Motor drive control method and motor

Abstract

The application discloses a motor driving control method and a motor. The method comprises the following steps: monitoring motor current, motor rotation angle and motor rotation speed; determining the current direction of the motor current according to the motor current and the motor rotation angle; determining the dead-time compensation parameter of the driving inverter bridge based on the motor current, the current direction and the motor rotation speed; and adjusting the duty cycle of the corresponding pulse width modulation signal of the motor based on the dead-time compensation parameter, so as to perform closed-loop control on the driving inverter bridge. The application solves the technical problem of poor dead-time compensation effect of the driving inverter bridge.

Description

Technical Field

[0001] This application relates to the field of motor control, and more specifically, to a motor drive control method and a motor. Background Technology

[0002] In the field of motor drives, the dead time of the inverter bridge is set to prevent shoot-through of the switching transistors during switching, which could cause a short circuit. Related technologies primarily focus on the direction and magnitude of the current, compensating for voltage uncertainties during the dead time by pre-adjusting the output voltage. However, this compensation method is not accurate enough in some cases, resulting in poor dead time compensation performance for the drive inverter bridge.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This application provides a motor drive control method and a motor to at least solve the technical problem of poor dead-time compensation effect in driving inverter bridges.

[0005] According to one aspect of the embodiments of this application, a motor drive control method is provided, comprising: monitoring the motor current, motor rotation angle, and motor rotation speed of a motor, wherein the motor is connected to a drive inverter bridge, and the drive inverter bridge is used to drive the motor to run by controlling the on or off state of an internal switching transistor; determining the current direction of the motor current based on the motor current and the motor rotation angle, wherein the current direction is used to indicate the direction in which the motor current flows through the motor windings in the motor; determining a target dead-zone compensation parameter for the drive inverter bridge based on the motor current, current direction, and motor rotation speed, wherein the target dead-zone compensation parameter is used to compensate for voltage distortion caused by the dead-zone effect during current reversal of the drive inverter bridge; and adjusting the duty cycle of the corresponding pulse width modulation signal of the motor based on the target dead-zone compensation parameter to perform closed-loop control of the drive inverter bridge.

[0006] Furthermore, based on the motor current, current direction, and motor rotation speed, the target dead-zone compensation parameters for driving the inverter bridge are determined, including: determining the motor current parameters based on the motor current and current direction; determining index combinations based on the current parameters and motor rotation speed, wherein the index combinations are used to represent the identification information for locating the target dead-zone compensation parameters; determining the target dead-zone compensation parameters based on the index combinations and a target table, or, determining the target dead-zone compensation parameters based on the index combinations and a parameter prediction model, wherein the target table stores the correspondence between different index combinations and different dead-zone compensation parameters.

[0007] Further, based on the index combination and the target table, the target dead zone compensation parameter is determined, including: indexing the target table based on the index combination to obtain the index result, wherein the index result is used to indicate whether the index combination exists in the target table; if the index result indicates that the target table has an index combination, the target dead zone compensation parameter corresponding to the index combination is determined from the target table; if the index result indicates that the target table does not have an index combination, multiple adjacent index combinations adjacent to the index combination are determined from the target table, and the target dead zone compensation parameter is determined based on the dead zone compensation parameters corresponding to the multiple adjacent index combinations.

[0008] Furthermore, based on the dead zone compensation parameters corresponding to multiple adjacent index combinations, the target dead zone compensation parameters are determined, including: interpolating the dead zone compensation parameters corresponding to multiple adjacent index combinations to obtain the target dead zone compensation parameters.

[0009] Furthermore, the parameter prediction model includes a feature extraction layer, a feature fusion layer, and a feature prediction layer. Based on the index combination and the parameter prediction model, the target dead zone compensation parameters are determined, including: obtaining the motor state parameters of the motor; using the feature extraction layer to extract features from the motor state parameters and the index combination respectively to obtain the first parameter feature and the second parameter feature, wherein the first parameter feature is the parameter feature in the motor state parameters that is related to the dead zone effect, and the second parameter feature is the parameter feature corresponding to the index combination; using the feature fusion layer to fuse the first parameter feature and the second parameter feature to obtain the fused parameter feature; and using the feature prediction layer to predict the fused parameter feature to obtain the target dead zone compensation parameters.

[0010] Furthermore, the direction of the motor current is determined based on the motor current and the motor rotation angle, including: determining the current vector angle of the motor current based on the motor current and the motor rotation angle; and determining the current direction based on the relative position of the current vector angle and the quadrant in which the motor rotation angle is located.

[0011] Furthermore, the motor current is a three-phase current. Based on the motor current and the motor rotation speed, the current vector angle of the motor current is determined, including: performing phase conversion on the three-phase current based on a preset phase coordinate system to obtain two-phase current; and determining the current vector angle based on the two-phase current and the motor rotation speed.

[0012] According to another aspect of the embodiments of this application, a motor is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0013] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0014] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0015] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0016] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0017] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0018] In this embodiment, multi-dimensional information about the motor's operating status is obtained by monitoring the motor current, motor rotation angle, and motor rotation speed. The direction of the motor current is determined based on the motor current and motor rotation speed. Monitoring the motor rotation speed helps to accurately identify the direction of the motor current, ensuring the accuracy of the current direction judgment. Simultaneously, monitoring the motor rotation angle and rotation speed allows the motor control system to adjust the target dead-zone compensation parameters according to the actual operating conditions of the motor. Next, the target dead-zone compensation parameters for driving the inverter bridge are determined based on the motor current, current direction, and motor rotation speed. Since the determination of the target dead-zone compensation parameters comprehensively considers the motor current, current direction, and motor rotation speed, the dead-zone compensation parameters can be calculated more accurately, thereby minimizing the impact of voltage distortion caused by the dead-zone effect on the current, reducing current fluctuations, improving the smoothness of motor operation, and enabling the method of this application to adapt to different operating conditions. Furthermore, the duty cycle of the corresponding pulse width modulation signal for the motor is adjusted based on the target dead-time compensation parameters to perform closed-loop control of the drive inverter bridge. This closed-loop control method dynamically adjusts the duty cycle of the pulse width modulation signal according to the real-time monitoring of the motor status, ensuring that the output voltage matches the required voltage and reducing voltage and current fluctuations. Thus, this application solves the technical problem of poor dead-time compensation effect in the drive inverter bridge. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0020] Figure 1 This is a flowchart of a motor drive control method according to an embodiment of this application;

[0021] Figure 2 This is a flowchart of an optional motor drive control method according to an embodiment of this application;

[0022] Figure 3 This is a schematic diagram of an optional two-dimensional table according to an embodiment of this application;

[0023] Figure 4 This is a schematic diagram comparing the real-time adjusted compensation value with the fixed compensation value according to an embodiment of this application;

[0024] Figure 5 This is a schematic diagram illustrating the effect of speed on dead zone compensation according to an embodiment of this application;

[0025] Figure 6 This is a schematic diagram of the current response of a motor in a stationary state according to an embodiment of this application;

[0026] Figure 7 This is a schematic diagram of the current response of a motor in a rotating state according to an embodiment of this application;

[0027] Figure 8 This is a schematic diagram of a motor drive control device according to an embodiment of this application. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0029] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] According to an embodiment of this application, a method embodiment for motor drive control is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] This application provides a motor drive control method and a motor. The motor drive control method can be used to provide drive inverter bridge control functions for preset application scenarios. The preset application scenarios may include the following scenarios in the field: motor drive control improvement scenarios for intelligent robots (such as cleaning robots, service robots, delivery robots, etc.).

[0032] When the aforementioned preset application scenario falls within a field other than robotics, those skilled in the art should understand that the robot in the above-mentioned motor drive control method can be replaced with other objects (such as agricultural machinery, drones, etc.), and correspondingly, the motor drive control improvement can be replaced with motor drive performance improvement related to other objects. Based on this, this application embodiment uses the field of motor control as an example to exemplify the specific implementation of the above-mentioned motor drive control method.

