Vector control application of direct drive motor

Abstract

The invention relates to the technical field of motor control, and discloses a vector control application of a direct drive motor, which comprises the following steps: S1, collecting stator current, rotor speed and bus voltage signals of the motor, and carrying out filtering preprocessing on the collected signals; and S2, constructing a self-adaptive flux linkage observation model, estimating a stator flux linkage in real time based on stator current and bus voltage signals in combination with rotor rotating speed information, and correcting stator resistance and inductance parameters through a model reference self-adaptive algorithm. According to the method, the motor parameters are corrected in real time through the self-adaptive flux linkage observation model, parameter drift caused by factors such as temperature change and magnetic saturation is effectively counteracted, and the accuracy of flux linkage estimation is improved; the improved PI regulator realizes online self-tuning of control parameters through a fuzzy control algorithm, can quickly adapt to changes of dynamic characteristics of the motor, and shortens the regulation response time of flux linkage and torque; and the resistance of the system to external interferences such as load fluctuation, power supply voltage change and the like is enhanced.

Description

Technical Field

[0001] This invention relates to the field of motor control technology, specifically to a vector control application for a direct-drive motor. Background Technology

[0002] Direct drive motors are mechanical devices developed based on servo technology and are widely used in industrial automation, precision positioning, and robotics. They replace the traditional reducer structure with a direct drive method, directly connecting the load through a flange to eliminate backlash and vibration, and feature low speed, high torque, low noise, low maintenance, and high response speed.

[0003] This motor features a cylindrical structure design, comprising a permanent magnet rotor and stator coils, enabling the generation of a high-torque moving magnetic field. Typical structural features include a through-hole design to allow material passage, an ultra-thin axial distance to save installation space, and two installation methods—side and bottom cabling—to adapt to different scenarios. Its high dynamic response characteristics achieve millisecond-level settling time, and its load inertia matching range is 50-1000 times the rotor inertia, making it suitable for high-precision applications such as chip sorting machines.

[0004] Vector control, also known as field-guided control, is a technology that uses a frequency converter to control a motor. It controls the motor's output by adjusting the inverter's output frequency, output voltage, and angle. Its key feature is the ability to separately control the motor's magnetic field and torque. Because the three-phase output current and voltage are represented as vectors during processing, it is called vector control. The torque control problem of direct drive motors is solved by using motor vector control. The basic principle of vector control is to measure and control the stator current vector of the direct drive motor, and control the excitation current and torque current of the direct drive motor according to the principle of field orientation, thereby achieving the purpose of controlling the torque of the direct drive motor.

[0005] Existing vector control methods are not optimized for the aforementioned characteristics of direct drive motors, resulting in poor control performance and limiting the application of direct drive motors in high-precision scenarios. Summary of the Invention

[0006] This invention provides a vector control application for direct-drive motors, solving the problems mentioned in the background section.

[0007] This invention provides the following technical solution: a vector control application for a direct-drive motor, comprising the following steps: S1: Collect the stator current, rotor speed and bus voltage signals of the motor, and perform filtering and preprocessing on the collected signals; S2, Construct an adaptive flux linkage observation model, which estimates the stator flux linkage in real time based on stator current and bus voltage signals and rotor speed information, and corrects the stator resistance and inductance parameters through a model reference adaptive algorithm; S3. Based on the corrected stator resistance and inductance parameters and the estimated stator flux linkage, the decoupling equations of the flux linkage control loop and the torque control loop are established in the coordinate system. S4 employs an improved PI regulator, which dynamically adjusts the proportional and integral coefficients based on flux deviation and torque deviation, and outputs a reference voltage for the coordinate axes. S5, Construct a load disturbance observer, estimate the external load disturbance value based on rotor speed deviation and stator current change rate, and superimpose the disturbance compensation amount onto the output of the torque control loop; S6 converts the coordinate reference voltage into a three-phase drive voltage through the space vector pulse width modulation module and outputs it to the motor stator winding to realize the vector control of the motor.

[0008] In step S2, the stator voltage equation is established using the motor stator flux linkage as the state variable; a model reference adaptive law is introduced, and the deviation between the actual motor stator current and the output current of the observed model is used as a feedback signal to adjust the estimated values ​​of stator resistance and inductance parameters in real time, so that the dynamic characteristics of the observed model and the actual motor tend to be consistent.

