SPMSM sensorless control method based on ave-hotsmo

Abstract

This invention relates to the technical field of permanent magnet synchronous motor (SPMSM) control. Specifically, it provides a sensorless control method for SPMSM based on AVE-HOTSMO. The method includes: obtaining stator current and stator voltage; establishing an SPMSM mathematical model with stator current and SPMSM back EMF as extended states; constructing a higher-order terminal sliding mode surface; constructing current-side correction injection terms and back EMF-side correction injection terms; constructing an adaptive variable-exponential higher-order terminal sliding mode observer AVE-HOTSMO to obtain stator current estimates and SPMSM back EMF estimates; inputting the SPMSM back EMF estimates into a quadrature phase-locked loop (QLL); and executing field-oriented control and space vector pulse width modulation (SVM) to control SPMSM operation. This invention solves the problem of traditional sliding mode observers and fixed-parameter higher-order terminal sliding mode observers struggling to balance fast convergence, chattering suppression, and robustness under complex operating conditions.

Description

Technical Field

[0001] This invention relates to the technical field of permanent magnet synchronous motor control, and more specifically, to a sensorless control method for SPMSM based on AVE-HOTSMO. Background Technology

[0002] Surface-mounted permanent magnet synchronous motors (SPMSMs) offer advantages such as high power density, high efficiency, and fast dynamic response, and are widely used in electric vehicles, rail transit, industrial servo systems, and automated equipment. To achieve vector control, motor drive systems typically require real-time rotor position and speed information. While mechanical position or speed sensors can directly provide this information, they increase system cost, size, and potential failure points, and can affect overall reliability in complex environments such as high temperature, vibration, and humidity. Therefore, sensorless control methods that obtain rotor position and speed through electrical quantity observation have significant engineering value.

[0003] Sliding mode observers are widely used in sensorless control of permanent magnet synchronous motors due to their simple structure and strong robustness. Traditional first-order sliding mode observers suffer from switching chattering and low-pass filter phase lag. Higher-order terminal sliding mode observers can improve finite-time convergence performance, but fixed-gain or fixed-exponential designs often struggle to simultaneously meet the requirements of fast convergence under strong dynamic conditions and low chattering under steady-state conditions. Existing gain-adaptive higher-order terminal sliding mode observers can adjust the gain according to the sliding surface amplitude, but under conditions of sudden speed changes, load disturbances, and parameter perturbations, they may still experience insufficient gain coverage in the large error phase or excessive injection in the small error phase, thus affecting the smoothness of back EMF estimation and the accuracy of speed estimation.

[0004] Therefore, it is necessary to propose a high-order terminal sliding mode observer that can change the correction injection intensity and exponential characteristics in real time according to the current observation error state, so as to enhance the convergence capability in the large error stage, actively reduce high-frequency chattering in the small error stage, and improve the dynamic response and steady-state operation quality of the SPMSM drive system without relying on mechanical position sensors. Summary of the Invention

[0005] This invention aims to solve the problem that traditional sliding mode observers and fixed-parameter high-order terminal sliding mode observers are difficult to balance between fast convergence, chattering suppression, and robustness under complex operating conditions.

[0006] Therefore, the purpose of this invention is to propose a sensorless control method for SPMSM based on AVE-HOTSMO.

[0007] To achieve the above objectives, the present invention provides a sensorless control method for SPMSMs based on AVE-HOTSMO. This sensorless control method for SPMSMs based on AVE-HOTSMO is applied to a motor drive system including an inverter and an SPMSM; SPMSM represents a surface-mounted permanent magnet synchronous motor, the output terminal of the inverter is connected to the stator winding of the SPMSM, and the inverter is used to apply a drive voltage to the SPMSM; the sensorless control method includes: Step S1: acquiring the stator current of the SPMSM and the output voltage applied to the SPMSM by the inverter, and performing coordinate transformation on the stator current of the SPMSM and the output voltage applied to the SPMSM by the inverter to obtain... Stator current and stator voltage in a stationary coordinate system;

[0008] The expression for the stator current in the stationary coordinate system is:

[0009] (1)

[0010] In equation (1), for Shaft stator current; for Shaft stator current; T indicates transpose;

[0011] The expression for the stator voltage in the stationary coordinate system is:

[0012] (2)

[0013] In equation (2), for Shaft-stator voltage; for Shaft-stator voltage;

