Radial vector control method and system of multi-element motor

Abstract

The invention relates to the field of motor radial vector control, provides a radial vector control method and system of a multi-element motor, and aims to solve the problem of poor radial vector control effect of the multi-element motor in the prior art. The method comprises the following steps: determining a current of a multi-element motor in a three-phase static coordinate system, converting a coordinate into a component under a two-phase static coordinate system, and converting the component into a two-phase rotating coordinate system synchronously rotating with a rotor flux linkage to obtain excitation and torque current components; generating a first control component according to the excitation current component and a first preset reference value by using a proportional-integral controller, and generating a second control component according to the motor torque, the torque current component and a second preset reference value; and obtaining a reference voltage of a three-phase static coordinate system through inverse coordinate transformation, and driving an inverter to output a corresponding three-phase voltage waveform so as to realize effective control of the motor. According to the technical scheme provided by the invention, accurate coordinate transformation and control are carried out on the motor current, so that efficient and accurate motor control performance improvement is realized.

Description

Technical Field

[0001] This application relates to the technical field of motor radial vector control, and particularly to a radial vector control method and system for a multi-motor. Background Art

[0002] With the rapid development of industrial automation and the new energy field, higher requirements are put forward for the control accuracy, efficiency, and dynamic response speed of motors. Especially in high-end application fields such as electric vehicles, precision CNC machine tools, and aerospace, motors are required to operate efficiently and smoothly within a wide speed regulation range and have fast response capabilities to meet complex operation requirements. Therefore, for multi-motors, their radial vector control methods not only need to improve the output performance of the motors but also ensure the stability and reliability of the system while reducing energy consumption.

[0003] Currently, a widely used solution is an improved vector control system based on field-oriented control. This system realizes effective control of the motor by real-time detecting the current and voltage parameters of the motor and combining with an accurate mathematical model to estimate the rotor flux position. This solution utilizes advanced digital signal processors or microcontrollers, cooperating with high-precision sensors for real-time data acquisition and processing, enabling the motor to maintain an optimal working state under different load conditions.

[0004] Although the improved vector control system based on field-oriented control performs well in many aspects, it is not perfect. Due to relying on high-precision sensors to obtain the internal state information of the motor, this not only increases the hardware cost of the system, but also the accuracy and stability of the sensors directly affect the performance of the entire control system. Summary of the Invention

[0005] This application provides a radial vector control method and system for a multi-motor to solve the problem of poor radial vector control effect of multi-motors in the prior art.

[0006] In a first aspect, this application provides a radial vector control method for a multi-motor, including: Determine the three-phase current of the multi-motor in the three-phase stationary coordinate system; Through a coordinate transformation method, transform the three-phase current in the three-phase stationary coordinate system into current components in the two-phase stationary coordinate system, and transform the current components into excitation current components and torque current components in the two-phase rotating coordinate system synchronized with the rotor flux; In the two-phase rotating coordinate system, through a proportional-integral controller, generate a first control component according to the excitation current component and the corresponding first preset reference value; generate a second control component according to the obtained motor torque, the torque current component, and the corresponding second preset reference value; Through the inverse coordinate transformation method, the first control component and the second control voltage in the two-phase rotating coordinate system are converted into the reference voltage in the three-phase stationary coordinate system, so as to drive the inverter to output the corresponding three-phase voltage waveform through the reference voltage, and realize the radial vector of the multi-source motor.

[0007] Optionally, it further includes: Obtain the position information of the rotor flux linkage; Combined with the obtained electrical parameters of the multi-source motor and the pre-established back electromotive force observation model, determine the angle of the rotor flux linkage; Wherein, the back electromotive force observation model extracts the back electromotive force components in the two-phase stationary coordinate system, and calculates the angle of the rotor flux linkage based on the orthogonal relationship of the back electromotive force components; the exciting current component and the torque current component are determined according to the angle of the rotor flux linkage.

