A sensorless control method for permanent magnet synchronous motor

Abstract

This application discloses a sensorless control method for a permanent magnet synchronous motor (PMSM), belonging to the field of motor control technology. The method includes: acquiring the three-phase current and three-phase voltage of the PMSM; obtaining the stator current and stator voltage in a two-phase stationary coordinate system through coordinate transformation; establishing a current equation based on a preset mathematical model of the PMSM and the stator current and voltage; establishing a current observation equation based on the current equation; and obtaining a current error equation by subtracting the current equation from the current observation equation, wherein the current observation equation includes current observation values ​​and extended back electromotive force observation values. This invention solves the problems of high system cost, complex structure, low reliability, and downtime and safety risks caused by sensor failure due to reliance on position sensors in existing technologies. It achieves accurate acquisition of motor rotor position and speed information without position sensors, reducing the cost of the motor assembly and the complexity of the system.

Description

Technical Field

[0001] This application belongs to the field of motor control technology, and specifically relates to a sensorless control method for a permanent magnet synchronous motor. Background Technology

[0002] Permanent magnet synchronous motors are widely used in electric vehicle drive systems due to their high efficiency and high power density. Magnetic field-oriented vector control is their mainstream strategy, but this strategy relies on accurate rotor position and speed information.

[0003] Currently, rotor position and speed are commonly obtained using position sensors such as encoders and resolvers. While these methods offer high accuracy, they increase system cost, wiring complexity, and installation space, reduce the reliability of the motor assembly, and sensor failure directly leads to downtime and safety risks. Sensorless control estimates rotor position and speed using observers, with sliding mode observers being widely used due to their robustness. However, the inherent high-frequency chattering in sliding mode control severely affects estimation accuracy, and traditional approach laws struggle to simultaneously achieve fast convergence and chattering suppression.

[0004] Existing technologies struggle to maintain estimation accuracy while eliminating position sensors, and they also fall short in terms of chatter suppression and dynamic response of sliding mode observers. Summary of the Invention

[0005] To address the aforementioned issues, this application provides a sensorless control method for permanent magnet synchronous motors, which solves the problems of high system cost, complex structure, low reliability, and downtime and safety risks caused by sensor failure due to reliance on position sensors in existing technologies.

[0006] This application provides a sensorless control method for a permanent magnet synchronous motor, including the following steps: The three-phase current and three-phase voltage of the permanent magnet synchronous motor are collected, and the stator current and stator voltage in the two-phase stationary coordinate system are obtained through coordinate transformation. Based on the pre-set mathematical model of the permanent magnet synchronous motor and the stator current and stator voltage, the current equation is established; Based on the current equation, the current observation equation is established. The difference between the current equation and the current observation equation is used to obtain the current error equation, where the current observation equation includes the current observation value and the extended back electromotive force observation value. Define the sliding surface function, design a novel approach law function, and solve for the extended back EMF observation value based on the current error equation, the sliding surface function, and the novel approach law function. The extended back EMF observations are low-pass filtered, and the electrical angle and electrical angular velocity are estimated using a phase-locked loop based on the filtered extended back EMF observations. By using the estimated electrical angle and electrical angular velocity as vector control feedback, sensorless control of the permanent magnet synchronous motor can be achieved.

[0007] In one embodiment, the three-phase current and three-phase voltage of a permanent magnet synchronous motor are collected, and the stator current and stator voltage in a two-phase stationary coordinate system are obtained through coordinate transformation, including: The three-phase stator winding current and three-phase stator winding voltage of the permanent magnet synchronous motor were collected respectively to obtain the three-phase current and three-phase voltage; Clark transformations were performed on the three-phase currents and three-phase voltages to obtain the stator current and stator voltage in a two-phase stationary coordinate system.

[0008] In one embodiment, based on a preset mathematical model of the permanent magnet synchronous motor and the stator current and stator voltage, a current equation is established, including: The relationship between motor parameters is determined based on the preset voltage equation, torque equation, and motion equation of the permanent magnet synchronous motor. Based on the relationship between motor parameters and stator current and stator voltage, current equations are established in a two-phase stationary coordinate system. The current equations include stator resistance, stator shaft inductance, electric angular velocity, and extended back electromotive force.