[0014] Step S2: Establish a mathematical model of the SPMSM with the stator current and SPMSM back electromotive force as extended states; wherein, the expression for the back electromotive force of the SPMSM in the stationary coordinate system is:

[0015] (3)

[0016] In equation (3), For SPMSM Shaft back electromotive force; For SPMSM Shaft back electromotive force;

[0017] Step S3: Based on the stator current observation error between the estimated stator current and the measured stator current, construct a higher-order terminal sliding surface; wherein, the higher-order terminal sliding surface is represented as:

[0018] (4)

[0019] In equation (4), for Higher-order terminal sliding surface functions of the axis; for Higher-order terminal sliding surface functions of the axis;

[0020] Step S4: Generate an adaptive variable exponential vector in real time based on the magnitude of the stator current observation error, and construct a current-side correction injection term based on the higher-order terminal sliding surface. and back EMF side correction injection term The expression for the adaptive variable exponential vector is:

[0021] (5)

[0022] In equation (5), for Axis-adaptive variable exponent term; for Axis-adaptive variable exponent term;

[0023] Step S5: Based on the SPMSM mathematical model and the current-side correction injection term Back EMF Side Correction Injection Item And the estimated rotor electric angular velocity of SPMSM at the previous time point An adaptive variable exponent high-order terminal sliding mode observer AVE-HOTSMO is constructed to obtain stator current estimates online. and SPMSM back electromotive force estimates ;

[0024] Step S6: Estimate the SPMSM back electromotive force. Input a quadrature phase-locked loop to obtain the estimated rotor electrical angle of the SPMSM rotor. The estimated SPMSM rotor electric angular velocity at the current time point The orthogonal phase-locked loop is used to estimate the back electromotive force based on the SPMSM. Tracking SPMSM rotor electrical angle ;

[0025] Step S7: Based on the estimated rotor electrical angle of the SPMSM The estimated rotor electric angular velocity of SPMSM at the current time point It performs magnetic field orientation control and space vector pulse width modulation to control the operation of SPMSM.

[0026] Preferably, in step S2, the expression of the SPMSM mathematical model is:

[0027] (6)

[0028] In equation (6), This indicates taking the derivative with respect to time; It is represented as a state matrix related to stator inductance and stator resistance; Represented as a state matrix related to the stator inductance; Represented as a state matrix related to electric angular velocity; The input matrix represents the control input. How does it affect electric current? ;

[0029] The expression is:

[0030] (7)

[0031] The expression is:

[0032] (8)

[0033] The expression is:

[0034] (9)

[0035] The expression is:

[0036] (10)

[0037] In equations (7), (8), (9) and (10), Stator resistance; For stator inductance; It is a second-order identity matrix; It is a second-order orthogonal matrix; The rotor electric angular velocity of SPMSM;

[0038] The expression is:

[0039] (11).

[0040] Preferably, the back electromotive force of the SPMSM in the stationary coordinate system Satisfy the following expression:

[0041] (12)

[0042] In equation (12), For SPMSM permanent magnet flux linkage; It is a sine function; It is a cosine function.

[0043] Preferably, in step S3, the expression for the higher-order terminal sliding surface is specifically expanded as follows:

[0044] (13)

[0045] In equation (13), for Shaft stator current observation error; for Shaft stator current observation error; for Time derivative of the observation error of shaft stator current; for Time derivative of the observation error of shaft stator current; Positive design gain; The terminal sliding mode index, satisfy ; It is a symbolic function.

[0046] Preferably, in step S4, the current-side correction injection term The expression is:

[0047] (14)

[0048] In equation (14), for Axial current-side correction injection term; for Axial current-side correction injection term; for Axis-assisted filtering status; for Axis-assisted filtering status;

[0049] The back EMF side correction injection item The expression is:

[0050] (15)

[0051] In equation (15), for Shaft back EMF side correction injection term; for Shaft back EMF side correction injection term; for Adaptive variable exponential term gain under the control law of shaft back electromotive force term; for Adaptive variable exponential term gain under the control law of shaft back electromotive force term; This is the positive design gain of the control law for the back EMF term.

