A sensorless control method for permanent magnet synchronous motor

Abstract

This invention discloses a sensorless control method for permanent magnet synchronous motors, relating to the field of sensorless control of permanent magnet synchronous motors. This invention addresses the problems of slow dynamic response speed and low rotor position accuracy in existing technologies. It involves introducing fuzzy control theory into sliding mode control, where the approach speed of the system state variables changes with the distance from the sliding surface, and the system employs a model reference adaptive sensorless control method. Then, by designing fuzzy rules to output a switching gain k, the system switching gain is self-tuned based on this switching gain k, reducing the system's chattering problem and thus obtaining the motor speed. This invention improves the performance of the control system, increases the dynamic response speed, and achieves overshoot-free start-up.

Description

Technical Field

[0001] This invention relates to the field of sensorless control of permanent magnet synchronous motors, and more particularly to a sensorless control method for permanent magnet synchronous motors. Background Technology

[0002] Due to the influence of nonlinear factors such as multivariables, strong coupling, and parameter perturbations in PMSMs, traditional PID control strategies can no longer achieve good dynamic response performance. Sliding mode control, due to its strong robustness, has been widely used. This paper adopts sliding mode control as the outer loop control method for the system's speed. Since sensors, encoders, and other mechanical devices are needed to determine the rotor position in the control process of permanent magnet synchronous motors, the commonly used incremental encoders and Hall sensors increase the cost and size of PMSMs and reduce system stability. Therefore, research on sensorless control has received widespread attention. Sensorless control technology extracts rotor position information, such as stator voltage and current, by detecting electrical signals in the motor windings. The control algorithm then estimates the rotor speed and position. Commonly used sensorless control methods can be divided into two categories: high-frequency injection methods based on saliency tracking and back-EMF methods based on machine models. Currently, commonly used algorithms include sliding mode observers, Model Reference Adaptive Control (MRAS), and Extended Kalman Filter (EPF). Model Reference Adaptive Control (MRAS), as a nonlinear control strategy, exhibits good robustness to motor parameter perturbations and external disturbances, and is simple to implement, making it widely used in PMSM control systems. Fuzzy control can self-tune the sliding mode switching parameters based on the distance between the system state variables and the sliding surface.

[0003] Therefore, those skilled in the art are dedicated to developing a sensorless control method for permanent magnet synchronous motors, which introduces fuzzy control theory into sliding mode control, effectively resolving the contradiction between system dynamic response performance and chattering. Summary of the Invention

[0004] To achieve the above objectives, this invention provides a sensorless control method for permanent magnet synchronous motors, which solves the problems of slow dynamic response speed and low rotor position accuracy in existing systems.

[0005] This invention provides a sensorless control method for a permanent magnet synchronous motor, comprising:

[0006] S1. The d-axis voltage and q-axis voltage of the permanent magnet synchronous motor are obtained by using the model reference adaptive method to obtain the mechanical angular velocity ω of the permanent magnet synchronous motor.

[0007] S2. Establish a sliding mode observer based on the permanent magnet synchronous motor model, determine the sliding surface based on the rotor angular velocity error e, and connect the sliding surface s with the reaching law. The switching gain k is obtained by inputting it into the fuzzy controller;

[0008] S3. Based on the self-tuning sliding mode switching gain k, the chattering problem of the system is reduced, thereby obtaining the q-axis current setpoint i. qref .

[0009] Furthermore, the speed error is: e = ω * -ω;

[0010] Where, ω * The desired mechanical angular velocity, ω, is the mechanical angular velocity obtained through the model reference adaptive method.

[0011] Furthermore, the sliding surface s is:

[0012]

[0013] Approach Law for:

[0014]

[0015] in, Let α be a relatively small constant, and let β be a constant with the ranges 0 < α < 1 and β > 0, respectively.

[0016] The sliding mode control law is:

[0017]

[0018] Furthermore, the control rules of the fuzzy controller are as follows:

[0019]

[0020] Furthermore, the membership function is a triangular membership function.

[0021] The sensorless control method for a permanent magnet synchronous motor provided by this invention has the following technical advantages:

[0022] 1. This invention uses fuzzy control method to achieve self-tuning of switching gain, which improves the performance of the control system, increases the dynamic response speed of the system, and achieves overshoot-free start-up of the system.