[0009] In one embodiment, a current observation equation is established based on the current equation, and the current error equation is obtained by subtracting the current equation from the current observation equation, including: The current observation equation is established based on the current equation. The current observation equation includes the current observation value and the extended back electromotive force observation value. The current observation error is obtained by subtracting the corresponding terms of the current observation equation from the current equation. A current error equation is established based on the current observation error.

[0010] In one embodiment, defining a sliding surface function includes: constructing a sliding surface function using the current observation error as a state variable, and obtaining the sliding surface function value.

[0011] In one embodiment, a novel reaching law function is designed, comprising: Construct a novel convergence law function composed of an exponential term and a continuous smooth function term; Substituting the sliding surface function value into the novel reaching law function yields the reaching law output.

[0012] In one embodiment, the extended back electromotive force observation is solved based on the current error equation, the sliding mode surface function, and the novel reaching law function, including: By combining the current error equation, the sliding mode surface function, and the approach law output, a relationship between the extended back electromotive force error and the approach law output is established. Based on the sliding mode equivalent control principle, the extended back electromotive force observation value is solved on the sliding mode surface.

[0013] In one embodiment, low-pass filtering of the extended back electromotive force observation includes: The extended back EMF observations are input into a low-pass filter to filter out high-frequency switching components, resulting in filtered extended back EMF observations.

[0014] In one embodiment, the electrical angle estimate and electrical angular velocity estimate are estimated using a phase-locked loop based on the filtered extended back electromotive force observation, including: The filtered extended back EMF observation is input into the phase-locked loop system. After phase error calculation, proportional-integral adjustment and integral operation, the estimated values ​​of electrical angle and electrical angular velocity are obtained.

[0015] In one embodiment, the estimated electrical angle and estimated electrical angular velocity are used as vector control feedback values ​​to achieve sensorless control of the permanent magnet synchronous motor, including: The electrical angle estimate is used as the electrical angle feedback value for vector control, and the electrical angular velocity estimate is used as the speed feedback value for vector control. Closed-loop vector control of the permanent magnet synchronous motor is performed based on the electrical angle feedback and speed feedback, realizing sensorless control of the permanent magnet synchronous motor.

[0016] Compared with the prior art, this application has the following advantages: 1. This invention solves the problems of insufficient convergence rate when far from the sliding surface and severe high-frequency chattering when close to the sliding surface by designing a novel reaching law function composed of continuous smooth function terms and exponential terms, and by substituting the sliding surface function into the reaching law to solve the extended back EMF observation value by solving the current error equation simultaneously. It also solves the technical contradiction that existing reaching laws cannot simultaneously take into account fast convergence and chattering suppression. This invention achieves rapid convergence of observation error and stable maintenance on the sliding surface, effectively weakens sliding chattering while improving the reaching rate, and enhances the control accuracy and anti-interference capability of the observer.

[0017] 2. This invention obtains stator current and stator voltage by collecting three-phase current and three-phase voltage and performing coordinate transformation. Then, based on the mathematical model of the permanent magnet synchronous motor, it establishes current equations and current observation equations to solve for the extended back electromotive force observation value. Subsequently, it estimates the electrical angle and electrical angular velocity through low-pass filtering and phase-locked loop. This invention solves the problems of high system cost, complex structure, low reliability caused by the reliance on position sensors in existing technologies, as well as the shutdown failures and safety risks caused by sensor failures. It realizes the accurate acquisition of motor rotor position and speed information without position sensors, reduces the cost of the motor assembly and system complexity, avoids shutdown failures caused by position sensor failures, and improves the stability and operational reliability of the control system.

[0018] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A schematic diagram of the process provided by the present invention is shown; Figure 2 A schematic diagram of the sliding mode observer algorithm model provided by the present invention is shown; Figure 3 A schematic diagram of the phase-locked loop algorithm model provided by the present invention is shown. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] like Figure 1 As shown, this application provides a sensorless control method for a permanent magnet synchronous motor, which includes the following steps.