[0052] Preferably, the Axis-assisted filter status and The axis-assisted filter state satisfies the following expression:

[0053] (16)

[0054] In equation (16), This is the auxiliary filter state vector; The time derivative of the auxiliary filter state vector; This is the equivalent low-pass filter cutoff angular frequency; The positive design gain for the auxiliary control law; For adaptive variable exponent generation Axis-assisted gain; For adaptive variable exponent generation Axis-assisted gain; This is generated by stator current observation error. Auxiliary parameters of the axis; This is generated by stator current observation error. Auxiliary parameters of the axis; This represents the hyperbolic sine function.

[0055] Preferably, in step S4, the adaptive variable exponential vector satisfies the following expression:

[0056] (17)

[0057] In equation (17), Positive design gain for adjusting the range of adaptive variable exponent; This represents the stator current observation error vector; It is the hyperbolic tangent function; To take the absolute value.

[0058] Preferably, ; and Satisfy the following expression:

[0059] (18)

[0060] In equation (18), This is the auxiliary gain vector generated by the adaptive variable exponent;

[0061] and Satisfy the following expression:

[0062] (19)

[0063] In equation (19), This is the auxiliary gain vector generated by the stator current observation error.

[0064] Preferably, in step S5, the expression for the adaptive variable exponential high-order terminal sliding mode observer AVE-HOTSMO is:

[0065] (20)

[0066] In equation (20), The time derivative of the stator current estimate; The time derivative of the back electromotive force estimate; The system matrix is ​​constructed from the estimated rotor electric angular velocity.

[0067] The expression is:

[0068] (twenty one).

[0069] Preferably, in step S6, the orthogonal phase-locked loop is an orthogonal component phase-locked loop, and the orthogonal component phase-locked loop uses the SPMSM back electromotive force estimate. As input, the quadrature component phase-locked loop estimates the rotor electrical angle using SPMSM. and SPMSM rotor electric angular velocity estimates This is the output.

[0070] The sensorless control method for SPMSM based on AVE-HOTSMO provided by this invention has the following beneficial effects:

[0071] (1) By introducing an adaptive variable exponent This allows the back EMF correction injection term to be dynamically adjusted according to the current observation error, enhancing the finite-time convergence capability during the large error stage and reducing the injection intensity during the small error stage, thus mitigating the contradiction between rapid convergence and steady-state chattering from a mechanistic perspective.

[0072] (2) Using auxiliary filtering of state vector and The nonlinear term constructs a current-side correction injection, which enables the observer to have stronger dynamic tracking capability under load changes, speed variations and inverter disturbances, while avoiding noise amplification caused by traditional direct differentiation.

[0073] (3) Using SPMSM back EMF as the extended state, the rotor electrical angle and electrical angular velocity can be estimated without mechanical position sensors, reducing system cost and hardware failure risk;

[0074] (4) The meaning of the parameters is clear. and It mainly determines the finite-time convergence rate. and The main factor determining the range of variable index injection is... It can be matched with the current loop bandwidth. Used to adjust the trade-off between robustness and chattering, facilitating engineering tuning and real-time DSP implementation.

[0075] Additional aspects and advantages of the invention will become apparent from the description which follows, or may be learned by practice of the invention. Attached Figure Description

[0076] Figure 1 A schematic flowchart of an embodiment of the present invention for a sensorless control method for SPMSM based on AVE-HOTSMO is shown. Detailed Implementation

[0077] To better understand the above-mentioned objects, features, and advantages of the present invention, such as Figure 1 As shown in the accompanying drawings and specific embodiments, the present invention will be further described in detail below. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0078] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0079] The technical solution of the present invention will be illustrated below with a specific embodiment. This specific embodiment describes a sensorless control method for an AVE-HOTSMO-based SPMSM, applied to a motor drive system including an inverter and an SPMSM; SPMSM represents a surface-mounted permanent magnet synchronous motor, the output terminal of the inverter is connected to the stator winding of the SPMSM, and the inverter is used to apply a drive voltage to the SPMSM; this sensorless control method is specifically implemented through the following steps:

[0080] 1) Step 1: Sample the motor phase current and DC bus voltage, switch status, or modulation voltage information. If a three-phase current sensor is used, the result is obtained via Clarke transformation. and If a two-phase current sensor is used, then according to After reconstructing the third-phase current, a coordinate transformation is performed to obtain... Stator current and stator voltage in a stationary coordinate system;

[0081] The expression for the stator current in the stationary coordinate system is:

[0082] (1)

[0083] In equation (1), for Shaft stator current; for Shaft stator current; T indicates transpose;

[0084] The expression for the stator voltage in the stationary coordinate system is:

[0085] (2)

[0086] In equation (2), for Shaft-stator voltage; for Shaft stator voltage.