[0033] Figure 1 This is a flowchart of a motor drive control method according to an embodiment of this application, such as... Figure 1 As shown, the method includes the following steps:

[0034] Step S102: Monitor the motor current, motor rotation angle, and motor rotation speed of the motor. The motor is connected to the drive inverter bridge, which is used to drive the motor by controlling the on or off state of the internal switching transistors.

[0035] The aforementioned motor can refer to an electric motor, which is a device that converts electrical energy into kinetic energy. In the embodiments of this application, the motor can refer to an electric motor widely used in fields such as robots, electric vehicles, and industrial automation equipment, such as a permanent magnet synchronous motor (PMSM) or a brushless direct current motor (BLDC), etc., and the motor is connected to the drive inverter bridge.

[0036] The motor current mentioned above refers to the current flowing through the motor windings. During motor operation, the current in the motor windings can be controlled by an inverter, thereby controlling the motor's torque and speed. The motor current can be either direct current (DC) or alternating current (AC). DC motor current can be controlled by a pulse width modulation (PWM) signal output from a chopper or H-bridge circuit, while AC motor current can be controlled by a PWM signal output from the inverter. Monitoring the motor current helps in real-time control of motor speed and torque. The motor current can be three-phase current, and its monitoring can be achieved using current sensors, integrated circuits, and other methods.

[0037] The aforementioned motor rotation angle refers to the rotational position of the motor rotor relative to the stator. It is typically measured in degrees and radians. The rotor refers to the rotating part of the motor, capable of rotational motion under electromagnetic influence within the motor. The stator refers to the stationary part of the motor, surrounding the rotor. In the embodiments of this application, the motor rotation angle is used to determine the motor's current position and direction to achieve accurate motor control, such as position control, speed control, and current control. Furthermore, the monitoring of the motor rotation angle can be achieved using sensors, which may include, but are not limited to, at least one of the following: encoders, Hall effect sensors, resolvers, etc.

[0038] The aforementioned motor rotational speed can refer to the rotational speed of the motor rotor per unit time, usually expressed in revolutions per minute (RPM) or angular velocity (rad / s, radians per second). In the embodiments of this application, monitoring the motor rotational speed helps to achieve closed-loop speed control, adjust the motor operating state, etc. The monitoring of motor rotational speed can be achieved through technologies such as encoders, rotary transformers, and photoelectric sensors.

[0039] The aforementioned drive inverter bridge can refer to a power electronic device, which can be composed of multiple switching transistors, typically six or more, interconnected to form a bridge circuit. The types of switching transistors can include, but are not limited to, at least one of the following: Insulated Gate Bipolar Transistor (IGBT), Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET), Silicon Carbide (SiC), and Gallium Nitride (GaN) based devices. The drive inverter bridge can be used to convert direct current (DC) to alternating current (AC), and by controlling the on / off state of each switching transistor, outputting AC power with a controllable frequency and voltage to drive a motor.

[0040] The aforementioned connection refers to the electrical connection between the motor and the drive inverter bridge. Specifically, the output terminal of the motor winding is connected to the output terminal of the inverter bridge. The PWM signal output by the inverter bridge controls the direction and magnitude of the current in the motor winding, thereby achieving speed and torque control of the motor.

[0041] In one optional embodiment, upon receiving a motor start command, the control system activates the monitoring system to monitor the motor current, motor rotation angle, and motor rotation speed. This can be achieved by connecting a low-resistance resistor in series between the inverter bridge output and the motor, and using an analog-to-digital converter to measure the voltage drop across this resistor to calculate the current. Alternatively, the rotor of a rotary transformer can be fixedly connected to the motor rotor, while the stator is connected to the motor housing or a fixed structure. Utilizing the principle of electromagnetic induction, changes in the output voltage reflect the motor's rotation angle, thus monitoring the motor's rotation angle. Another option is to mount an encoder on the motor shaft, directly connected to the motor rotor, and calculate the motor speed using the pulse frequency output by the encoder, thereby monitoring the motor's rotation speed.

[0042] Motor current monitoring methods can also include Hall effect current sensors. By placing Hall sensors between the inverter bridge output and the motor, one line per phase, a total of three points need to be placed to monitor the three-phase current. Among them, the Hall sensor mainly utilizes the relationship between the magnetic field and the current, and indirectly measures the current by detecting the change in the magnetic field around the motor windings.

[0043] For high-current applications, a current transformer can be placed on the connection line between the inverter bridge output and the motor to convert the large current in the motor windings into a small current for measurement.

[0044] In certain types of motors (such as permanent magnet synchronous motors or brushless DC motors), the motor speed can be estimated by utilizing the direct proportionality between the motor's back electromotive force (EMF) and its speed, thus monitoring the motor's rotational speed. Specifically, during motor operation, the motor's rotational speed can be indirectly calculated by measuring the back EMF signal output from the inverter to the motor windings. The frequency of the back EMF is directly proportional to the motor's rotational speed. By analyzing the frequency components of the back EMF signal using digital signal processing techniques (such as Fourier transform), the motor's rotational speed can be accurately estimated.

[0045] Through the above steps, the motor's current, rotation angle, and rotation speed can be accurately monitored, enabling the control algorithm to adjust control parameters in real time. This avoids voltage distortion caused by dead-zone effects, thereby improving the control accuracy of the current loop and reducing current distortion. Furthermore, by acquiring real-time motor operating information, dead-zone compensation parameters can be dynamically adjusted to ensure effective motor performance under different operating conditions, especially under current direction changes and different speeds, effectively compensating for voltage distortion and improving motor operating efficiency.

[0046] Step S104: Determine the direction of the motor current based on the motor current and the motor rotation angle, wherein the direction of the current is used to indicate the direction in which the motor current flows through the motor windings in the motor.

[0047] The current direction mentioned above refers to the positive or negative direction of the current flowing through the motor windings, i.e., whether the current flows into or out of one end of the motor within a specific time period. The current direction determines the path of current flow during the dead time, when the upper and lower bridge arm switches are off, thus affecting the actual voltage applied to the motor. Correct current direction determination ensures that the compensation strategy can effectively eliminate voltage distortion and prevents insufficient or excessive compensation due to misjudgment.

[0048] In one optional embodiment, after monitoring the motor current and motor rotation angle, the three-phase motor current can be converted into a coordinate system based on the motor rotation angle, such as the Direct-Quadrature (dq) coordinate system. In the dq coordinate system, the d-axis and q-axis represent the current components along the rotor flux linkage direction and perpendicular to the flux linkage direction, respectively. In the dq coordinate system, the vector angle of the motor current can be obtained by calculating the angle between the current components along the d-axis and q-axis. The current vector angle ranges from 0 to 360 degrees, reflecting the position of the motor current in space. Based on the calculated current vector angle and the motor rotation angle, the direction of the current is determined, and the quadrant in which the current vector angle lies directly reflects the positive or negative direction of the current.

[0049] In another alternative embodiment, firstly, the current value of each phase of the motor is collected and compared with a zero current threshold, for example, the current values ​​IA, IB, and IC of phases A, B, and C. If the current value of a certain phase in the motor circuit, such as phase A, is zero... If the phase current is positive, then the phase current is determined to be positive; otherwise, if... If the current in that phase is negative, then the current in that phase is negative. The motor rotation angle indicates the instantaneous position of the motor. By combining this with the determination of the positive or negative motor current, the specific direction of the current flowing through the motor windings can be determined. For example, if the motor rotates in the positive direction, and the determination of the positive current occurs within a specific range of the motor rotation angle, then the current is considered to be in the same direction as the motor rotation; conversely, if the determination of the negative current occurs in other ranges, then the current direction is opposite to the motor rotation direction.