[0023] Step 1: Collect the three-phase current and three-phase voltage of the permanent magnet synchronous motor, and obtain the stator current and stator voltage in the two-phase stationary coordinate system through coordinate transformation.

[0024] The three-phase stator winding current and three-phase stator winding voltage of the permanent magnet synchronous motor were collected separately to obtain the three-phase current and three-phase voltage. Clarke transforms were then performed on the three-phase current and three-phase voltage to obtain the stator current and stator voltage in a two-phase stationary coordinate system.

[0025] The Clarke transform formula is as follows: ; ; In the formula, , , This refers to the three-phase stator winding current. , , This refers to the voltage of the three-phase stator windings. , The stator current is in a two-phase stationary coordinate system. , The stator voltage is in a two-phase stationary coordinate system. The Clarke transform converts the current and voltage in a three-phase stationary coordinate system into the current and voltage in a two-phase stationary coordinate system, realizing the dimensionality reduction from a three-phase system to a two-phase system, which facilitates the subsequent establishment of a sliding mode observer model.

[0026] Step 2: Based on the preset mathematical model of the permanent magnet synchronous motor and the stator current and stator voltage, establish the current equation.

[0027] A mathematical model of a permanent magnet synchronous motor is constructed. This model consists of voltage equations, torque equations, and motion equations.

[0028] In the dq two-phase rotating coordinate system, the stator voltage equation is: ; ; In the formula, , These are the stator voltages along the d-axis and q-axis. , These are the stator currents along the d-axis and q-axis. , For the d-axis and q-axis stator inductance, For stator resistance, Electric angular velocity, It is a permanent magnet flux linkage.

[0029] The electromagnetic torque equation is: ; In the formula, For electromagnetic torque, It is an extreme logarithm.

[0030] The equation of motion for the machine is: ; In the formula, For rotational inertia, For mechanical angular velocity, For load torque, is the coefficient of viscous friction.

[0031] The stator voltage equations in the dq coordinate system are transformed to the αβ two-phase stationary coordinate system using the Park transformation. The Park transformation relationship is as follows: ; ; In the formula, It is an electrical angle.

[0032] Combining the Park-transformed voltage equation with the stator current and stator voltage, we obtain the current equation in the αβ coordinate system: ; In the formula, , It is a direct-axis inductor. It is a quadrature axis inductor. For stator resistance, Electric angular velocity, , To extend the back electromotive force, its expression is: ; ; For surface-mounted permanent magnet synchronous motors, the direct-axis inductance is equal to the quadrature-axis inductance, i.e. At this time, the matrix Simplified to The extended back electromotive force is only related to the permanent magnet flux linkage and electric angular velocity.

[0033] For example, take the stator resistance This value is determined by the motor winding material and wire diameter, directly affecting copper losses and observer gain design. (Using a direct-axis inductance...) For surface-mounted permanent magnet synchronous motors, This value is determined by the number of turns in the stator winding and the magnetic circuit structure, affecting the current response speed and the observer bandwidth. (The text then abruptly shifts to discussing permanent magnet flux linkage.) This value is determined by the properties of the permanent magnet material and the rotor structure, directly affecting the amplitude of the extended back EMF and the estimation accuracy of the phase-locked loop. (Taking the number of pole pairs) This value is determined by the arrangement of the rotor's permanent magnets and affects the conversion relationship between electrical angular velocity and mechanical angular velocity. The moment of inertia is taken as... This value is determined by the rotor mass and radius, and affects the system's dynamic response. The viscous friction coefficient is taken as... This value is determined by bearing characteristics and wind resistance, and affects steady-state speed fluctuations.

[0034] Step 3: Establish the current observation equation based on the current equation, and obtain the current error equation by subtracting the current equation from the current observation equation.