[0087] 2) Step 2: Based on the SPMSM electrical equations, establish the SPMSM mathematical model with stator current and SPMSM back electromotive force as extended states; whereby the expression for the SPMSM back electromotive force in the stationary coordinate system is:

[0088] (3)

[0089] In equation (3), For SPMSM Shaft back electromotive force; For SPMSM Shaft back electromotive force; since the mechanical time constant is usually greater than the electrical time constant, in electrical transient analysis and observer design, the short-time electrical angular velocity can be regarded as a slow variable, and the back electromotive force can be estimated as an extended state;

[0090] Back electromotive force of SPMSM in stationary coordinate system Satisfy the following expression:

[0091] (12)

[0092] In equation (12), For SPMSM permanent magnet flux linkage; It is a sine function; It is a cosine function;

[0093] The expression for the SPMSM mathematical model is as follows:

[0094] (6)

[0095] In equation (6), This indicates taking the derivative with respect to time; It is represented as a state matrix related to stator inductance and stator resistance; Represented as a state matrix related to the stator inductance; Represented as a state matrix related to electric angular velocity; The input matrix represents the control input. How does it affect electric current? ;

[0096] The expression is:

[0097] (7)

[0098] The expression is:

[0099] (8)

[0100] The expression is:

[0101] (9)

[0102] The expression is:

[0103] (10)

[0104] In equations (7), (8), (9) and (10), Stator resistance; For stator inductance; It is a second-order identity matrix; It is a second-order orthogonal matrix; The rotor electric angular velocity of SPMSM;

[0105] The expression is:

[0106] (11).

[0107] 3) Step 3: Based on the stator current observation error between the estimated stator current and the measured stator current, construct a higher-order terminal sliding surface; wherein, the higher-order terminal sliding surface is represented as:

[0108] (4)

[0109] In equation (4), for Higher-order terminal sliding surface functions of the axis; for Higher-order terminal sliding surface functions of the axis;

[0110] The expression for the higher-order terminal sliding surface is specifically expanded as follows:

[0111] (13)

[0112] In equation (13), for Shaft stator current observation error; for Shaft stator current observation error; for Time derivative of the observation error of shaft stator current; for Time derivative of the observation error of shaft stator current; Positive design gain; The terminal sliding mode index, satisfy ; It is a sign function; to improve real-time performance, an auxiliary integration variable is used for judgment. The symbol.

[0113] 4) Step 4: Construct current-side correction injection term based on high-order terminal sliding surface Current-side correction injection term The expression is:

[0114] (14)

[0115] In equation (14), for Axial current-side correction injection term; for Axial current-side correction injection term; for Axis-assisted filtering status; for Axis-assisted filtering status;

[0116] The Axis-assisted filter status and The axis-assisted filter state satisfies the following expression:

[0117] (16)

[0118] In equation (16), This is the auxiliary filter state vector; The time derivative of the auxiliary filter state vector; This is the equivalent low-pass filter cutoff angular frequency; The positive design gain for the auxiliary control law; For adaptive variable exponent generation Axis-assisted gain; For adaptive variable exponent generation Axis-assisted gain; This is generated by stator current observation error. Auxiliary parameters of the axis; This is generated by stator current observation error. Auxiliary parameters of the axis; Represents the hyperbolic sine function;

[0119] and Satisfy the following expression:

[0120] (18)

[0121] In equation (18), This is the auxiliary gain vector generated by the adaptive variable exponent; The positive design gain is the control law of the back EMF term;

[0122] and Satisfy the following expression:

[0123] (19)

[0124] In equation (19), This is the auxiliary gain vector generated by the stator current observation error.

[0125] 5) Step 5: Generate an adaptive variable exponential vector in real time based on the magnitude of the stator current observation error. The expression for an adaptive variable exponential vector is:

[0126] (5)

[0127] In equation (5), for Axis-adaptive variable exponent term; for Axis-adaptive variable exponent term;

[0128] The adaptive variable exponential vector satisfies the following expression:

[0129] (17)

[0130] In equation (17), Positive design gain for adjusting the range of adaptive variable exponent; ; This represents the stator current observation error vector; It is the hyperbolic tangent function; To obtain the absolute value; adaptive variable exponent Values ​​vary The gain increases and is limited to a preset bounded range, thereby avoiding the instability of the value caused by the infinite increase of the gain.