[0050] In another alternative embodiment, in the dq coordinate system, the phase of the motor current is determined by analyzing the relationship between the magnitudes of the direct-axis current (Id) and the quadrature-axis current (Iq). and When the current phase is in the first quadrant; when and When the current phase is in the second quadrant; when and When the current phase is in the third quadrant; when and At this point, the current phase is in the fourth quadrant. Next, the rate of change of the motor's rotation angle is used to determine the motor's rotation direction, i.e., forward or reverse rotation. Combining the motor's rotational speed and direction, and the phase relationship between Id and Iq in the dq coordinate system, the specific direction of the motor current is determined. If the motor rotates forward and the current phase is in the first or fourth quadrant, the current direction is the same as the motor's rotation direction; if the current phase is in the second or third quadrant, the current direction is opposite to the motor's rotation direction. For a reverse-rotating motor, the corresponding logic is reversed.

[0051] By following the steps above, the direction of current can be accurately monitored and determined. Combined with the motor rotation angle, the accuracy of current direction determination can be improved. Especially in scenarios where the motor operating conditions are complex or change rapidly, voltage distortion caused by dead zone effect is effectively suppressed, the accuracy and response speed of motor control are improved, control errors caused by current direction conversion are reduced, and the overall performance and stability of the motor drive system are further improved.

[0052] Step S106: Based on the motor current, current direction and motor rotation speed, determine the target dead zone compensation parameters for the drive inverter bridge. The target dead zone compensation parameters are used to compensate for the voltage distortion caused by the dead zone effect during the current reversal process of the drive inverter bridge.

[0053] The aforementioned target dead-time compensation parameter refers to the calculated value used to correct voltage distortion, where voltage distortion refers to the deviation of the inverter bridge output voltage waveform from the ideal desired waveform. Voltage distortion is mainly caused by dead time, which refers to the waiting time inserted between the turn-off of one switch and the turn-on of another to avoid a DC-side short circuit caused by simultaneous conduction of the upper and lower bridge arms. The target dead-time compensation parameter can be implemented by adjusting the duty cycle of the PWM signal. The setting of the target dead-time compensation parameter can comprehensively consider the motor current, current direction, and motor rotation speed to ensure that the compensation effect is neither excessive nor insufficient, thereby effectively improving the current loop performance and reducing current distortion.

[0054] The aforementioned current swerving refers to the phenomenon where current changes direction during motor operation. In motor control, current swerving can be caused by changes in motor load, speed, or control commands. The current swerving process is susceptible to voltage distortion during the dead time, leading to a decrease in system performance.

[0055] In one optional embodiment, a suitable target dead-zone compensation parameter is determined by establishing a two-dimensional table containing current, speed, and compensation amount, combined with the real-time value of the motor current, current direction, and motor rotation speed. Specifically, the maximum current and maximum rotation speed are divided into multiple intervals, forming the rows and columns of the table. For example, the maximum current can be divided into 10 parts, and the maximum speed can also be divided into 10 parts. The motor is operated under different combinations of current and speed to obtain the operating characteristics of the current during the turning process. The operating characteristics include current transition characteristics, voltage distortion, etc. The current transition characteristics can refer to the characteristics of the current value changing with time during the process of the current changing from positive to negative or from negative to positive, involving the rate of the current zero crossing and the degree of fluctuation during the transition process. The degree of voltage distortion can refer to the degree of deviation between the inverter bridge output voltage and the ideal voltage during the current turning process after the dead time is introduced. This deviation is manifested as an additional voltage increase or decrease, and a change in the shape of the voltage waveform. Then, by comparing the effects of different compensation parameters, a suitable compensation value is found, and these data are then filled into the pre-created two-dimensional table. Each table cell represents a compensation parameter under a specific operating condition. During operation, the motor control system monitors the motor's current and rotational speed in real time, and searches for the closest compensation parameter in a table based on these current values. If the current current and speed combination does not appear directly in the table, interpolation is performed using adjacent data points to obtain a more accurate compensation value.

[0056] In another optional embodiment, the drive inverter bridge system is run under various combinations of motor current, current direction, and rotational speed, recording key data during each run, including but not limited to current waveforms, motor rotational speed, motor rotation angle, and the corresponding voltage waveform distortion. This data is used as the dataset for the target dead-zone compensation parameter prediction model. The data is cleaned and preprocessed, such as removing outliers and normalizing current and speed data. The processed dataset is then divided into training, validation, and test sets. The selected machine learning model is trained using the training set data to minimize the error between the model's predicted target dead-zone compensation parameters and the actual compensation parameters. The machine learning model can include, but is not limited to, at least one of the following: multilayer perceptron, convolutional neural network, support vector machine, decision tree, and deep neural network.

[0057] By using validation set data, the model's hyperparameters are adjusted, and the overall performance of the model is evaluated using test set data. The model parameters are iteratively adjusted to obtain a well-trained target dead zone compensation parameter prediction model. During motor operation, the motor's current value, current direction, and rotational speed information are collected in real time and input into the trained prediction model to obtain appropriate target dead zone compensation parameters under the current operating conditions.

[0058] In another optional embodiment, adaptive adjustment rules are set for the proportional (P), integral (I), and derivative (D) coefficients of the proportional-integral-derivative (PID) controller. These coefficients are dynamically adjusted based on the real-time current, current direction, and rotational speed of the motor to improve control performance and establish a control model for driving the inverter bridge. The deviation between the actual output voltage and the desired voltage of the inverter bridge is compared, and the error is calculated. Parameter adjustment follows these rules: if a rapid increase in motor speed is detected, the P value is increased to accelerate the response; when the speed is stable, the P value is maintained or decreased. If the current direction changes frequently, the I value is decreased to avoid instability caused by the accumulation of integral terms; when the current direction is stable, the I value can be increased to reduce steady-state error. Adjustment is made according to the rate of current change: when the current changes rapidly, the D value is increased to compensate in advance; when the current changes slowly, the D value is decreased to avoid overreaction. Based on the set control rules, the P, I, and D parameters of the PID controller are adjusted in real time to obtain good target dead-zone compensation parameters under the current operating conditions.

[0059] Through the above steps, by comprehensively considering motor current, current direction and rotation speed, and dynamically adjusting the target dead zone compensation parameters, the performance degradation of the current loop and current distortion caused by dead time are effectively suppressed, enabling the motor current to quickly and accurately follow the control command, thereby improving the response speed and control accuracy of current control.

[0060] Step S108: Adjust the duty cycle of the corresponding pulse width modulation signal of the motor based on the target dead zone compensation parameter to perform closed-loop control of the drive inverter bridge.

[0061] The aforementioned pulse width modulation (PWM) signal can refer to a signal modulation technique used to control the power output of a system. In the field of motor drives, PWM signals are used to control the on and off times of the switching transistors in an inverter bridge to generate variable output voltage and current, thereby controlling the speed and torque of the motor. A PWM signal consists of a series of periodic pulses, the width of which can be adjusted within each cycle. The pulse width determines the average value of the output voltage, thus affecting the motor's operating state.

[0062] The duty cycle mentioned above refers to a concept describing the ratio of the high-level time in a PWM signal to the entire period, usually expressed as a percentage. For example, if a PWM signal has a period of 10ms and a high-level duration of 5ms, then the duty cycle of that PWM signal is 50%. In motor control, the duty cycle is adjusted by changing the length of the high-level time in the PWM signal.

[0063] The aforementioned closed-loop control can refer to a control system in which the output of the controlled system is fed back to the controller. The controller adjusts the control strategy based on the deviation between the feedback signal and the set value to achieve precise regulation of the output. In the embodiments of this application, closed-loop control specifically refers to dynamically adjusting the duty cycle of the PWM signal to compensate for the dead-zone effect based on the real-time current, current direction, and rotational speed feedback of the motor, thereby improving the control performance of the drive inverter bridge. The adjusted motor operating state (such as current and speed) is then detected again and fed back to the control system.