[0008] Optionally, it further includes: According to the operating conditions and control objectives of the multi-source motor, adjust the first preset parameter value corresponding to the exciting current component and the second preset reference value corresponding to the torque current component; Input the adjusted first preset reference value and second preset reference value into the proportional-integral controller to regenerate the first control component and the second control component, so as to adjust the radial force application point of the rotor flux linkage; Wherein, the process of adjusting the first preset parameter value corresponding to the exciting current component and the second preset reference value corresponding to the torque current component includes: In the starting stage, when the multi-source motor is in the inner ring operation mode, reduce the first preset reference value and increase the second preset reference value to reduce the torque output and increase the speed; or, when the multi-source motor is in the outer ring operation mode, increase the first preset reference value and reduce the second preset reference value to increase the torque output and reduce the current consumption.

[0009] Optionally, it further includes: Collect the current fluctuation components corresponding to the double three-phase windings of the multi-source motor and the magnetic field interaction parameters, and construct a multi-dimensional relationship table, which is used to describe the interaction characteristics between the double three-phase windings; Based on the magnetic field detection sensor array, detect the radial position offset of the rotor magnetic field with a preset accuracy, and synchronously measure the magnetic field distribution uniformity index to generate a magnetic field adjustment signal; Input the multi-dimensional relationship table and the magnetic field adjustment signal into the back electromotive force calculation model to correct the calculation deviation of the angle corresponding to the rotor magnetic field, and update the independent adjustment weights of the exciting current component and the torque current component.

[0010] Optionally, it further includes: Monitoring the drift amount corresponding to the electrical parameters of the multi-source motor through a sliding mode observer, and dynamically canceling the mutual interference between the dual three-phase windings by combining an interference cancellation algorithm to obtain an interference suppression result; Inputting the drift amount and the interference suppression result into the proportional-integral controller to adjust the generation logic of the first control component and the second control component; Based on the adjusted first control component and second control component, correcting the voltage output rule of the inverter to ensure that the output of the three-phase voltage waveform matches the co-driving requirement of the multi-source motor.

[0011] Optionally, the method of converting the three-phase current in the three-phase stationary coordinate system into current components in the two-phase stationary coordinate system and then converting the current components into the excitation current component and torque current component in the two-phase rotating coordinate system synchronized with the rotor flux linkage includes: Mapping the three-phase current in the three-phase stationary coordinate system to the two-phase stationary coordinate system through a linear projection transformation to obtain a first-axis current component and a second-axis current component, where the first-axis current component is composed of a weighted combination of the three-phase currents, and the second-axis current component is composed of an orthogonal projection of the three-phase currents; Based on the angle of the rotor flux linkage, performing a rotation transformation on the first-axis current component and the second-axis current component in the two-phase stationary coordinate system to obtain an excitation current component and a torque current component, where the excitation current component is in the same direction as the rotor flux linkage, and the torque current component is orthogonal to the direction of the rotor flux linkage.

[0012] Optionally, in the two-phase rotating coordinate system, generating a first control component by a proportional-integral controller according to the excitation current component and a corresponding first preset reference value, includes: In the two-phase rotating coordinate system, calculating the superposition result of a first proportional adjustment term and a first integral adjustment term by a proportional-integral controller based on the difference between the actual measured value of the excitation current component and the first preset reference value, where the weight of the first proportional adjustment term is determined by a preset proportional coefficient of the d-axis current controller in the two-phase rotating coordinate system, and the weight of the first integral adjustment term is determined by a preset integral coefficient of the d-axis current controller; Applying a limit constraint to the accumulation process of the first integral adjustment term to limit the growth range of the integral accumulation value, and mapping the superposition result of the proportional adjustment term and the integral adjustment term to the first control component in the two-phase rotating coordinate system for adjusting the voltage output of the inverter to make the actual measured value of the excitation current component approach the first preset reference value.