[0131] 6) Step 6: Construct the back EMF side correction injection term based on the high-order terminal sliding mode surface The state of the adaptive variable exponential high-order terminal sliding mode observer AVE-HOTSMO is updated to obtain the SPMSM back electromotive force estimate. ;

[0132] The back EMF side correction injection item The expression is:

[0133] (15)

[0134] In equation (15), for Shaft back EMF side correction injection term; for Shaft back EMF side correction injection term; for Adaptive variable exponential term gain under the control law of shaft back electromotive force term; for Adaptive variable exponential term gain under the control law of shaft back electromotive force term; This is the positive design gain of the control law for the back EMF term.

[0135] Sign function of higher-order terminal sliding surfaces , This is obtained by comparing adjacent sampled values ​​of the auxiliary integral variable, thus avoiding direct numerical differentiation of the current observation error;

[0136] The expression for the adaptive variable exponential high-order terminal sliding mode observer AVE-HOTSMO is:

[0137] (20)

[0138] In equation (20), The time derivative of the stator current estimate; The time derivative of the back electromotive force estimate; The system matrix is ​​constructed from the estimated rotor electric angular velocity.

[0139] The expression is:

[0140] (twenty one).

[0141] 7) Step 7: Estimate the SPMSM back electromotive force. Input quadrature component phase-locked loop (PLL). Output SPMSM rotor electrical angle estimate. And PMSM rotor electric angular velocity estimation value Afterwards, Provided to Park / inverse Park coordinate transformation, Provided to the velocity loop or the internal matrix of the observer .

[0142] 8) Step 8: Based on the given speed value and The difference is used by the speed regulator to generate the q-axis current setpoint, and combined with the d-axis current setpoint, current PI controller, inverse Park transform and SVPWM to generate the inverter drive signal.

[0143] In the above specific embodiments, parameters , Used to set the finite-time convergence rate of the current observation error; parameters , Used to set the range of the variable exponential gain of the back EMF correction injection term; Parameter Matching the current loop bandwidth, parameters This is used to adjust the trade-off between robustness in the arrival phase and steady-state chattering.

[0144] In the specific embodiments described above, the adaptive variable exponent is achieved by using the tanh function to realize bounded monotonic adjustment. In other embodiments, a piecewise continuous function, a sigmoid function, or a monotonic function with a saturation element can also be used to generate the adaptive variable exponent, as long as the function can change continuously or quasi-continuously between preset upper and lower bounds according to the magnitude of the current observation error, it falls within the scope of the present invention.

[0145] In the above specific embodiments, the phase-locked loop (PLL) is preferably an orthogonal component PLL. In other embodiments, other PLL structures or angle estimation structures capable of extracting the rotor electrical angle and electrical angular velocity from the back electromotive force estimate can also be used. The above embodiments are illustrated using a surface-mounted permanent magnet synchronous motor as an example, for motors that satisfy the same... The permanent magnet synchronous motor system with extended back EMF modeling conditions can also be equivalently adjusted according to inductance parameters and motor structure.

[0146] The following is in conjunction with the appendix Figure 1This section demonstrates the implementation process of the SPMSM sensorless control method based on AVE-HOTSMO in this specific embodiment. For example... Figure 1 As shown, Figure 1 The upper part is a schematic flowchart of the sensorless magnetic field orientation control closed loop of SPMSM. Figure 1 The lower half of the dashed box is a schematic diagram of the internal structure of the AVE-HOTSMO observer.