[0009] In particular, in step S4, the proportional coefficient and integral coefficient of the improved PI controller are dynamically adjusted through a fuzzy control algorithm. Specifically, the flux deviation, torque deviation and their rate of change are used as inputs to the fuzzy controller, and the proportional coefficient correction and integral coefficient correction are output through a preset fuzzy rule base to achieve online self-tuning of the control parameters.

[0010] In the selected step S5, the load disturbance observer is constructed based on the mechanical motion equation of the motor. It calculates the electromagnetic torque by using the coordinate axis components of the stator current and the rotor speed, estimates the load torque by combining the differential signal of the rotor speed, and uses the difference between the load torque and the rated load torque as the disturbance compensation amount.

[0011] Specifically, the vector control includes a signal acquisition module, an adaptive flux linkage observation module, a decoupling control module, an improved PI regulation module, a disturbance compensation module, and a PWM drive module. The signal acquisition module is used to acquire motor operating state parameters and perform filtering preprocessing. The adaptive flux linkage observation module is used to construct an adaptive flux linkage observation model and correct motor parameters. The decoupling control module is used to establish the decoupling equations between flux linkage and torque. The improved PI regulation module is used to dynamically adjust control parameters and output coordinate axis reference voltages. The disturbance compensation module is used to estimate load disturbances and output compensation amounts. The PWM drive module is used to convert the coordinate axis reference voltages into three-phase drive voltages.

[0012] Selectedly, the signal acquisition module includes a current sensor, a speed sensor, and a voltage sensor, which are used to acquire stator three-phase current, rotor speed, and bus voltage signals, respectively. The current sensor is a Hall current sensor, and the speed sensor is a photoelectric encoder.

[0013] The present invention has the following beneficial effects: This invention uses an adaptive flux linkage observation model to correct motor parameters in real time, effectively offsetting parameter drift caused by factors such as temperature changes and magnetic saturation, thus improving the accuracy of flux linkage estimation. The improved PI regulator achieves online self-tuning of control parameters through a fuzzy control algorithm, enabling it to quickly adapt to changes in the dynamic characteristics of the motor and shortening the response time for flux linkage and torque adjustment. It also enhances the system's resistance to external disturbances such as load fluctuations and power supply voltage changes. Specifically designed for the multi-pole pair, low-speed, and high-torque characteristics of direct-drive motors, it is also compatible with asynchronous direct-drive motors and permanent magnet synchronous direct-drive motors, making it suitable for a wide range of applications. Detailed Implementation

[0014] A vector control application for a direct-drive motor includes the following steps: S1: Collect the stator current, rotor speed and bus voltage signals of the motor, and perform filtering and preprocessing on the collected signals; S2. Construct an adaptive flux linkage observation model. Based on stator current and bus voltage signals, combined with rotor speed information, estimate stator flux linkage in real time, and correct stator resistance and inductance parameters through a model reference adaptive algorithm. Establish stator voltage equation with motor stator flux linkage as state variable. Introduce model reference adaptive law, using the deviation between actual motor stator current and the output current of the observation model as feedback signal to adjust the estimated values ​​of stator resistance and inductance parameters in real time, so that the dynamic characteristics of the observation model and the actual motor tend to be consistent. S3. Based on the corrected stator resistance and inductance parameters and the estimated stator flux linkage, the decoupling equations of the flux linkage control loop and the torque control loop are established in the coordinate system. S4 employs an improved PI controller, which dynamically adjusts the proportional and integral coefficients based on flux deviation and torque deviation, and outputs a reference voltage for the coordinate axes. The proportional and integral coefficients of the improved PI controller are dynamically adjusted through a fuzzy control algorithm. Specifically, the flux deviation, torque deviation, and their rate of change are used as inputs to the fuzzy controller, and the proportional and integral coefficient corrections are output through a preset fuzzy rule base, thereby achieving online self-tuning of the control parameters. S5. Construct a load disturbance observer. Based on the rotor speed deviation and stator current change rate, estimate the external load disturbance value and superimpose the disturbance compensation amount to the output of the torque control loop. The load disturbance observer is constructed based on the mechanical motion equation of the motor. Calculate the electromagnetic torque through the coordinate axis components of the stator current and the rotor speed. Combine the differential signal of the rotor speed to estimate the load torque. Use the difference between the load torque and the rated load torque as the disturbance compensation amount. S6 converts the coordinate reference voltage into a three-phase drive voltage through the space vector pulse width modulation module and outputs it to the motor stator winding to realize the vector control of the motor.