[0013] Optionally, generating a second control component according to the obtained motor torque, the torque current component, and the corresponding second preset reference value includes: Based on the difference between the actual measured value of the torque current component and the second preset reference value, a proportional-integral controller generates a combined result of a second proportional adjustment term and a second integral adjustment term. Among them, the weight of the second proportional adjustment term is determined by the preset proportional coefficient of the q-axis current controller in the two-phase rotating coordinate system, and the weight of the integral adjustment term is determined by the preset integral coefficient of the q-axis current controller; Apply a dynamic amplitude limiting constraint to the cumulative process of the second integral adjustment term to limit the growth range of the integral cumulative value, and map the combined result of the second proportional adjustment term and the second integral adjustment term to the second control component in the two-phase rotating coordinate system, which is used to adjust the voltage output of the inverter to make the actual value of the torque current component approach the second preset reference value.

[0014] Optionally, converting the first control component and the second control voltage in the two-phase rotating coordinate system into a reference voltage in the three-phase stationary coordinate system through an inverse coordinate transformation method, so as to drive the inverter to output a corresponding three-phase voltage waveform through the reference voltage, includes: Based on the angle of the rotor magnetic flux, perform an inverse rotation transformation on the first control component and the second control voltage in the two-phase rotating coordinate system to generate orthogonal voltage components in the two-phase stationary coordinate system; Map the orthogonal voltage components in the two-phase stationary coordinate system to the three-phase stationary coordinate system through a phase expansion transformation to obtain three-phase voltage components. Among them, the first-phase voltage component in the three-phase voltage components is consistent with the first-axis component of the orthogonal voltage component, and the second-phase voltage component and the third-phase voltage component in the three-phase voltage components are composed of a linear combination of the first-axis and second-axis components of the orthogonal voltage component; Use the three-phase voltage components in the three-phase stationary coordinate system as the reference voltage to drive the inverter to output a corresponding three-phase voltage waveform.

[0015] In a second aspect, the present application provides a radial vector control system for a multi-motor, including: A determination module for determining the three-phase current of the multi-motor in the three-phase stationary coordinate system; A conversion module for converting the three-phase current in the three-phase stationary coordinate system into current components in the two-phase stationary coordinate system through a coordinate conversion method, and converting the current components into field current components and torque current components in the two-phase rotating coordinate system that synchronously rotate with the rotor magnetic flux; A generating module, configured to generate a first control component according to the exciting current component and a corresponding first preset reference value through a proportional-integral controller in the two-phase rotating coordinate system; and generate a second control component according to the obtained motor torque, the torque current component and a corresponding second preset reference value. The conversion module is further configured to convert the first control component and the second control voltage in the two-phase rotating coordinate system into a reference voltage in the three-phase stationary coordinate system through an inverse coordinate transformation method, so as to drive an inverter to output corresponding three-phase voltages through the reference voltage, thereby realizing the radial vector of the multi-motor.

[0016] Advantages of the present application: By determining the three-phase currents of the multi-motor in the three-phase stationary coordinate system, the present application ensures the acquisition of basic data on the operating state of the motor, providing necessary inputs for subsequent precise control. Accurately obtaining the three-phase currents is a prerequisite for efficient motor control. Through a coordinate transformation method, the three-phase currents in the three-phase stationary coordinate system are converted into current components in the two-phase stationary coordinate system, and the current components are further converted into an exciting current component and a torque current component in the two-phase rotating coordinate system that synchronously rotates with the rotor flux linkage, realizing the conversion from a complex and difficult-to-directly-control three-phase AC system to a more intuitive and easy-to-control two-phase DC system, simplifying the control logic and improving the control accuracy. In the two-phase rotating coordinate system, a first control component is generated according to the exciting current component and a corresponding first preset reference value through a proportional-integral controller; a second control component is generated according to the obtained motor torque, the torque current component and a corresponding second preset reference value. By using a PI controller to adjust the exciting and torque current components respectively, the motor magnetic field and torque output can be independently and accurately controlled, thereby optimizing the motor performance and response speed. Through an inverse coordinate transformation method, the first control component and the second control voltage in the two-phase rotating coordinate system are converted into a reference voltage in the three-phase stationary coordinate system, so as to drive an inverter to output a corresponding three-phase voltage waveform through the reference voltage, realizing the radial vector of the multi-motor. This step remaps the control instruction back to the three-phase stationary coordinate system, generating an actual control signal for driving the motor, ensuring that the motor operates according to the expected parameters.