[0023] 2. This invention employs a model reference adaptive approach to construct the observer, combining it with fuzzy control to improve the control accuracy of the rotor position. The system's fuzzy control output value k represents the sliding mode switching gain. A large sliding mode switching gain results in a fast system convergence speed, while a small gain leads to a slow convergence speed. By using fuzzy control to self-tune the sliding mode switching gain, the sliding mode approach speed is also self-tuned. The system uses a continuous function instead of the discontinuous function in traditional SMC (Sliding Mode Control), which reduces sliding mode chattering and makes sliding mode switching smoother.

[0024] 3. The stator current of the present invention has only a quadrature axis component, and the stator flux linkage vector is orthogonal to the permanent magnet flux linkage vector. By controlling the stator current, electromagnetic torque control is achieved, thereby achieving motor speed control. The control system is simple and has good torque and speed regulation performance.

[0025] 4. This invention can be applied to the field of permanent magnet synchronous motor system control and sensorless rotor position estimation, solving the problems of slow dynamic response speed and low rotor position accuracy without position sensors in existing systems.

[0026] 5. This invention is applicable to the control of various permanent magnet synchronous motors, has wide applicability, is easy to implement in hardware circuits, and has many applications.

[0027] The following will further explain the concept, specific structure, and technical effects of the present invention in conjunction with the accompanying drawings, so as to fully understand the purpose, features, and effects of the present invention. Attached Figure Description

[0028] Figure 1 This is a block diagram of the sensorless vector control of a three-phase PMSM based on FSMC-MRAS according to the present invention;

[0029] Figure 2 The fuzzy control membership input function s is used in this invention. The range of the fuzzy control input function s is [-2.8e-32.8e3]. The system adopts a triangular membership function.

[0030] Figure 3 This is the fuzzy control membership degree input for the present invention. Function, fuzzy control input function The range is [-1.6e-31.6e3], and the system uses a triangular membership function;

[0031] Figure 4 The fuzzy control output membership function of this invention has a range of k of [850 1250], and the system adopts a triangular membership function;

[0032] Figure 5The figure shows the speed waveform of traditional SMC control. As shown in the figure, traditional SMC control has a large overshoot and the system chatter is large.

[0033] Figure 6 The figure shows the speed waveform of a traditional MRAS control system. As can be seen from the figure, the speed overshoot of the traditional MRAS control system is large, and the speed fluctuation is large.

[0034] Figure 7 The figure shows the rotor position angle controlled by the FSMC-MRAS of the present invention. As can be seen from the figure, the system improves the accuracy of rotor position observation.

[0035] Figure 8 The output speed waveform of the FSMC-MRAS of this invention is shown in the figure. The system can achieve overshoot-free start-up, which greatly reduces system chattering and improves system stability compared to the traditional SMC. Detailed Implementation

[0036] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0037] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the illustrations only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0038] Some exemplary embodiments of the invention have been described for illustrative purposes. It should be understood that the invention may be implemented in other ways not specifically shown in the accompanying drawings.

[0039] according to Figure 1As shown in the control principle diagram, this embodiment of a sensorless control method for a permanent magnet synchronous motor introduces fuzzy control theory into sliding mode control. The system adopts a model reference adaptive (MRAS) sensorless control mode. By designing fuzzy rule output switching gain k, where k is the output value of the fuzzy rule, the output control principle is to set fuzzy rules in the form of if...then... based on expert experience. Different changes in the distance between the state variable and the sliding surface correspond to different fuzzy rule output values, thereby controlling the speed of sliding mode approach to achieve self-tuning, reducing the chattering problem of the system, and thus obtaining the motor speed.

[0040] The control method in this embodiment specifically includes the following steps:

[0041] S1. The d-axis voltage and q-axis voltage of the permanent magnet synchronous motor are obtained by using the model reference adaptive method to obtain the mechanical angular velocity ω of the permanent magnet synchronous motor.

[0042] The model reference adaptation consists of three parts: a reference model, an adjustable model, and an adaptive law. The adjustable model contains the mechanical angular velocity ω to be identified. The reference model is the three-phase PMSM itself. The speed error information is obtained through the reference model and the adjustable model. The speed is obtained by solving the Popov integral inequality in reverse. This part can be obtained through existing model reference adaptation methods, which will not be elaborated here.