[0035] A current observation equation is established based on the current equation, which includes the observed current value and the extended back electromotive force (EMF) observation value. The difference between the corresponding terms of the current observation equation and the current equation is used to obtain the current observation error. A current error equation is then established based on the current observation error.

[0036] The equation for current observation is as follows: ; In the formula, , These are current observations. , To expand the observed back electromotive force.

[0037] The difference between the corresponding terms of the current observation equation and the current equation is used to obtain the current observation error. , Based on the current observation error, the current error equation is established: ; In the formula, To extend the back electromotive force observation error along the α axis, This represents the observation error of the β-axis extended back electromotive force.

[0038] Step 4: Define the sliding surface function, design a new approaching law function, and solve for the extended back electromotive force observation value based on the current error equation, the sliding surface function, and the new approaching law function.

[0039] A sliding mode surface function is constructed using the current observation error as the state variable, and the value of the sliding mode surface function is obtained. A novel reaching law function composed of exponential terms and continuously smooth function terms is constructed. Substituting the sliding mode surface function value into the novel reaching law function, the reaching law output is obtained. By simultaneously solving the current error equation, the sliding mode surface function, and the reaching law output, the relationship between the extended back EMF error and the reaching law output is established. Based on the sliding mode equivalent control principle, the extended back EMF observation value is solved on the sliding mode surface.

[0040] The sliding surface function is as follows: ; In the formula, For the sliding surface function value, These are current observations. For stator current, This represents the error in current observation.

[0041] The novel reaching law function is as follows: ; In the formula, , , For the parameters to be designed, >0, 1> >0, >0. The overall rate at which the system approaches the sliding surface determines the overall rate at which the system approaches the sliding surface. The steepness of a continuous smooth function is determined by... Determines the gain of the exponential term.

[0042] For example, take This value determines the rate at which the system approaches the sliding surface. A value that is too small leads to prolonged convergence time, while a value that is too large will exacerbate chattering. Simulation results show that setting it to 100 achieves a balance between fast convergence and chattering suppression. This value determines the steepness of the continuous smooth function. A value between 0 and 1 ensures a smooth transition, while a value of 0.5 provides moderate linearity, balancing acceleration away from the sliding surface with smoothness near it. This value determines the gain of the exponential term. A value greater than 0 ensures accelerated approach when far from the sliding surface. A value of 2 provides a moderate exponential gain, avoiding excessive overshoot.

[0043] By combining the current error equation, the sliding mode surface function, and the novel reaching law function, a relationship between the extended back electromotive force error and the reaching law output is established: ; In the formula, To expand the observed back electromotive force, To extend the actual value of the back electromotive force.

[0044] Based on the sliding mode equivalent control principle, on the sliding mode surface When the extended back EMF observation error approaches zero, solve for the extended back EMF observation value: ; Step 5: Perform low-pass filtering on the extended back EMF observations, and estimate the electrical angle and electrical angular velocity values ​​using a phase-locked loop based on the filtered extended back EMF observations.

[0045] The extended back EMF observations are input into a low-pass filter to remove high-frequency switching components, resulting in filtered extended back EMF observations. These filtered extended back EMF observations are then input into a phase-locked loop (PLL) system. After phase error calculation, proportional-integral (PI) adjustment, and integral operation, estimated electrical angle and electrical angular velocity values ​​are obtained.

[0046] The low-pass filter is a first-order low-pass filter, and its transfer function is as follows: ; In the formula, For transfer functions, The cutoff angular frequency, For the Laplace operator.

[0047] For example, take the cutoff frequency Corresponding cutoff angular frequency The basis for this value is that the output of the sliding mode observer contains high-frequency switching components, which are usually above 10kHz. Choosing 5000Hz can effectively filter out high-frequency chattering while retaining the fundamental information of the extended back EMF, thus avoiding excessive phase delay that could affect the estimation accuracy of the phase-locked loop.

[0048] In a phase-locked loop system, the phase error is calculated according to the following formula: ; In the formula, For phase error, , These are the filtered extended back electromotive force observations. This is an estimated value for the electrical angle.