[0017] The method further includes obtaining the position information of the rotor flux linkage, and determining the angle of the rotor flux linkage in combination with the electrical parameters of the motor and a pre-established back electromotive force observation model. By extracting the back electromotive force components in the two-phase stationary coordinate system and calculating the rotor flux linkage angle based on their orthogonal relationship, the exciting and torque current components are determined. This method not only improves the understanding and prediction ability of the internal dynamic characteristics of the motor, but also significantly enhances the robustness and adaptability of the control system, especially in dealing with motor parameter changes and external disturbances, enabling the motor to operate stably and efficiently under various working conditions.

[0018] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0020] Figure 1 A flowchart showing a radial vector control method for a multi - motor provided by the present application is shown; Figure 2 A schematic structural diagram of a radial vector control system for a multi - motor provided by the present application is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application.

[0022] In some processes described in the specification, claims and the above - mentioned drawings of the present application, there are multiple operations that appear in a specific order. However, it should be clearly understood that these operations may not be executed in the order in which they appear in this text or may be executed in parallel. The operation numbers such as 101, 102, etc. are only used to distinguish different operations, and the numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions such as "first", "second", etc. in this text are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, nor do they limit that "first" and "second" are of different types.

[0023] Considering that in the current context of the growing demand for high - precision and high - efficiency motor control in fields such as industrial automation, electric vehicles, and renewable energy power generation systems, researchers are committed to developing a multi - motor control method that can provide precise and fast dynamic response. Based on this demand, the present application proposes a radial vector control scheme for multi - motors. First, researchers determine the three - phase currents of the multi - motor in the three - phase stationary coordinate system as the basic data source for control. Then, through a series of coordinate transformation techniques, these currents are transformed from the three - phase stationary coordinate system to the two - phase rotating coordinate system (dq coordinate system), thus simplifying the design of the control system and achieving independent control of the excitation and torque current components.

[0024] On this basis, a proportional-integral controller is used to generate control components for excitation and torque respectively according to preset reference values to ensure that the motor output meets expectations. Then, through inverse coordinate transformation, these control instructions are remapped back to the three-phase stationary coordinate system to form the reference voltage for driving the inverter, ultimately achieving effective control of the motor.

[0025] The entire R & D process reflects a series of steps from basic current measurement, coordinate transformation, formulation of precise control strategies to the final practical application, aiming to overcome problems such as poor adaptability to parameter changes and insufficient real-time performance in existing control methods to meet the high standards for motor performance in modern complex application scenarios.

[0026] The solution of this application is particularly suitable for motor drive systems that require high precision, fast dynamic response speed and high operating efficiency, and can be specifically applied to the following scenarios: Industrial automation equipment: In equipment such as precision machine tools and robots that require precise position control and fast response, the radial vector control of multi-motors can ensure that the actuator moves accurately along the predetermined trajectory.

[0027] Electric vehicles: Electric vehicle drive systems have high requirements for motor efficiency, dynamic performance and energy efficiency optimization. This control method can improve the response speed and torque output stability of the motor, thereby enhancing the overall performance of the vehicle.

[0028] Renewable energy generation systems: For example, the motor control in wind turbines and solar tracking systems needs to adjust the motor working state in real time according to environmental changes to optimize the energy collection efficiency. This method can achieve efficient energy conversion through precise control of the motor.

[0029] Next, the technical solutions in the embodiments of this application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts belong to the scope of protection of this application.

[0030] Figure 1 The flowchart of a radial vector control method for multi-motors provided for the embodiments of this application is as Figure 1 shown, and this method includes: 101. Determine the three-phase currents of the multi-motor in the three-phase stationary coordinate system; In this step, the three-phase stationary coordinate system (abc coordinate system) is a standard reference framework for describing electrical parameters such as phase currents and voltages in a three-phase AC motor. Among them, the phase A, phase B, and phase C currents are respectively expressed as , and (i.e., three-phase current), which represent the instantaneous current values in the three-phase windings of the motor.