[0064] In one alternative embodiment, the obtained target dead-time compensation parameters are applied to the duty cycle of the PWM signal for adjustment based on the current direction. If the current direction is positive, a percentage T is added to the planned PWM duty cycle. d The compensation amount is / T, and vice versa, the compensation amount is subtracted, where T d T is the dead time, and T is the switching period. Next, the adjusted PWM signal is sent to the inverter bridge to control the on and off states of internal switching transistors (such as MOSFETs or IGBTs), thereby accurately controlling the motor's voltage and current. The motor's operating state (such as current and speed) adjusted by the PWM signal is detected again and fed back to the control system, compared with the target value, to further adjust the PWM signal's duty cycle, forming a closed-loop control mechanism.

[0065] In another optional embodiment, firstly, a mathematical model of the motor and its driving inverter bridge is established. This model includes key factors such as the motor's voltage, current, electromagnetic torque, and the switching state of the inverter bridge. Based on the current motor state (current, current direction, rotational speed) and the target dead-zone compensation parameters, the mathematical model predicts the motor's voltage, current, and electromagnetic torque states over a future period. Based on this future state prediction, a model predictive control method based on the target dead-zone compensation parameters uses optimization algorithms (such as quadratic programming, linear programming, etc.) to determine a predicted PWM signal duty cycle sequence. During model predictive control adjustment, the target dead-zone compensation parameters are incorporated as an additional constraint or part of the objective function to ensure that the PWM signal adjustment takes into account the dead-zone effect. The motor state, including current, current direction, and rotational speed, is monitored in real time and compared with the predicted values ​​to form a closed-loop feedback. If there is a significant difference between the prediction and the actual state, the model predictive control updates the model prediction and readjusts the control sequence to ensure that the motor state is close to the expected state.

[0066] In the above steps, the dynamic adjustment mechanism overcomes the problem of poor performance of traditional fixed compensation values ​​under different operating conditions, improves the overall performance and efficiency of the motor drive system, reduces overshoot and oscillation in the control process, and ensures that the motor runs more smoothly and efficiently.

[0067] In this embodiment, multi-dimensional information about the motor's operating status is obtained by monitoring the motor current, motor rotation angle, and motor rotation speed. The direction of the motor current is determined based on the motor current and motor rotation speed. Monitoring the motor rotation speed helps to accurately identify the direction of the motor current, ensuring the accuracy of the current direction judgment. Simultaneously, monitoring the motor rotation angle and rotation speed allows the control system to adjust the target dead-zone compensation parameters according to the actual operating conditions of the motor. Next, the target dead-zone compensation parameters for driving the inverter bridge are determined based on the motor current, current direction, and motor rotation speed. Since the determination of the target dead-zone compensation parameters comprehensively considers the motor current, current direction, and motor rotation speed, the target dead-zone compensation parameters can be calculated more accurately, thereby minimizing the impact of voltage distortion caused by the dead-zone effect on the current, reducing current fluctuations, improving the smoothness of motor operation, and enabling the method of this application to adapt to different operating conditions. Furthermore, the duty cycle of the corresponding pulse width modulation signal for the motor is adjusted based on the target dead-time compensation parameters to perform closed-loop control of the drive inverter bridge. This closed-loop control method dynamically adjusts the duty cycle of the pulse width modulation signal according to the real-time monitoring of the motor status, ensuring that the output voltage matches the required voltage and reducing voltage and current fluctuations. Thus, this application solves the technical problem of poor dead-time compensation effect in the drive inverter bridge.

[0068] In this embodiment of the application, the method further includes: determining the target dead-zone compensation parameters for driving the inverter bridge based on the motor current, current direction, and motor rotation speed, including: determining the motor current parameters based on the motor current and current direction; determining the index combination based on the current parameters and motor rotation speed, wherein the index combination is used to represent the identification information for locating the target dead-zone compensation parameters; determining the target dead-zone compensation parameters based on the index combination and a target table, or determining the target dead-zone compensation parameters based on the index combination and a parameter prediction model, wherein the target table stores the correspondence between different index combinations and different dead-zone compensation parameters.

[0069] The aforementioned current parameters can refer to a quantitative description of the motor current under different conditions. Current parameters can include the magnitude, direction, and rate of change of the motor current. In the embodiments of this application, the current parameters mainly consist of the amplitude and direction of the motor current, providing real-time feedback on the motor's operating state. For example, if the motor current is 3A at a certain moment and the current direction is positive, then the current parameter at this time can be expressed as (3A, positive).

[0070] The aforementioned index combination refers to a set of identifying information used to locate a specific compensation value during the determination of target dead-zone compensation parameters. The index combination can consist of the motor's current parameters and motor rotational speed, pointing together to a specific operating condition. For example, (3A, forward, 1000rpm) can be considered an index combination. This index combination forms the basis for searching or predicting suitable target dead-zone compensation parameters in a database or algorithm model.

[0071] The aforementioned identification information can refer to a marker used to distinguish and locate data or states. In the embodiments of this application, the identification information can refer to information jointly constructed by current parameters and motor rotation speed, used to find or generate corresponding target dead zone compensation parameters in a target table or parameter prediction model.

[0072] The aforementioned target table can refer to a database table storing different motor operating conditions and corresponding dead-zone compensation parameters. For example, the target table could be a database table consisting of operating conditions composed of current parameters and motor rotation speed, along with corresponding dead-zone compensation parameters. The target table can be pre-created using experimental data, simulation results, or theoretical calculations, and is used to quickly retrieve the compensation parameters that best match the current motor operating state, thereby achieving effective compensation for the dead-zone effect.

[0073] The aforementioned parameter prediction model can refer to an algorithmic model constructed using machine learning, deep learning, or other data-driven methods. The parameter prediction model can predict appropriate dead zone compensation parameters based on the input motor operating state data, which may include current parameters and rotational speed, etc.

[0074] The aforementioned correspondence can refer to the key information stored in the target table, while the index relationship describes the mapping between different index combinations and the matching dead zone compensation parameters. Each index combination has its corresponding compensation parameters in the table, which are derived based on a large amount of experimental or simulation data.

[0075] In one optional embodiment, firstly, the motor current parameters are determined based on the detected motor current and current direction. These current parameters are then combined with the motor's rotational speed to form an index combination. For example, if the current parameter is (3A, forward) and the motor rotational speed is 1000 rpm, then the index combination would be (3A, forward, 1000 rpm). Next, a target table is pre-constructed. This target table is a database storing a large number of suitable dead-zone compensation parameters corresponding to different operating conditions (current parameters and rotational speeds) obtained from experiments or simulations. The index combinations are compared with the target table. When there is a direct match between the current parameter and rotational speed in the index combination and a record in the target table, the dead-zone compensation parameter in that record is directly read as the compensation value for the current operating condition. If there is no direct match in the parameter combination in the index combination, then interpolation processing is required using methods such as linear interpolation or polynomial interpolation. Specifically, the interpolation processing involves calculating the dead-zone compensation parameter suitable for the current index combination based on the multiple nearest-neighbor compensation parameter records already existing in the target table. For example, if (3A, forward, 1000rpm) is not in the table, but (3A, forward, 950rpm) and (3A, forward, 1050rpm) are in the table, then the compensation parameters applicable to the 1000rpm rotation speed can be calculated based on these two records using an interpolation method.

