using a multi-continuous sampling delay module. Specifically, this includes: Replace the variable in equation (12) with the symbol K. and variables At this time, the rotor flux linkage is: （13） Rewriting equation (13) yields: （14） in, represents the fundamental component, This is the DC bias component. For harmonic components, For the first The amplitude of the second harmonic component, For the first The harmonic order of the second harmonic For the first The phase of the subharmonic component; At this point, the rotor flux linkage is obtained after four delay processes at different time intervals: （15） In equation (15), The adaptive time constant is obtained from the stator current period estimation module, where: （16） in, for shaft or The period of the stator current of the shaft; The initial sampled signal and delay 2 Subsequent sampled signal Expanding and adding them together, we get: （17） Delay 2 Subsequent sampled signal and delay 4 Subsequent sampled signal Expanding and adding them together, we get: （18） Define parameters , Simplifying equations (17) and (18) respectively, we get: （19） （20） Subtracting equation (20) from equation (19) yields: （21） Satisfy the following formula: （22） According to equation (19), the rotational angular velocity of the motor rotor can be obtained as: （23）； Step S6: Convert the rotational angular velocity of the motor rotor obtained in step S5 into the speed of the motor and feed it back to the PI controller to form a speed closed loop for vector control. The method for converting the rotational angular velocity of the motor rotor into the motor's rotational speed is as follows: Define parameters according to equation (23). It is a parameter The estimated value of the parameter is then... The estimation process is as follows: （24） in, , is a variable gain coefficient; The motor speed e is: （25）。 2. The sensorless control method for permanent magnet synchronous motors based on multiple continuous sampling delays according to claim 1, characterized in that: Step S2 involves performing coordinate system transformations on the obtained three-phase currents and voltages, including: By using one or more combinations of Park transform and Clarke transform, we can obtain a result based on... Voltage and current in a coordinate system.

3. The sensorless control method for permanent magnet synchronous motors based on multiple continuous sampling delays according to claim 1, characterized in that, The specific steps of generating rotor flux in step S3 are as follows: based on Dynamic model of a permanent magnet synchronous motor in a coordinate system: （1） （2） in, It is the stator current. It is the motor terminal voltage. For stator resistance, It is a stator inductor. It is a permanent magnet flux chain. It is electromagnetic torque. It is an extreme logarithm; Define a new state variable x: （3） Let the variable y be: （4） Combining equations (1), (3), and (4), we obtain: （5） Define a vector function As shown in the following formula: （6） Combining equations (3) and (6), we obtain the vector function. The Euclidean norm is: （7） Therefore, the nonlinear flux linkage observation model can be obtained as follows: （8） in, It is the state variable of the observer. It is the gain of the observer. yes and The square of the distance between them; Next, the angle output by the magnetic flux observer... Reconstruction is performed, and the following is derived from equation (3): （9） Then we define: （10） Ultimately, we can obtain: （11） in, Angle output by the flux linkage observer The estimated value.

4. A sensorless control system for a permanent magnet synchronous motor based on multiple continuous sampling delay, characterized in that, The sensorless control method for a permanent magnet synchronous motor based on multiple continuous sampling delay, as described in any one of claims 1-3, further includes: A flux linkage observer module, which is used to construct a rotor flux linkage that includes motor speed information; The stator current period module, specifically the stator current period estimation module, is used to estimate the period of the stator current and obtain an adaptive time constant based on the stator current period. ; The multi-continuous sampling delay module is used to estimate the frequency of the rotor flux output by the flux observer module, extract the speed information of the permanent magnet synchronous motor and feed it back to the PI regulator to form a speed closed loop for vector control.

5. A permanent magnet synchronous motor, characterized in that, The sensorless control system for a permanent magnet synchronous motor based on multiple continuous sampling delay, as described in claim 4, is adopted.

Images