[0043] S2. Establish a sliding mode observer based on the permanent magnet synchronous motor model, determine the sliding surface based on the rotor angular velocity error e, and connect the sliding surface s with the reaching law. The switching gain k is obtained from the input fuzzy controller; specifically, it includes:

[0044] S21. Establish a sliding mode controller based on the state equation of the permanent magnet synchronous motor.

[0045] A PMSM is a strongly coupled nonlinear power device. To simplify its analysis and modeling process, and to ignore secondary factors affecting motor control, this embodiment makes the following assumptions about the PMSM: For the excitation magnetic field generated by the permanent magnet and the spatial rotating magnetic field generated by the windings, only the fundamental frequency sinusoidal component is considered, while the harmonic components are ignored; the air gap magnetic field is sinusoidally distributed; the stator and rotor core reluctance is ignored, and core eddy current losses and hysteresis losses are disregarded; magnetic circuit saturation is ignored, and the inductance parameters remain unchanged; there are no damping windings on the rotor. The mathematical model of the permanent magnet synchronous motor (PMSM) in the stationary coordinate system is established as follows:

[0046]

[0047] Among them, u d u q i d i qL represents the voltage and current on the d and q axes, respectively. d L q Let ω be the inductance on the d and q axes. re Let ω be the electric angular velocity of the motor, and ψ be the flux linkage between the permanent magnet and the stator.

[0048] The stator flux linkage equation is:

[0049]

[0050] Where, ψ d ψ q Let be the flux linkage components on the d and q axes.

[0051] The torque equation of the permanent magnet synchronous motor in the d and q coordinates is:

[0052]

[0053] Where Te is the electromagnetic torque of the permanent magnet synchronous motor; p is the number of pole pairs of the motor. For surface-mounted PMSMs, Ld = Lq = L.

[0054] The mechanical motion equation of the electric motor is:

[0055]

[0056] Among them, T L ω is the load torque; J is the motor moment of inertia; B is the rotor viscosity coefficient; ω is the motor mechanical angular velocity.

[0057] By solving the simultaneous equations, we can obtain the state equations of the PMSM in the d and q coordinates as follows:

[0058]

[0059] Using a vector control strategy, let i d =0 decouples the electromagnetic torque current component from the air gap flux linkage current component. This confines the motor stator current to the q-axis direction, eliminating the d-axis current component (i.e., i... d =0). The electromagnetic torque is proportional to the q-axis current. Vector control makes the stator current of the motor equal to the q-axis current. By controlling the stator current, the electromagnetic torque and speed are controlled.

[0060] Setting the sliding surface:

[0061] In this embodiment, the system control variables selected for PMSM are:

[0062]

[0063] Where, ω * Let ω be the desired mechanical angular velocity of the motor.

[0064] Taking the derivative of the system control variables, we get:

[0065]

[0066] Based on the obtained system control variables, the sliding surface s is defined as follows:

[0067]

[0068] Here, c satisfies the Hurwitz condition, i.e., c > 0.

[0069] make And by taking the derivative, we can obtain:

[0070]

[0071] The above equation shows that the systematic error x1 is an exponential function with -c as a constant. The error x1 will approach zero infinitely with the constant -c as the exponent, and the convergence rate depends on the value of c.

[0072] When the derivative of the sliding surface is 0, the sliding control law is obtained as follows:

[0073]

[0074] To avoid high-frequency chattering in the controller and ensure that the state variables quickly reach the sliding surface near the sliding surface and slide towards the origin along the control law, this embodiment adopts the following fuzzy reaching law:

[0075]

[0076] in, Let α and β be relatively small constants, 0 < α < 1, β > 0. These constants are selected and adjusted according to specific circumstances. By appropriately adjusting the values ​​of α and β, the anti-interference performance of the control system can be enhanced, and the chattering of the control system can be reduced, making the control system more stable. Therefore, the control law of sliding mode control in this embodiment is:

[0077]

[0078] S22, with s and A fuzzy control rule is established using the input quantity, and the switching gain k is obtained based on the fuzzy control rule.