[0076] In another optional embodiment, the real-time current parameters and rotational speed of the motor are monitored and acquired to form an index combination. Subsequently, the feature extraction layer of the parameter prediction model extracts features from the motor state parameters (current and rotational speed) and the index combination. Specifically, the original current parameters and rotational speed are first converted into more expressive feature vectors, such as extracting the rate of change of current magnitude, the frequency of current direction reversal, and the stability of rotational speed. Next, the current parameter features and the index combination features are fused to generate a fused parameter feature that integrates motor operating state information. Finally, the feature prediction layer in the model predicts the fused parameter feature to calculate the target dead zone compensation parameters under the current operating condition.

[0077] In the above method, the use of target tables and parameter prediction models can reduce the complexity of control algorithm design in the control system, making the control strategy simpler and more effective, and reducing the difficulty and cost of implementation. The determination of dead-zone compensation parameters comprehensively considers the real-time operating state of the motor, including current magnitude, direction, and rotational speed, enabling the control system to more accurately perform closed-loop control of the motor, reducing current loop errors, and improving the motor's response speed and control accuracy. Through accurate dead-zone compensation, the decrease in motor operating efficiency caused by the dead-zone effect is reduced, energy consumption is lowered, and the overall system efficiency is improved.

[0078] In this embodiment of the application, the method further includes: determining a target dead zone compensation parameter based on index combinations and a target table, including: indexing the target table based on index combinations to obtain index results, wherein the index results are used to indicate whether an index combination exists in the target table; if the index results indicate that an index combination exists in the target table, determining the dead zone compensation parameter corresponding to the index combination from the target table; if the index results indicate that no index combination exists in the target table, determining multiple adjacent index combinations adjacent to the index combination from the target table, and determining the dead zone compensation parameter based on the dead zone compensation parameters corresponding to the multiple adjacent index combinations.

[0079] The aforementioned index can refer to a combination of variables, such as the motor's current parameters and rotational speed, used to locate specific dead-zone compensation parameters in a target table. The index is similar to a search key in a database, helping to quickly locate the compensation strategy that matches the current motor state.

[0080] The index results mentioned above can refer to the feedback obtained after querying the target table using the index, indicating whether there are records in the target table that match the given index combination. The index results may indicate whether the record exists or not.

[0081] The adjacent index combination mentioned above refers to the records in the target table that are closest to the queried index combination in terms of various parameters. When no directly matching index is found, the adjacent index combination is used for interpolation calculations to fill in the gaps.

[0082] In one optional embodiment, firstly, an index combination is constructed based on the real-time monitored motor current, motor current direction, and motor rotation speed. Next, the constructed index combination is used to query a predefined target table. The target table is a pre-built database storing suitable dead-zone compensation parameters for different motor operating conditions. The target table can be constructed based on a large amount of experimental data, theoretical motor models, and optimization algorithms. After the query is completed, an index result is obtained, indicating whether there is a record in the target table that matches the current index combination. If it exists, the compensation parameter in that record is used directly; if it does not exist, it means that there is no directly corresponding compensation parameter for the currently monitored operating condition. When the index result indicates that there is a record in the target table that matches the current index combination, the dead-zone compensation parameter is directly read from the target table. If the index result indicates that there is no record in the target table that matches the current index combination, the system automatically retrieves several adjacent index combinations that are close to the current index combination in the parameter space. These adjacent combinations are close to the current operating condition in terms of current parameters, current direction, and rotation speed, but have differences. The target dead-zone compensation parameter is determined based on the dead-zone compensation parameters corresponding to the adjacent index combinations.

[0083] In the above method, the dead-zone compensation parameters suitable for the current motor operating state can be found directly or indirectly through indexing, improving control accuracy and motor operating efficiency. Using indexes and target tables, compensation parameters can be quickly located and obtained, enhancing the real-time response capability of the motor control system. Even if there is no directly matching record in the target table, the system can adaptively adjust the compensation strategy by using adjacent index combinations through interpolation calculations, adapting to a wider range of operating conditions.

[0084] In this embodiment of the application, the method further includes: determining a target dead zone compensation parameter based on dead zone compensation parameters corresponding to multiple adjacent index combinations, including: performing interpolation processing on the dead zone compensation parameters corresponding to multiple adjacent index combinations to obtain the target dead zone compensation parameter.

[0085] The interpolation process described above can refer to a mathematical method used to find a continuous function between known data points, thereby estimating the value of unknown data points. Interpolation processes can include, but are not limited to, at least one of the following: linear interpolation, polynomial interpolation, and bilinear interpolation.

[0086] Linear interpolation refers to estimating the function value at any point between two known data points using a linear equation if the function value changes linearly between them. Polynomial interpolation uses a higher-order polynomial to fit the data points, more accurately reflecting the complex relationships between the data. Spline interpolation uses a piecewise polynomial (usually a cubic polynomial) to connect the data points, ensuring that the function curve between the data points is not only continuous but also smooth.

[0087] In an optional embodiment, when the trends of motor current, current direction, and rotational speed are relatively linear, and the compensation parameters in the target table also exhibit a linear relationship, linear interpolation can be used. For example, when the combination of motor current, current direction, and rotational speed monitored in real time does not find a matching record in the target table, a missing combination is formed. At this time, the motor control system can automatically locate and determine the four cells in the parameter space of the target table that are closest to the missing combination. These four cells are located at the four corners surrounding the missing combination, and the compensation parameters of these cells have been determined experimentally or empirically. Then, using the positions of these cells and the compensation parameters, a two-dimensional linear equation is constructed. Based on the currently monitored motor current and rotational speed, the linear equation is substituted to obtain the target dead-zone compensation parameters under the current operating condition.

[0088] In another optional embodiment, when there is an interaction between motor current, current direction, and rotational speed, and the trend of the compensation parameters is bilinear, bilinear interpolation can be used. Specifically, this involves locating the position of the missing combination in the parameter space of the target table. After determining the position of the missing combination, the motor control system finds four cells closest to the missing combination, located above, below, to the left, and to the right of the missing combination position, forming a small rectangular area. First, a linear interpolation calculation is performed along both the current magnitude and rotational speed dimensions to obtain estimated values ​​of the compensation parameters in both directions. Then, based on these estimated values, a second linear interpolation is performed to obtain the final target dead zone compensation parameters.

[0089] In another alternative embodiment, when the relationship between the compensation parameters and motor current, current direction, and rotational speed is nonlinear, but can be well fitted by a polynomial curve, polynomial interpolation can be used. Specifically, this involves finding multiple points, including those containing missing combinations, whose compensation parameters are recorded in a table. A polynomial equation is constructed using these points, typically a quadratic polynomial or higher, to capture more complex nonlinear trends. The current motor current and rotational speed values ​​are then substituted into the polynomial equation to calculate the target dead-zone compensation parameters.

[0090] In the above method, interpolation can calculate dead-zone compensation parameters that are closer to the actual requirements based on known data points near the current operating state of the motor, thereby improving the accuracy and effectiveness of inverter bridge control. The motor's operating state is dynamically changing, and interpolation ensures that even in operating conditions not directly recorded in the target table, the duty cycle of the PWM signal can be adjusted in a timely manner to effectively compensate for the dead-zone effect and achieve smooth motor operation.

[0091] In this embodiment of the application, the method further includes: a parameter prediction model comprising a feature extraction layer, a feature fusion layer, and a feature prediction layer; determining target dead zone compensation parameters based on index combination and the parameter prediction model; including: acquiring motor state parameters of the motor; extracting features from the motor state parameters and index combination using the feature extraction layer to obtain first parameter features and second parameter features, wherein the first parameter features are parameter features in the motor state parameters associated with the dead zone effect, and the second parameter features are parameter features corresponding to the index combination; fusing the first parameter features and the second parameter features using the feature fusion layer to obtain fused parameter features; and predicting the fused parameter features using the feature prediction layer to obtain the target dead zone compensation parameters.