[0049] The proportional-integral (PI) control calculates the electrical angular velocity correction based on the phase error, and then integrates this correction to obtain an estimated electrical angle. The PI control formula is as follows: ; In the formula, This is the correction amount for electric angular velocity. This is the proportionality coefficient. The integral coefficient is... For time derivative.

[0050] The formula for integral calculation is as follows: ; In the formula, This is an estimated electrical angle value. This is the correction amount for the electric angular velocity.

[0051] For example, take , This set of parameters makes the PLL bandwidth approximately 100Hz, balancing dynamic response speed and noise suppression capability, ensuring that the electrical angle estimate converges quickly and has small steady-state fluctuations during sudden changes in rotational speed.

[0052] Step 6: Use the estimated electrical angle and electrical angular velocity as vector control feedback values ​​to achieve sensorless control of the permanent magnet synchronous motor.

[0053] The estimated electrical angle is used as the electrical angle feedback value for vector control, and the estimated electrical angular velocity is used as the speed feedback value for vector control. Closed-loop vector control of the permanent magnet synchronous motor is performed based on the electrical angle and speed feedback values, achieving sensorless control of the permanent magnet synchronous motor.

[0054] Stability analysis is as follows: Choose the Lyapunov function: ; In the formula, The value of the Lyapunov function. This represents the function value of the sliding surface.

[0055] Differentiate the Lyapunov function: ; Substituting the new approach law function, we get: ; If and only if hour, Therefore, the novel reaching law designed satisfies the sliding mode reachability condition, and the sliding mode observer is asymptotically stable.

[0056] like Figure 2 As shown, the sliding mode observer algorithm model includes a sliding mode observer input module, a current observation equation calculation module, a current error equation calculation module, a novel reaching law solution module, a low-pass filter module, and a sliding mode observer output module. The sliding mode observer input module receives the stator voltage and stator current. The current observation equation calculation module calculates the current observation value based on the stator voltage and the extended back EMF observation value. The current error equation calculation module subtracts the stator current from the current observation value to obtain the current observation error. The novel reaching law solution module solves for the extended back EMF observation value based on the sliding mode surface function and the novel reaching law function. The low-pass filter module filters the extended back EMF observation value. The sliding mode observer output module outputs the filtered extended back EMF observation value.

[0057] like Figure 3 As shown, the phase-locked loop (PLL) algorithm model includes a PLL input module, a phase error calculation module, a proportional-integral (PI) controller module, an integral module, and a PLL output module. The PLL input module receives the filtered extended back electromotive force (EMF) observation. The phase error calculation module calculates the phase error based on the filtered EMF observation and the electrical angle estimate. The PI controller module performs proportional-integral (PI) adjustment on the phase error. The integral module performs integral calculations on the PI adjustment result. The PLL output module outputs the electrical angle estimate and the electrical angular velocity estimate.

[0058] This application, through the aforementioned steps, can acquire motor rotor position and speed information without relying on position sensors, avoiding shutdown-related faults caused by position sensor failure, reducing safety risks, and improving the stability of the control system. Simultaneously, a novel sliding mode control reaching law function is introduced into the extended back EMF observation algorithm, enabling the observation error to approach the sliding surface more quickly and remain on the sliding surface at all times. This improves the reaching speed law while effectively reducing sliding mode chattering, thus enhancing the observer's control performance and anti-interference capability.

[0059] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A sensorless control method for a permanent magnet synchronous motor, characterized in that, Includes the following steps: The three-phase current and three-phase voltage of the permanent magnet synchronous motor are collected, and the stator current and stator voltage in the two-phase stationary coordinate system are obtained through coordinate transformation. Based on the pre-set mathematical model of the permanent magnet synchronous motor and the stator current and stator voltage, the current equation is established; Based on the current equation, the current observation equation is established. The difference between the current equation and the current observation equation is used to obtain the current error equation, where the current observation equation includes the current observation value and the extended back electromotive force observation value. Define the sliding surface function, design a novel approach law function, and solve for the extended back EMF observation value based on the current error equation, the sliding surface function, and the novel approach law function. The extended back EMF observations are low-pass filtered, and the electrical angle and electrical angular velocity are estimated using a phase-locked loop based on the filtered extended back EMF observations. By using the estimated electrical angle and electrical angular velocity as vector control feedback, sensorless control of the permanent magnet synchronous motor can be achieved.