[0147] The main process of sensorless control using SPMSM will be described below. Figure 1 The upper part is shown, and the given speed signal is The rotor electrical angular velocity estimate obtained from the phase-locked loop feedback. The speed error is obtained by comparison. Further, the speed error is input to the first PI controller, which outputs a q-axis current reference value. Furthermore, the d-axis current reference value is set to... This indicates that the system uses SPMSM, a commonly used architecture. The control strategy ensures that the electromagnetic torque is primarily regulated by the q-axis current. Furthermore, With feedback q-axis current After comparison, the error is input to the q-axis current PI regulator, and the output is the q-axis voltage command. Furthermore, With feedback d-axis current After comparison, the error is input to the d-axis current PI regulator, and the d-axis voltage command is output. Furthermore, and Input iPark (i.e., the inverse Park transform module). This inverse Park transform module utilizes the rotor electrical angle estimate. Transform the voltage command in the dq coordinate system into Voltage command in stationary coordinate system and Furthermore, and Input to the SVPWM module, the SVPWM module according to The voltage command in the coordinate system generates the inverter switching control signal. Furthermore, the switching signal output by SVPWM drives the inverter. The inverter is powered by the DC bus voltage. It supplies power and outputs three-phase drive voltage to the PMSM. Furthermore, the PMSM generates three-phase stator current after operation. , and These currents are collected and then sent to the Clark converter module. Further, the Clark converter module converts the three-phase currents (a, b, and c) into... , and Convert to Stator current in coordinate system and Furthermore, the stator current... and One input path leads to the Park transform module. Furthermore, the Park transform module utilizes... Will and Convert to dq coordinate system and This is then fed back to the d-axis and q-axis current closed loop. Furthermore, the stator current... and Another input to the AVE-HOTSMO observer, and also inputs to the AVE-HOTSMO observer are... , as well as Furthermore, the AVE-HOTSMO observer outputs an estimate of the back electromotive force. and Furthermore, and Input a Q-PLL quadrature phase-locked loop. Further, the Q-PLL quadrature phase-locked loop obtains the rotor electrical angle estimate based on the back electromotive force estimate. And the estimated value of rotor electric angular velocity Furthermore, Feedback is sent to the Park transformation module and iPark (i.e., the inverse Park transformation module) for coordinate transformation. Furthermore, It is fed back to the velocity closed loop and used as input to the AVE-HOTSMO observer.

[0148] The following section describes the internal signal flow direction of the AVE-HOTSMO observer. For example... Figure 1 The lower half of the diagram shows the internal structure of the AVE-HOTSMO observer, within the dashed box. The first line of the observer's mathematical model receives the following input: and ,Right now Stator voltage in coordinate system; and , that is, the estimated value of the back electromotive force; and This refers to the current term correction injection term. Furthermore, the output stator current estimate in the first row of the observer's mathematical model... and Furthermore, the aforementioned and , compared with the actual collected and transformed data and By comparison, the stator current observation error is obtained. and . and Input the sliding surface function module to generate higher-order terminal sliding surface functions. and Furthermore, and The auxiliary control rate module is input, and the auxiliary control rate module is also input at the same time. , , and Furthermore, the auxiliary control module outputs the auxiliary filter status. and Furthermore, and Input current term control rate module, generate current-side correction injection term and Furthermore, and This feedback is then fed back to the first line of the observer's mathematical model to correct the dynamics of the current estimation. Furthermore, the back EMF term control law module receives the following inputs: and This refers to the current observation error; and That is, the sliding surface function; and This refers to the auxiliary filtering state; , which is the positive design gain used to adjust the range of the adaptive variable exponent; This refers to the positive design gain of the back EMF term control law. Furthermore, the back EMF term control law module outputs: and ,Will and Input auxiliary control rate; and ,Will and Input auxiliary control rate; and This refers to the back-EMF side correction injection term; and the term related to the second row of the observer's mathematical model. Signal. Furthermore, the second line of the observer mathematical model receives the following input: and That is, the back EMF side correction injection term; That is, the estimated value of the rotor's electric angular velocity; and This refers to the feedback of the back electromotive force estimate. Furthermore, the second line of the observer's mathematical model outputs a new back electromotive force estimate. and This output is sent to the upper Q-PLL quadrature phase-locked loop on one hand, and used for feedback within the observer on the other.

[0149] pass Figure 1 The following conclusions can be drawn: 1. This AVE-HOTSMO-based SPMSM sensorless control method is a sensorless SPMSM vector control method. The rotor position and speed are not obtained by an encoder, but by estimating the back EMF using AVE-HOTSMO and then obtaining it via a Q-PLL quadrature phase-locked loop. 2. The system adopts a dual closed-loop control structure with an outer speed loop and an inner current loop. The speed loop output... Current loop output and Then, the inverter is driven by inverse Park conversion and SVPWM. 3. The system adopts... The control method, explaining the Figure 1 This corresponds to the zero-d-axis current control strategy commonly used in surface-mounted permanent magnet synchronous motors. 4. AVE-HOTSMO is the core module of the entire sensorless control system. It utilizes... , , , and estimate and Then generated by Q-PLL and 5. Figure 1 The lower half explains that AVE-HOTSMO is not a simple sliding mode observer, but rather a system composed of current observation error, sliding surface function, auxiliary control law, current term control law, and back EMF term control law. 6. Current-side correction injection term. and Used to correct current estimation; back EMF side correction injection term and Used to correct the back electromotive force estimate. 7. , , , , and This indicates that the observer has an adaptive adjustment mechanism, which can dynamically adjust the injection intensity based on the current observation error and the sliding surface state. 8. Figure 1It can support the main technical route in the patent: sampling three-phase current and inverter voltage, constructing AVE-HOTSMO to estimate back EMF after coordinate transformation, obtaining rotor angle and speed through Q-PLL, and finally using FOC and SVPWM to realize SPMSM sensorless control.