[0092] The aforementioned feature extraction layer can refer to the first few layers of a neural network model, whose main task is to extract features that are helpful for prediction from the original input data. In the embodiments of this application, the feature extraction layer is used to analyze the combination of motor state parameters and indices to identify parameter features associated with the dead-zone effect. For example, the feature extraction layer will identify features closely related to the dead-zone effect, such as current magnitude and rate of change of rotational speed, remove irrelevant or redundant information, and improve the predictive ability of the model.

[0093] The aforementioned feature fusion layer can refer to a layer following feature extraction. The feature fusion layer combines features extracted from different sources to construct a feature representation. In embodiments of this application, the feature fusion layer can receive first-parameter features and second-parameter features from the feature extraction layer, and combine these features into an enhanced feature set using a specific fusion method. The first-parameter features can refer to features extracted from motor state parameters that are particularly related to the dead-zone effect. Examples include the peak value of the motor current, the rate of change of the current direction, and the stability of the motor's rotational speed. The second-parameter features can refer to features extracted based on index combinations. The second-parameter features can include a quantized representation of the index combinations, such as the quantization levels of current and speed, and statistical or trend features obtained based on these combinations.

[0094] The fusion method of the aforementioned feature fusion layer may include, but is not limited to, at least one of the following: concatenation, weighted summation, and attention mechanism. The fused feature set can reflect the characteristics of the motor's operating state, providing richer information for the final dead-zone compensation parameter prediction.

[0095] The aforementioned feature prediction layer can refer to the model's output layer, which predicts dead zone compensation parameters based on the fused feature set. The feature prediction layer utilizes the fused parameter features received from the feature fusion layer, along with trained weights and bias parameters, to perform the final prediction operation. The feature prediction layer typically comprises multiple layers of fully connected neurons and may also include activation functions such as the Rectified Linear Unit (ReLU), the Sigmoid Function (Sigmoid), or the Hyperbolic Tangent (Tanh) to introduce non-linearity, enabling the model to learn the complex mapping relationship between input features and output parameters.

[0096] The aforementioned motor status parameters can include key information monitored during motor operation, such as motor current and motor speed. These parameters directly reflect the motor's real-time operating status and are crucial inputs for predicting dead-zone compensation parameters.

[0097] The aforementioned fused feature parameters refer to the result of combining the first and second parameter features after processing by the feature fusion layer. The fused feature parameters are a feature set that integrates motor state and operating condition information, reflecting the motor's behavior patterns under specific conditions. This provides richer input to the feature prediction layer, thereby improving the accuracy and reliability of dead-zone compensation parameter prediction.

[0098] In one optional embodiment, firstly, the monitored real-time current, current direction, rotational speed, and index of the motor are combined and input into the parameter prediction model. The feature extraction layer can analyze signal features using preprocessing algorithms such as wavelet transform or Fourier transform, or automatically learn these features using convolutional or fully connected layers in a neural network, outputting first parameter features and second parameter features. Next, the feature fusion layer receives the first and second parameter features obtained from the feature extraction layer and integrates them into a single feature identifier using methods such as concatenation, weighted summation, or attention mechanisms, outputting fused feature parameters. Then, the fused feature parameters are input into the feature prediction layer to obtain the output target dead zone compensation parameters.

[0099] In the above method, the parameter prediction model can dynamically predict and adjust the dead zone compensation parameters based on the real-time operating status of the motor, thereby improving the control effect of the drive inverter bridge, reducing voltage distortion, and improving the smoothness and efficiency of motor operation.

[0100] In this embodiment of the application, the method further includes: determining the current direction of the motor current based on the motor current and the motor rotation angle, including: determining the current vector angle of the motor current based on the motor current and the motor rotation angle; and determining the current direction based on the relative position of the current vector angle and the quadrant in which the motor rotation angle is located.

[0101] The aforementioned current vector angle refers to the angular position of the motor current in a rotating coordinate system. In motor control, the three-phase components of the motor current are typically transformed into a rotating coordinate system (such as the dq coordinate system) to better reflect the electromagnetic state of the motor and control requirements. The current vector angle can provide information about the actual position of the motor current in the motor windings, and it can be obtained through mathematical transformations.

[0102] The quadrants mentioned above can refer to four regions in a Cartesian coordinate system, each defined by the sign of its axis. For example, in the dq coordinate system, the d-axis represents the direct-axis current, which is aligned with the direction of the motor rotor flux linkage, while the q-axis represents the quadrature-axis current, which is perpendicular to the flux linkage direction.

[0103] The aforementioned relative position refers to the spatial relationship between the motor current vector angle and the quadrant containing the motor rotation angle. Relative position can be used to determine the direction of the current, i.e., whether the current flows in the direction of motor rotation or in the opposite direction.

[0104] In one optional embodiment, the motor current and rotation angle are monitored in real time by sensors to obtain current and rotation angle data during motor operation. The monitored three-phase currents are transformed into the dq coordinate system using either the Clarke Transform or the Park Transform to obtain Id and Iq components. Then, based on the Id and Iq components, the current vector angle θ is calculated using inverse trigonometric functions, and the quadrant of the dq coordinate system where the motor rotation angle lies is determined according to the motor rotation angle. The relative position of the current vector angle and the quadrant of the motor rotation angle is compared, and the current direction is determined based on quadrant rules. If the current vector angle is in the same direction as the motor rotation angle and lies in the same or adjacent quadrants, the current direction is in the same direction as the motor rotation direction; otherwise, the current direction is opposite to the motor rotation direction.

[0105] In the above method, by introducing motor rotation angle information and current vector angle for comprehensive judgment, the change of current direction can be tracked more accurately. Even in the process of rapidly changing current direction, the timely adjustment of the control strategy can be ensured, thereby improving the accuracy and response speed of current control.

[0106] In this embodiment of the application, the method further includes: the motor current is a three-phase current, and the current vector angle of the motor current is determined according to the motor current and the motor rotation speed, including: performing phase conversion on the three-phase current based on a preset phase coordinate system to obtain two-phase current; and determining the current vector angle based on the two-phase current and the motor rotation speed.

[0107] The aforementioned three-phase current refers to a current flowing in three AC circuits with a phase difference of 120 degrees. Three-phase current ensures a uniform distribution of electromagnetic force in the motor, thereby avoiding torque fluctuations and efficiency losses that occur during single-phase operation.

[0108] A preset phase coordinate system refers to a system in which the three-phase current of a motor is converted to a specific phase coordinate system for easier analysis and control. The two most commonly used phase coordinate systems are the stationary αβ coordinate system and the synchronously rotating dq coordinate system (direct axis d and quadrature axis q).

[0109] The two-phase currents mentioned above can refer to the current components obtained after transformation in a preset phase coordinate system, such as the result of three-phase current transformation in the αβ coordinate system. )and( In the dq coordinate system, it is the direct-axis current. ) and quadrature axis current ( In the αβ coordinate system transformation, the Clarke transform is typically used to convert the three-phase current into current components in the two-phase stationary coordinate system αβ. When transforming to the dq coordinate system, the current in the αβ coordinate system is first obtained through the Clarke transform, and then the Park transform is used to transform the current in the αβ coordinate system to the synchronous rotating coordinate system dq, obtaining the direct-axis current and the quadrature-axis current.

[0110] In an optional embodiment, when the preset phase coordinate system is the dq coordinate system, the three-phase current is first converted into a two-phase current in the stationary coordinate system using the Clarke transformation. , Then, the Park transformation was used to convert the currents in these two static coordinate systems to direct-axis currents in the rotating coordinate system. ) and quadrature axis current ( Next, based on and Determine the vector angle of the motor current in the dq coordinate system. Furthermore, based on the rotational speed, the duty cycle of the PWM signal can be adjusted in real time to ensure optimal control of the inverter bridge.