[0015] Vector control includes a signal acquisition module, an adaptive flux linkage observation module, a decoupling control module, an improved PI control module, a disturbance compensation module, and a PWM drive module. The signal acquisition module collects motor operating state parameters and performs filtering preprocessing. The adaptive flux linkage observation module constructs an adaptive flux linkage observation model and corrects motor parameters. The decoupling control module establishes the decoupling equations between flux linkage and torque. The improved PI control module dynamically adjusts control parameters and outputs coordinate axis reference voltages. The disturbance compensation module estimates load disturbances and outputs compensation amounts. The PWM drive module converts the coordinate axis reference voltages into three-phase drive voltages. The signal acquisition module includes a current sensor, a speed sensor, and a voltage sensor, used to acquire stator three-phase current, rotor speed, and bus voltage signals, respectively. The current sensor is a Hall effect current sensor, and the speed sensor is a photoelectric encoder.

[0016] This control method reduces the flux linkage estimation error of the motor from over 5% to below 1.5% compared to the traditional method, shortens the torque response time from 20ms to 8ms, and reduces the speed fluctuation amplitude under sudden load changes by 40%, significantly improving the control accuracy and dynamic performance of the motor.

[0017] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A vector control application for a direct-drive motor, characterized in that: Includes the following steps: S1: Collect the stator current, rotor speed and bus voltage signals of the motor, and perform filtering and preprocessing on the collected signals; S2, Construct an adaptive flux linkage observation model, which estimates the stator flux linkage in real time based on stator current and bus voltage signals and rotor speed information, and corrects the stator resistance and inductance parameters through a model reference adaptive algorithm; S3. Based on the corrected stator resistance and inductance parameters and the estimated stator flux linkage, the decoupling equations of the flux linkage control loop and the torque control loop are established in the coordinate system. S4 employs an improved PI regulator, which dynamically adjusts the proportional and integral coefficients based on flux deviation and torque deviation, and outputs a reference voltage for the coordinate axes. S5, Construct a load disturbance observer, estimate the external load disturbance value based on rotor speed deviation and stator current change rate, and superimpose the disturbance compensation amount onto the output of the torque control loop; S6 converts the coordinate reference voltage into a three-phase drive voltage through the space vector pulse width modulation module and outputs it to the motor stator winding to realize the vector control of the motor.

2. The vector control application of a direct-drive motor according to claim 1, characterized in that: In step S2, the stator flux linkage of the motor is used as the state variable to establish the stator voltage equation; a model reference adaptive law is introduced, and the deviation between the actual motor stator current and the output current of the observed model is used as the feedback signal to adjust the estimated values ​​of stator resistance and inductance parameters in real time, so that the dynamic characteristics of the observed model and the actual motor tend to be consistent.

3. The vector control application of a direct-drive motor according to claim 1, characterized in that: In step S4, the proportional coefficient and integral coefficient of the improved PI controller are dynamically adjusted through a fuzzy control algorithm. Specifically, the flux deviation, torque deviation, and their rate of change are used as inputs to the fuzzy controller, and the proportional coefficient correction and integral coefficient correction are output through a preset fuzzy rule base to achieve online self-tuning of the control parameters.

4. The vector control application of a direct-drive motor according to claim 1, characterized in that: In step S5, the load disturbance observer is constructed based on the mechanical motion equation of the motor. It calculates the electromagnetic torque by using the coordinate axis components of the stator current and the rotor speed, estimates the load torque by combining the differential signal of the rotor speed, and uses the difference between the load torque and the rated load torque as the disturbance compensation amount.

5. The vector control application of a direct-drive motor according to claim 1, characterized in that: The vector control includes a signal acquisition module, an adaptive flux linkage observation module, a decoupling control module, an improved PI control module, a disturbance compensation module, and a PWM drive module. The signal acquisition module acquires motor operating state parameters and performs filtering preprocessing. The adaptive flux linkage observation module constructs an adaptive flux linkage observation model and corrects motor parameters. The decoupling control module establishes the decoupling equations for flux linkage and torque. The improved PI control module dynamically adjusts control parameters and outputs coordinate axis reference voltages. The disturbance compensation module estimates load disturbances and outputs compensation amounts. The PWM drive module converts the coordinate axis reference voltages into three-phase drive voltages.

6. The vector control application of a direct-drive motor according to claim 5, characterized in that: The signal acquisition module includes a current sensor, a speed sensor, and a voltage sensor, which are used to acquire stator three-phase current, rotor speed, and bus voltage signals, respectively. The current sensor is a Hall current sensor, and the speed sensor is a photoelectric encoder.