[0031] In the embodiments of the present application, first, current sensors installed on the three-phase windings of the motor are used to monitor and collect the current data of each phase in real time. These current data contain key information about the operating state of the motor. Then, the collected original current signals are filtered to remove noise interference to ensure the accuracy of the data used for subsequent analysis. Finally, accurate three-phase current values , and are obtained as the basic inputs for the next coordinate transformation.

[0032] For example, in an electric vehicle drive system, in order to optimize the motor efficiency, it is first necessary to accurately obtain the current state of the motor under different driving conditions. The current changes in the three-phase windings of the motor are monitored in real time through high-precision current sensors, and the collected data is preprocessed using a digital filtering algorithm to obtain stable three-phase current values, providing a reliable basis for subsequent control strategies.

[0033] 102. By means of coordinate transformation, the three-phase current in the three-phase stationary coordinate system is converted into current components in the two-phase stationary coordinate system, and the current components are converted into the exciting current component and torque current component in the two-phase rotating coordinate system synchronized with the rotor magnetic flux; In this step, the Clark Transformation is used to convert the current in the three-phase stationary coordinate system into the two-phase stationary coordinate system (αβ coordinate system). The Park Transformation further converts the current in the αβ coordinate system into the exciting ( ) and torque ( ) current components in the dq coordinate system.

[0034] In the embodiments of the present application, first, the Clark transformation formula is used to calculate the current components and in the αβ coordinate system. Then, based on the rotor magnetic flux position information, the Park transformation formula is applied to convert and into and in the dq coordinate system. In this process, accurate rotor position information is required to ensure the accuracy of the coordinate transformation. Finally, the current components reflecting the magnetic field and torque characteristics of the motor are obtained.

[0035] For example, continuing with the above example of an electric vehicle, after obtaining stable three-phase currents, the Clarke and Park transformations are performed through an embedded control system to convert the three-phase currents into the excitation and torque current components in a two-phase rotating coordinate system that is easier to control. This step enables the control strategy to directly act on the magnetic field and torque of the motor, improving the system's response speed and control accuracy.

[0036] 103. In the two-phase rotating coordinate system, through a proportional-integral controller, a first control component is generated based on the excitation current component and the corresponding first preset reference value; a second control component is generated based on the obtained motor torque, the torque current component, and the corresponding second preset reference value. In this step, the proportional-integral (PI) controller is a commonly used feedback controller that adjusts the output according to the error between the set target value (reference value) and the actual measured value to achieve stable control. In this step, the first preset reference value is usually the specified target value of the excitation current, and the second preset reference value is the desired target value of the torque current.

[0037] In the embodiment of the present application, first, the excitation current component is compared with the first preset reference value, and the corrected excitation current control component is calculated through a PI controller. Similarly, the torque current component is compared with the second preset reference value to generate the corresponding torque current control component. These two control components are used to adjust the inverter output to ensure that the motor operates according to the predetermined performance indicators.

[0038] For example, in an electric vehicle driving scenario, when the driver accelerates or decelerates, the system dynamically adjusts the torque and magnetic field strength of the motor according to the vehicle's requirements. By continuously adjusting the excitation and torque current components through a PI controller, it is ensured that the motor can work efficiently under various working conditions while providing a smooth power output experience.

[0039] 104. Through an inverse coordinate transformation method, the first control component and the second control voltage in the two-phase rotating coordinate system are converted into a reference voltage in the three-phase stationary coordinate system to drive the inverter to output the corresponding three-phase voltage waveform through the reference voltage, realizing the radial vector of the multi-motor.

[0040] In this step, the Inverse Clark Transformation and the Inverse Park Transformation are used to convert the control signals in the dq coordinate system back into the three-phase reference voltage in the abc coordinate system for direct application to inverter control.