[0111] In another alternative embodiment, when the preset phase coordinate system is the αβ coordinate system, firstly, the Clarke transformation is used to convert the three-phase currents ( , , Transforming to the stationary αβ coordinate system, we obtain the two-phase currents ( , ). In obtaining and( After that, the arctangent function (arctan2) can be used to calculate the current vector angle.

[0112] In the above method, the calculation of the current vector angle provides the precise position of the motor current in the rotating coordinate system, which helps to achieve accurate current control and torque control. Furthermore, by using two-phase current instead of directly processing three-phase current, the control algorithm is simplified without sacrificing control accuracy, thus improving the system's response speed and control efficiency.

[0113] Figure 2 This is a flowchart of an optional motor drive control method according to an embodiment of this application. The following is in conjunction with... Figure 2 A preferred embodiment of this application will be described, such as... Figure 2 As shown, the motor drive control method flow is as follows:

[0114] Step S202: Divide the maximum current and maximum speed into 10 equal parts to create a two-dimensional table with current and speed as independent variables and compensation duty cycle as dependent variable.

[0115] Figure 3 This is a schematic diagram of an optional two-dimensional table according to an embodiment of this application. For example... Figure 3 As shown, the example two-dimensional table includes the following: the independent variables of the two-dimensional table are current and speed. Each row in the table represents a specific current value, and each column represents a specific rotational speed value. The units for the rows and columns are current percentage (%Imax) and voltage percentage (%Vmax), respectively. %Imax represents the ratio of the current value to the maximum current, expressed as a percentage. Similarly, %Vmax represents the ratio of the current voltage value to the maximum current. For example, if the current motor current is 30% of Imax, the corresponding cell in the table is 30%Imax. The cells (intersections) in the table represent the motor operating conditions under a specific combination of current and speed. The row values ​​in the table can include 10%Imax, 20%Imax, 30%Imax, 40%Imax, 50%Imax, 60%Imax, 70%Imax, 80%Imax, 90%Imax, and 100%Imax, while the column values ​​can include 10%Vmax, 20%Vmax, 30%Vmax, 40%Vmax, 50%Vmax, 60%Vmax, 70%Vmax, 80%Vmax, 90%Vmax, and 100%Vmax. Each cell stores the appropriate compensation duty cycle corresponding to that operating condition. The compensation duty cycle value is selected and recorded in the table after testing the motor under various operating conditions, observing and analyzing the PWM signal compensation effect. In the two-dimensional table, both current and speed values ​​are positive. When the motor operates under a specific condition, the monitoring module records its current and speed values ​​in real time, then converts them into quantized levels in the table for use in calculating the compensation duty cycle based on the two-dimensional table lookup or interpolation.

[0116] Step S204: Run the motor according to the different speed conditions set in the table, test the different current step response effects in the table, find the appropriate compensation amount for each working condition and fill it into the table.

[0117] Step S206: Repeat the test until all current-speed combinations have been tested.

[0118] Step S208: Based on the preset table of motor current and speed index, linear interpolation is used to obtain the compensation duty cycle, and the pulse width is adjusted in combination with the current direction to adjust the inverter bridge control.

[0119] The table data is incorporated into the program code. The program indexes the table based on the target current and current speed, using the absolute values ​​of current and speed for indexing. Values ​​between table data points are linearly interpolated using data from the four adjacent positions (up, down, left, and right) to obtain the current compensation duty cycle. The final three-phase compensation value is then determined based on the current direction and added to the duty cycle calculated by the loop before being output.

[0120] Figure 4 This is a schematic diagram comparing the real-time adjusted compensation value with the fixed compensation value according to an embodiment of this application. Figure 4 This paper demonstrates a comparison of the effects of a fixed compensation value in simulation and a real-time adjusted compensation value according to a preferred embodiment of this application at a certain speed. Figure 4 As shown, the horizontal axis represents time points in seconds, with values ​​including 0.03, 0.035, 0.04, 0.045, 0.05, 0.055, and 0.06, representing the duration of the entire experimental cycle and reflecting the time history of the current response. The vertical axis represents the motor current value, i.e., the magnitude of the current flowing through the motor windings, in amperes, with values ​​including -3, -2, -1, 0, 1, 2, and 3, representing the current value over the entire experimental cycle and reflecting the changes in the motor current over time. The fixed compensation value curve represents the current response curve when the same dead-zone compensation parameter remains constant throughout the motor's operation. This curve exhibits significant current fluctuations because the dead-zone compensation parameter is not adapted to the real-time changing motor operating conditions, resulting in significant voltage distortion and consequently causing sudden jumps or overshoots in the motor current. The curve in this embodiment represents the current response curve obtained using the method of dynamically adjusting the dead-zone compensation parameter based on the motor current, current direction, and rotational speed as described in this embodiment. Compared to the fixed compensation value curve, the curve in this embodiment shows a smoother and more stable current response. Especially during the current direction conversion process, due to the adoption of an adaptive compensation strategy, voltage distortion is effectively suppressed, current fluctuations are reduced, and the smoothness of motor operation and control accuracy are ensured.

[0121] Depend on Figure 4 A comparison of the effects of the fixed compensation value and that of this application shows that the compensation method of this application not only ensures a fast response but also reduces the overshoot, resulting in better performance.

[0122] The following is combined Figure 5 , Figure 6 and Figure 7 A preferred embodiment of this application will be described. Figure 5 This is a schematic diagram illustrating the effect of speed on dead zone compensation according to an embodiment of this application. Figure 6 This is a schematic diagram of the current response of a motor in a stationary state according to an embodiment of this application. Figure 7This is a schematic diagram of the current response of a motor in a rotating state according to an embodiment of this application. Figure 5 , Figure 6 and Figure 7 As shown, the influence of speed on the dead zone compensation effect is analyzed.

[0123] Dead time primarily affects the current commutation process at zero crossing. If the current can be guaranteed to remain in the same direction without commutation, then the dead time can be ignored. Current ripple will have an impact during the commutation process, and speed will affect the ripple, thus affecting the dead time compensation effect. Figure 5 The effect of speed on dead zone compensation is shown below. Figure 5 As shown, the horizontal axis represents time in seconds, with values ​​including 0.015, 0.02, 0.025, 0.03, 0.035, 0.04, 0.045, and 0.05. This represents the motor's response time after receiving a control signal, covering the entire test cycle. The horizontal axis also represents the motor's Q-axis current in amperes, with values ​​including -2, -1, 0, 1, 2, and 3. This represents the current component perpendicular to the flux linkage direction. The figure includes two curves: the quadrature-axis current command response when stationary and the quadrature-axis current command response when rotating. These curves demonstrate how the rise time and overshoot of the current response change with increasing motor speed under the same dead-zone compensation duty cycle. A comparison of the Q-axis current response with the same compensation duty cycle shows that the same compensation value has different effects when stationary and rotating; overcompensation during rotation exacerbates the overshoot.

[0124] Figure 6 The current response of the motor when it is stationary is shown below. Figure 6 As shown, the horizontal axis represents time in seconds, with values ​​including 0.0299, 0.03, 0.0301, 0.0302, 0.0303, and 0.0304, representing a complete observation cycle or the time until the current stabilizes. The values ​​on the left side of the vertical axis represent the switching status of the A-phase arm, with 1 for on and 0 for off. The values ​​on the right side of the vertical axis represent the A-phase current of the motor, in amperes, with values ​​including 2, 0, and -2, reflecting the change of the A-phase current over time when the motor is stationary and the current crosses zero for commutation. The curve represents the dynamic response of the A-phase current when the motor is stationary. Because the motor is stationary, there is almost no ripple when the A-phase current crosses zero, therefore, there is no repeated zero-crossing phenomenon.