[0150] In this specific embodiment, by constructing an adaptive variable-exponential back-EMF correction injection term and a current-side correction injection term with an auxiliary filtering state, the problem of traditional sliding mode observers and fixed-parameter high-order terminal sliding mode observers being unable to simultaneously achieve fast convergence, chattering suppression, and robustness under complex operating conditions is solved. Specifically, firstly, an SPMSM is established... An extended state model in a stationary coordinate system unifies stator current and back EMF as the observed states. Then, a higher-order terminal sliding mode surface is constructed, and an adaptive variable exponent is generated in real time using the magnitude of the current observation error. Based on this, current-side correction injection terms and back EMF-side correction injection terms are constructed separately, forming AVE-HOTSMO. Finally, the rotor electrical angle and electrical angular velocity are obtained from the back EMF estimate output by AVE-HOTSMO via a phase-locked loop, and used for field-oriented control and space vector pulse width modulation.

[0151] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A sensorless control method for SPMSM based on AVE-HOTSMO, applied to a motor drive system including an inverter and an SPMSM; SPMSM represents a surface-mounted permanent magnet synchronous motor, the output terminal of the inverter is connected to the stator winding of the SPMSM, and the inverter is used to apply a drive voltage to the SPMSM; characterized in that, The sensorless control method includes: Step S1: Acquire the stator current of the SPMSM and the output voltage applied to the SPMSM by the inverter, and perform coordinate transformation on the stator current of the SPMSM and the output voltage applied to the SPMSM by the inverter to obtain... Stator current and stator voltage in a stationary coordinate system; The expression for the stator current in the stationary coordinate system is: （1） In equation (1), for Shaft stator current; for Shaft stator current; T indicates transpose; The expression for the stator voltage in the stationary coordinate system is: （2） In equation (2), for Shaft-stator voltage; for Shaft-stator voltage; Step S2: Establish a mathematical model of the SPMSM with the stator current and SPMSM back electromotive force as extended states; wherein, the expression for the back electromotive force of the SPMSM in the stationary coordinate system is: （3） In equation (3), For SPMSM Shaft back electromotive force; For SPMSM Shaft back electromotive force; Step S3: Based on the stator current observation error between the estimated stator current and the measured stator current, construct a higher-order terminal sliding surface; wherein, the higher-order terminal sliding surface is represented as: （4） In equation (4), for Higher-order terminal sliding surface functions of the axis; for Higher-order terminal sliding surface functions of the axis; Step S4: Generate an adaptive variable exponent in real time based on the amplitude of the stator current observation error, and construct a current-side correction injection term based on the higher-order terminal sliding surface. and back EMF side correction injection term The expression for the adaptive variable exponential vector is: （5） In equation (5), for Axis-adaptive variable exponent term; for Axis-adaptive variable exponent term; Step S5: Based on the SPMSM mathematical model and the current-side correction injection term Back EMF Side Correction Injection Item And the estimated rotor electric angular velocity of SPMSM at the previous time point An adaptive variable exponent high-order terminal sliding mode observer AVE-HOTSMO is constructed to obtain stator current estimates online. and SPMSM back electromotive force estimates ; Step S6: Estimate the SPMSM back electromotive force. Input a quadrature phase-locked loop to obtain the estimated rotor electrical angle of the SPMSM rotor. The estimated SPMSM rotor electric angular velocity at the current time point The orthogonal phase-locked loop is used to estimate the back electromotive force based on the SPMSM. Tracking SPMSM rotor electrical angle ; Step S7: Based on the estimated rotor electrical angle of the SPMSM The estimated rotor electric angular velocity of SPMSM at the current time point It performs magnetic field orientation control and space vector pulse width modulation to control the operation of SPMSM.