2. The sensorless control method for a permanent magnet synchronous motor according to claim 1, characterized in that, The three-phase current and three-phase voltage of the permanent magnet synchronous motor are collected, and the stator current and stator voltage in a two-phase stationary coordinate system are obtained through coordinate transformation, including: The three-phase stator winding current and three-phase stator winding voltage of the permanent magnet synchronous motor were collected respectively to obtain the three-phase current and three-phase voltage; Clark transformations were performed on the three-phase currents and three-phase voltages to obtain the stator current and stator voltage in a two-phase stationary coordinate system.

3. The sensorless control method for a permanent magnet synchronous motor according to claim 2, characterized in that, Based on the pre-defined mathematical model of the permanent magnet synchronous motor and the stator current and stator voltage, the current equations are established, including: The relationship between motor parameters is determined based on the preset voltage equation, torque equation, and motion equation of the permanent magnet synchronous motor. Based on the relationship between motor parameters and stator current and stator voltage, current equations are established in a two-phase stationary coordinate system. The current equations include stator resistance, stator shaft inductance, electric angular velocity, and extended back electromotive force.

4. The sensorless control method for a permanent magnet synchronous motor according to claim 1, characterized in that, Based on the current equation, the current observation equation is established. The difference between the current equation and the current observation equation is used to obtain the current error equation, which includes: The current observation equation is established based on the current equation. The current observation equation includes the current observation value and the extended back electromotive force observation value. The current observation error is obtained by subtracting the corresponding terms of the current observation equation from the current equation. A current error equation is established based on the current observation error.

5. The sensorless control method for a permanent magnet synchronous motor according to claim 4, characterized in that, Define the sliding surface function, including: constructing the sliding surface function with the current observation error as the state variable, and obtaining the sliding surface function value.

6. The sensorless control method for a permanent magnet synchronous motor according to claim 5, characterized in that, Design novel reaching law functions, including: Construct a novel convergence law function composed of an exponential term and a continuous smooth function term; Substituting the sliding surface function value into the novel reaching law function yields the reaching law output.

7. The sensorless control method for a permanent magnet synchronous motor according to claim 6, characterized in that, The extended back electromotive force observations are solved based on the current error equation, sliding mode surface function, and novel reaching law function, including: By combining the current error equation, the sliding mode surface function, and the approach law output, a relationship between the extended back electromotive force error and the approach law output is established. Based on the sliding mode equivalent control principle, the extended back electromotive force observation value is solved on the sliding mode surface.

8. The sensorless control method for a permanent magnet synchronous motor according to claim 1, characterized in that, Low-pass filtering is applied to the extended back EMF observations, including: The extended back EMF observations are input into a low-pass filter to filter out high-frequency switching components, resulting in filtered extended back EMF observations.

9. The sensorless control method for a permanent magnet synchronous motor according to claim 8, characterized in that, Based on the filtered extended back EMF observations, the electrical angle and electrical angular velocity estimates are estimated using a phase-locked loop, including: The filtered extended back EMF observation is input into the phase-locked loop system. After phase error calculation, proportional-integral adjustment and integral operation, the estimated values ​​of electrical angle and electrical angular velocity are obtained.

10. The sensorless control method for a permanent magnet synchronous motor according to claim 1, characterized in that, Using the estimated electrical angle and electrical angular velocity as vector control feedback values, sensorless control of the permanent magnet synchronous motor is achieved, including: The electrical angle estimate is used as the electrical angle feedback value for vector control, and the electrical angular velocity estimate is used as the speed feedback value for vector control. Closed-loop vector control of the permanent magnet synchronous motor is performed based on the electrical angle feedback and speed feedback, realizing sensorless control of the permanent magnet synchronous motor.

Images