[0041] In the embodiments of the present application, first, the control components in the dq coordinate system are converted back to the voltage components in the αβ coordinate system using the inverse Park transformation formula. Subsequently, the inverse Clarke transformation is employed to convert the voltage components in the αβ coordinate system into the reference voltages in the three-phase stationary coordinate system. , , . Finally, these reference voltages are used as the input signals for the inverter to generate the corresponding three-phase voltage waveforms to drive the motor.

[0042] For example, in an electric vehicle application example, the field and torque current components optimized by the PI controller are converted into three-phase reference voltages and transmitted to the inverter. The inverter generates accurate three-phase voltage waveforms based on these reference voltages, driving the motor to operate according to the expected speed and torque requirements, thus achieving efficient and precise motor control.

[0043] The method proposed in the present application realizes the complete process from basic current data acquisition to efficient motor control through a series of operations such as accurate measurement of the three-phase current of the motor, coordinate transformation, PI control, and inverse coordinate transformation. This method not only improves the dynamic response speed and control accuracy of the motor but also enhances the adaptability and stability of the system under complex working conditions, and is particularly suitable for high-performance application scenarios such as electric vehicle drive.

[0044] To further improve the accuracy and robustness of motor control, in some embodiments, the method further includes: 201. Obtain the position information of the rotor flux linkage; In this step, the position information of the rotor flux linkage refers to the direction and position of the magnetic field inside the motor rotor. It is crucial for achieving accurate vector control because it directly affects the calculation of the field current component ( ) and the torque current component ( ).

[0045] In the embodiments of the present application, the position changes of the rotor flux linkage are monitored in real time through sensors (such as Hall effect sensors or resolvers) installed on the motor. These sensors can provide high-precision angle data, providing a basis for subsequent coordinate transformation and controller parameter adjustment. Finally, based on these angle data, the system can accurately determine the position of the rotor flux linkage.

[0046] 202. Combine the obtained electrical parameters of the multi-motor and the pre-established back electromotive force observation model to determine the angle of the rotor flux linkage; In this step, the back electromotive force (EMF) observation model is a mathematical model used to estimate the angle of the rotor flux based on the back EMF generated during motor operation. This model analyzes the back EMF components in the two-phase stationary coordinate system and uses their orthogonal characteristics to calculate the angle of the rotor flux. Specifically, it extracts the back EMF components in the two-phase stationary coordinate system and calculates the angle of the rotor flux based on the orthogonal relationship of the back EMF components.

[0047] Among them, the exciting current component and the torque current component are determined according to the angle of the rotor flux.

[0048] In the embodiment of the present application, first, the back EMF components in the αβ coordinate system are extracted from the motor operation process. and . Then, based on the orthogonal relationship between these back EMF components, a specific algorithm (such as Park transformation or extended Kalman filter) is used to calculate the angle of the rotor flux. . Finally, the calculated angle is used to correct the exciting current component and the torque current component to ensure that the motor operates according to the predetermined performance indicators.

[0049] As a specific implementation method, usually, the position information of the rotor can be obtained through an encoder, and then combined with the electrical parameters and mathematical model of the motor for calculation. A common method is to use an Extended Electromotive Force Observer (EEMF) to estimate the rotor flux angle, which specifically includes the following formulas:

[0050] Among them, represents the angle of the rotor flux (actually, it refers to the updated angle of the rotor flux, and the mentioned in the subsequent steps refers to the current angle of the rotor flux), which is a very important parameter in motor control because according to the position of the rotor flux, the exciting current and torque current of the motor can be controlled more precisely, thereby optimizing the motor performance; and respectively represent the estimated back EMF components in the two-phase stationary coordinate system (αβ coordinate system). These back EMFs are the voltage differences generated by the changes in the internal electromagnetic field during motor operation, and they reflect the state information of the internal magnetic field of the motor.