2. The sensorless control method for SPMSM based on AVE-HOTSMO according to claim 1, characterized in that, In step S2, the expression of the SPMSM mathematical model is: （6） In equation (6), This indicates taking the derivative with respect to time; It is represented as a state matrix related to stator inductance and stator resistance; Represented as a state matrix related to the stator inductance; Represented as a state matrix related to electric angular velocity; The input matrix represents the control input. How does it affect electric current? ; The expression is: （7） The expression is: （8） The expression is: （9） The expression is: （10） In equations (7), (8), (9) and (10), Stator resistance; For stator inductance; It is a second-order identity matrix; It is a second-order orthogonal matrix; The rotor electric angular velocity of SPMSM; The expression is: （11）。 3. The sensorless control method for SPMSM based on AVE-HOTSMO according to claim 2, characterized in that, Back electromotive force of SPMSM in stationary coordinate system Satisfy the following expression: （12） In equation (12), For SPMSM permanent magnet flux linkage; It is a sine function; It is a cosine function.

4. The SPMSM sensorless control method based on AVE-HOTSMO according to claim 1, characterized in that, In step S3, the expression for the higher-order terminal sliding surface is specifically expanded as follows: （13） In equation (13), for Shaft stator current observation error; for Shaft stator current observation error; for Time derivative of the observation error of shaft stator current; for Time derivative of the observation error of shaft stator current; Positive design gain; The terminal sliding mode index, satisfy ; It is a symbolic function.

5. The SPMSM sensorless control method based on AVE-HOTSMO according to claim 4, characterized in that, In step S4, the current-side correction injection term The expression is: （14） In equation (14), for Axial current-side correction injection term; for Axial current-side correction injection term; for Axis-assisted filtering status; for Axis-assisted filtering status; The back EMF side correction injection item The expression is: （15） In equation (15), for Shaft back EMF side correction injection term; for Shaft back EMF side correction injection term; for Adaptive variable exponential term gain under the control law of shaft back electromotive force term; for Adaptive variable exponential term gain under the control law of shaft back electromotive force term; This is the positive design gain of the control law for the back EMF term.

6. The SPMSM sensorless control method based on AVE-HOTSMO according to claim 5, characterized in that, The Axis-assisted filter status and The axis-assisted filter state satisfies the following expression: （16） In equation (16), This is the auxiliary filter state vector; The time derivative of the auxiliary filter state vector; This is the equivalent low-pass filter cutoff angular frequency; The positive design gain for the auxiliary control law; For adaptive variable exponent generation Axis-assisted gain; For adaptive variable exponent generation Axis-assisted gain; This is generated by stator current observation error. Auxiliary parameters of the axis; This is generated by stator current observation error. Auxiliary parameters of the axis; This represents the hyperbolic sine function.

7. The SPMSM sensorless control method based on AVE-HOTSMO according to claim 6, characterized in that, In step S4, the adaptive variable exponential vector satisfies the following expression: （17） In equation (17), Positive design gain for adjusting the range of adaptive variable exponent; This represents the stator current observation error vector; It is the hyperbolic tangent function; To take the absolute value.

8. The SPMSM sensorless control method based on AVE-HOTSMO according to claim 7, characterized in that, ； and Satisfy the following expression: （18） In equation (18), This is the auxiliary gain vector generated by the adaptive variable exponent; and Satisfy the following expression: （19） In equation (19), This is the auxiliary gain vector generated by the stator current observation error.

9. The SPMSM sensorless control method based on AVE-HOTSMO according to claim 8, characterized in that, In step S5, the expression for the adaptive variable exponential high-order terminal sliding mode observer AVE-HOTSMO is: （20） In equation (20), The time derivative of the stator current estimate; The time derivative of the back electromotive force estimate; The system matrix is ​​constructed from the estimated rotor electric angular velocity. The expression is: （21）。 10. The SPMSM sensorless control method based on AVE-HOTSMO according to any one of claims 1 to 9, characterized in that, In step S6, the quadrature phase-locked loop is a quadrature component phase-locked loop, and the quadrature component phase-locked loop uses the SPMSM back electromotive force estimate. As input, the quadrature component phase-locked loop estimates the rotor electrical angle using SPMSM. and SPMSM rotor electric angular velocity estimates This is the output.

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