[0125] and Figure 7 This demonstrates the current response of the motor while it is rotating. Figure 6Similarly, the horizontal axis represents time in seconds, with values ​​including 0.0298, 0.0299, 0.03, 0.0301, 0.0302, 0.0303, 0.0304, and 0.0305, representing a complete observation cycle or the time until the current stabilizes. The values ​​on the left side of the vertical axis represent the switching status of the A-phase arm, with 1 for on and 0 for off. The values ​​on the right side of the vertical axis represent the A-phase current of the motor, in amperes, with values ​​including 2, 1, 0, -2, and -1, used to represent the dynamic response of the A-phase current when the motor is rotating. Because the motor is rotating, there is significant ripple in the current when it crosses zero and reverses, causing the current to repeatedly cross zero within several consecutive switching cycles, and the current direction differs when the upper and lower transistors operate. This phenomenon indicates that increasing the motor speed alters the effectiveness of dead-zone compensation, and a fixed compensation amount can lead to overcompensation at high speeds.

[0126] According to an embodiment of this application, an apparatus embodiment for a motor drive control method is provided. It should be noted that the apparatus can be used to execute the above-described motor drive control method. Figure 8 This is a schematic diagram of a motor drive control device according to an embodiment of this application, such as... Figure 8 As shown, the device includes: a monitoring module 802, a determination module 804, a compensation module 806, and an adjustment module 808.

[0127] The system includes a monitoring module for monitoring motor current, rotation angle, and speed, with the motor connected to a drive inverter bridge that controls the on / off state of internal switching transistors to drive the motor. A determination module determines the direction of the motor current based on the current and rotation angle, indicating the direction of current flow through the motor windings. A compensation module determines the target dead-zone compensation parameters for the drive inverter bridge based on the current, direction, and speed, compensating for voltage distortion caused by the dead-zone effect during current redirection. An adjustment module adjusts the duty cycle of the corresponding pulse width modulation signal based on the target dead-zone compensation parameters to perform closed-loop control of the drive inverter bridge.

[0128] Optionally, the determining module can also be used to determine the motor current parameters based on the motor current and current direction; determine the index combination based on the current parameters and the motor rotation speed, wherein the index combination is used to represent the identification information of the positioning target dead zone compensation parameters; determine the target dead zone compensation parameters based on the index combination and the target table, or determine the target dead zone compensation parameters based on the index combination and the parameter prediction model, wherein the target table stores the correspondence between different index combinations and different dead zone compensation parameters.

[0129] Optionally, the compensation module can also be used to index the target table based on the index combination to obtain the index result, wherein the index result is used to indicate whether there is an index combination in the target table; if the index result indicates that there is an index combination in the target table, the target dead zone compensation parameter corresponding to the index combination is determined from the target table; if the index result indicates that there is no index combination in the target table, multiple adjacent index combinations adjacent to the index combination are determined from the target table, and the target dead zone compensation parameter is determined based on the dead zone compensation parameters corresponding to the multiple adjacent index combinations.

[0130] Optionally, the compensation module can also be used to interpolate the dead zone compensation parameters corresponding to multiple adjacent index combinations to obtain the target dead zone compensation parameters.

[0131] Optionally, the determination module can also be used in a parameter prediction model including a feature extraction layer, a feature fusion layer, and a feature prediction layer to obtain the motor state parameters of the motor; the feature extraction layer extracts features from the motor state parameters and index combinations respectively to obtain first parameter features and second parameter features, wherein the first parameter features are parameter features related to the dead zone effect in the motor state parameters, and the second parameter features are parameter features corresponding to the index combinations; the feature fusion layer fuses the first parameter features and the second parameter features to obtain fused parameter features; and the feature prediction layer predicts the fused parameter features to obtain the target dead zone compensation parameters.

[0132] Optionally, the determining module can also be used to determine the current vector angle of the motor current based on the motor current and the motor rotation angle; and to determine the current direction based on the relative position of the current vector angle and the quadrant in which the motor rotation angle is located.

[0133] Optionally, the determining module can also be used to perform phase conversion of the three-phase current based on a preset phase coordinate system to obtain two-phase current; and to determine the current vector angle based on the two-phase current and the motor rotation speed.

[0134] Embodiments of this application also provide a motor, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0135] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0136] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0137] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0138] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of this application.

[0139] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0140] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0141] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0142] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0143] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0144] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0145] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A motor drive control method, characterized in that, include: The motor current, motor rotation angle, and motor rotation speed of the motor are monitored. The motor is connected to a drive inverter bridge, which is used to drive the motor to run by controlling the on or off state of the internal switching transistors. The direction of the motor current is determined based on the motor current and the motor rotation angle, wherein the current direction is used to indicate the direction in which the motor current flows through the motor windings in the motor; Based on the motor current, current direction and motor rotation speed, the target dead zone compensation parameter of the drive inverter bridge is determined, wherein the target dead zone compensation parameter is used to compensate for the voltage distortion caused by the dead zone effect during the current reversal process of the drive inverter bridge; The duty cycle of the corresponding pulse width modulation signal of the motor is adjusted based on the target dead zone compensation parameter in order to perform closed-loop control of the drive inverter bridge. The target dead-time compensation parameters for the drive inverter bridge are determined based on the motor current, current direction, and motor rotation speed, including: Based on the motor current and the current direction, determine the current parameters of the motor; Based on the current parameters and the motor rotation speed, an index combination is determined, wherein the index combination is used to represent the identification information for locating the target dead zone compensation parameters; Based on the index combination and the target table, the target dead zone compensation parameter is determined, or based on the index combination and the parameter prediction model, the target dead zone compensation parameter is determined, wherein the target table stores the correspondence between different index combinations and different dead zone compensation parameters; The target dead zone compensation parameters are determined based on the index combination and the target table, including: The target table is indexed based on the index combination to obtain an index result, wherein the index result is used to indicate whether the index combination exists in the target table; If the index result indicates that the target table contains the index combination, determine the target dead zone compensation parameter corresponding to the index combination from the target table; If the index result indicates that the target table does not contain the index combination, then multiple adjacent index combinations adjacent to the index combination are determined from the target table, and the target dead zone compensation parameter is determined based on the dead zone compensation parameter corresponding to the multiple adjacent index combinations.

2. The method according to claim 1, characterized in that, Based on the dead zone compensation parameters corresponding to the multiple adjacent index combinations, the target dead zone compensation parameters are determined, including: The dead zone compensation parameters corresponding to the multiple adjacent index combinations are interpolated to obtain the target dead zone compensation parameters.

3. The method according to claim 1, characterized in that, The parameter prediction model includes a feature extraction layer, a feature fusion layer, and a feature prediction layer. Based on the index combination and the parameter prediction model, the target dead zone compensation parameters are determined, including: Obtain the motor status parameters of the motor; The feature extraction layer is used to extract features from the motor state parameters and the index combination to obtain a first parameter feature and a second parameter feature. The first parameter feature is the parameter feature of the motor state parameters that is associated with the dead zone effect, and the second parameter feature is the parameter feature corresponding to the index combination. The first parameter feature and the second parameter feature are fused using the feature fusion layer to obtain the fused parameter feature; The target dead zone compensation parameters are obtained by predicting the fusion parameter features using the feature prediction layer.

4. The method according to any one of claims 1-3, characterized in that, Determining the direction of the motor current based on the motor current and the motor rotation angle includes: Determine the current vector angle of the motor current based on the motor current and the motor rotation angle; The direction of the current is determined based on the relative position of the current vector angle and the quadrant in which the motor rotation angle is located.

5. The method according to claim 4, characterized in that, The motor current is a three-phase current. The current vector angle of the motor current is determined based on the motor current and the motor's rotational speed, including: The three-phase currents are phase-converted based on a preset phase coordinate system to obtain two-phase currents; The current vector angle is determined based on the two-phase current and the motor rotation speed.

6. An electric motor, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 1 to 5.

8. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 5.

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