[0079] In a sliding mode controller, the magnitude of the switching gain k directly determines the performance of the control system. The switching gain k is adjusted in real time according to the change in the distance between the state variable and the sliding surface.

[0080] In this embodiment, the triangular membership function is used to define them as NB (negative large), NS (negative small), ZO (zero), PS (positive small), and PB (positive large), respectively, with the membership degree defined in the range of [0, 1].

[0081] When the system state variable is far from the sliding surface, the switching gain k is increased to improve the system's approach speed; when it is close to the sliding surface, the switching gain k is decreased to reduce the system's approach speed, thereby weakening the system's chattering. Based on this, the principles for establishing the fuzzy rules in this embodiment are shown in Table 1. The switching gain k is obtained after defuzzification according to the fuzzy rules shown in Table 1. For example... Figure 2 As shown, the fuzzy control membership input s function of this invention has a range of [-2.8e-32.8e3], and the system adopts a triangular membership function; Figure 3 This is the fuzzy control membership degree input for the present invention. Function, fuzzy control input function The range is [-1.6e-3 1.6e3], and the system uses a triangular membership function; Figure 4 The membership function of the fuzzy control output k in this invention is defined as follows: the range of the fuzzy control output k is [850 1250], and the system adopts a triangular membership function.

[0082] Table 1. Fuzzy Rule Table:

[0083]

[0084] The fuzzy sliding mode controller is designed as follows:

[0085]

[0086] In the formula, α and β are the same as α and β in the sliding mode approach law. By introducing fuzzy logic to control α and β, the control effect can be further improved and the system chattering can be reduced.

[0087] B′ and C′ are both constants greater than 0. When the system state is far from the sliding surface and the rate of change of the state error is large (|s| is large), the values ​​of α and β are large, which can ensure that the system can quickly reach the sliding surface. When the system state variable is close to the sliding surface and the rate of change of the error is small (|s| is small), the values ​​of α and β are small, which can ensure that the system state variable smoothly tends towards the sliding surface at a small rate, and the state variable slides towards the origin according to a predetermined trajectory, reducing system chattering.

[0088] S3. The switching gain k is self-tuned, which reduces the chattering problem of the system. The q-axis current setpoint i is obtained from the fuzzy sliding mode control law of the self-tuned switching gain k. qref .

[0089] To further verify the effectiveness of this application, the results of this application, conventional SMC control, and conventional MRAS control are compared, such as... Figure 5 The figure shows the speed waveform of traditional SMC control. As shown in the figure, traditional SMC control has a large overshoot and the system has a large chatter. Figure 6 The figure shows the speed waveform of a traditional MRAS control system. As can be seen from the figure, the speed overshoot of the traditional MRAS control system is large, and the speed fluctuation is large. Figure 7 The figure shows the rotor position angle controlled by the FSMC-MRAS of the present invention. As can be seen from the figure, the system improves the accuracy of rotor position observation. Figure 8 The output speed waveform of the FSMC-MRAS of this invention is shown in the figure. The system can achieve overshoot-free start-up, which greatly reduces system chattering and improves system stability compared to the traditional SMC.

[0090] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A position sensorless control method of a permanent magnet synchronous motor, characterized by, Comprising: S1, d-axis voltage and q-axis voltage of the permanent magnet synchronous motor are obtained by model reference adaptive method to get the mechanical angular velocity of the permanent magnet synchronous motor ; S2, a sliding mode observer is established according to a permanent magnet synchronous motor model, and a rotor angular velocity error A sliding mode surface is determined, and a sliding mode surface s and a reaching law A switching gain k is obtained in the input fuzzy controller. S3、According to the switching gain k self-tuning sliding mode switching gain, the chattering problem of the system is weakened, and then the q-axis current given value is obtained ; the q-axis current command value is: ； where the velocity error is: ; the sliding surface s is: ; the reaching law is: ; , > 0, is a small constant; a, b are constants, whose ranges are 0 < a < 1, b > 0, , , B', C' are both constants greater than 0.

2. A sensorless control method of a permanent magnet synchronous motor as claimed in claim 1, characterized in that, The control rule of the fuzzy controller is: 。 3. A sensorless control method of a permanent magnet synchronous motor as claimed in claim 1, characterized in that, The membership function is a triangular membership function.

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