[0051] In this implementation method, first, the αβ components of the back EMF need to be extracted from the actual operating state of the motor ( and ). This typically involves measuring the motor voltage, current, and other electrical parameters and performing calculations using a mathematical model. An extended back-EMF observer is a commonly used tool that can estimate the back-EMF components based on the motor's electrical parameters and operating conditions.

[0052] Secondly, once the back-EMF components and are obtained, can be used to calculate the angle of the rotor flux linkage. The arctan2 function used here is a four-quadrant arctangent function that can accept two arguments (y, x) and return an angle value that indicates the direction of the point (x, y) relative to the positive x-axis in a two-dimensional plane. In this context, corresponds to the value in the y-axis direction, while corresponds to the value in the x-axis direction.

[0053] Finally, the calculated rotor flux linkage angle can be used to adjust the field current component ( ) and the torque current component ( ) in the motor control strategy to ensure that the motor operates according to the expected performance specifications. For example, in a vector control system, this angle information is used to perform the Park transformation and the inverse Park transformation to convert the control signals from the rotating coordinate system to the stationary coordinate system, or vice versa.

[0054] By this method, even without a direct position sensor, the angle of the rotor flux linkage can be estimated relatively accurately, and then efficient and precise motor control can be achieved. This is of great significance for improving the motor efficiency, response speed, and the overall robustness of the system.

[0055] The following is a specific example for steps 201 - 202: For example, in an electric vehicle drive system, to optimize the motor efficiency and response speed, it is first necessary to accurately obtain the position information of the motor rotor flux linkage. The rotor position is monitored in real time by a resolver installed on the motor and converted into a digital signal for the control system to process. Then, based on the collected rotor position data and the motor's electrical parameters, the system calculates the angle of the rotor flux linkage using a preset back-EMF observation model. In this process, the system also extracts the back-EMF components in the αβ coordinate system and applies an extended Kalman filter for precise angle calculation. Based on this angle information, the system further adjusts the field and torque current components, thus achieving efficient and precise control of the motor. Throughout the driving process, whether accelerating, decelerating, or driving at a constant speed, the motor can maintain an optimal working state, significantly improving the vehicle's power performance and energy efficiency ratio.

[0056] By introducing a method of obtaining rotor flux position information and combining it with the back-EMF observation model, this application not only improves the accuracy and robustness of the motor control system, but also enhances the system's adaptability to motor parameter changes and external disturbances. This method enables the motor to operate stably and efficiently under various working conditions, and is particularly suitable for application scenarios with high-performance requirements, such as electric vehicle drive systems. It effectively solves the problems existing in traditional control methods, such as insufficient control accuracy and slow dynamic response, and greatly improves the performance of the overall system.

[0057] In order to further improve the flexibility and adaptability of motor control, in some embodiments, the method further includes: 301. Adjust the first preset parameter value corresponding to the excitation current component and the second preset reference value corresponding to the torque current component according to the operating conditions and control objectives of the multi-motor; In this step, the first preset parameter value refers to the target set value for controlling the motor magnetic field strength (i.e., the excitation current component ), and the second preset reference value is the target set value for controlling the motor torque output (i.e., the torque current component ). These parameters are dynamically adjusted according to the specific operating conditions and control objectives of the motor.

[0058] Among them, the process of adjusting the first preset parameter value corresponding to the excitation current component and the second preset reference value corresponding to the torque current component includes: in the startup phase, when the multi-motor is in the inner ring operation mode, reduce the first preset reference value and increase the second preset reference value to reduce the torque output and increase the speed; or, when the multi-motor is in the outer ring operation mode, increase the first preset reference value and reduce the second preset reference value to increase the torque output and reduce the current consumption.

[0059] In the embodiments of this application, the system first monitors the current operating state of the motor (such as speed, load, etc.) and combines it with the preset control objectives (such as energy-saving mode, fast response mode, etc.). Based on this information, it is judged through algorithm logic whether the motor is in the inner ring operation mode or the outer ring operation mode. In the startup phase or under light load conditions, if the motor is in the inner ring operation mode, reduce the first preset parameter value to reduce the excitation current, and at the same time increase the second preset reference value to increase the torque current, so as to achieve the effect of reducing the torque output and increasing the speed. On the contrary, in the case of high load or large torque output required, if the motor is in the outer ring operation mode, increase the first preset parameter value to enhance the excitation current, and at the same time reduce the second preset reference value to reduce the torque current, so as to achieve the purpose of increasing the torque output and reducing the current consumption.

[0060] It should be noted that the reduced value and the increased value can be set according to experience, and the present application does not limit this.

[0061] 302. Input the adjusted first preset reference value and second preset reference value into the proportional-integral controller to regenerate the first control component and the second control component, so as to adjust the radial force application point of the rotor flux linkage.

[0062] In this step, the proportional-integral controller (PI controller) is a feedback controller that adjusts the output according to the error between the set target value and the actual measured value. In this process, the adjusted first preset reference value and second preset reference value are used as the new target values of the PI controller to generate new control signals to optimize the motor performance.

[0063] In the embodiment of the present application, the adjusted first preset reference value and second preset reference value are input into the PI controller as new targets. The PI controller calculates the errors of the field current component and the torque current component, and generates the corrected first control component and second control component through proportional and integral operations. These control components are then used to adjust the output voltage of the inverter, thereby changing the field and torque characteristics of the motor, and achieving precise control of the radial force application point of the rotor flux linkage.

[0064] For example, in an electric vehicle application example, when the vehicle starts, the motor control system first detects that the vehicle is in a low-speed and light-load state and determines it as the inner-ring operation mode. At this time, the system automatically reduces the first preset reference value of the field current component and increases the second preset reference value of the torque current component to reduce the torque output and quickly increase the vehicle speed. As the vehicle accelerates into the high-speed driving stage, the motor gradually switches to the outer-ring operation mode, and the system correspondingly increases the first preset reference value of the field current component and reduces the second preset reference value of the torque current component to increase the torque output and reduce the current consumption. Throughout the process, the PI controller continuously optimizes the control components according to the adjusted reference values to ensure that the motor can work efficiently under different working conditions and provide a smooth power output experience.

[0065] The present application dynamically adjusts the preset reference values of the field current component and the torque current component and inputs them into the PI controller for real-time optimization. This method not only significantly improves the flexibility and adaptability of the motor control system, but also effectively responds to different operating conditions and control requirements. This enables the motor to maintain the best performance in different states such as starting, accelerating, and cruising, greatly enhancing the overall efficiency and stability of the system, and is particularly suitable for application scenarios with high performance requirements such as electric vehicle drive systems. This method solves the problem of poor adaptability in traditional fixed-parameter control strategies and realizes more intelligent and efficient motor control.

[0066] In order to further improve the accuracy of motor control and the flexibility of magnetic field regulation, in some embodiments, the method further includes: 401. Collect the current fluctuation components corresponding to the dual three-phase windings of the multi-motor and the magnetic field interaction parameters, and construct a multi-dimensional relationship table, which is used to describe the interaction characteristics between the dual three-phase windings; In this step, the current fluctuation component refers to the instantaneous current fluctuation value caused by factors such as load changes during the operation of the motor. The magnetic field interaction parameter describes the mutual influence between different windings due to the magnetic field effect. The multi-dimensional relationship table is a data structure that records the specific values of these interactions to help understand and optimize the coordinated operation between the windings.

[0067] In the embodiments of the present application, the current fluctuations in the dual three-phase windings are real-time monitored by a high-precision current sensor installed on the motor, and the data of the magnetic field sensor is combined to analyze the magnetic field interaction between the windings. Using these data, the system can construct a multi-dimensional relationship table, which details the relationship between current fluctuations and magnetic field interactions under different working conditions. This step provides important basic data support for subsequent magnetic field adjustment.

[0068] 402. Detect the radial position offset of the rotor magnetic field with a preset accuracy based on the magnetic field detection sensor array, and synchronously measure the magnetic field distribution uniformity index to generate a magnetic field adjustment signal; In this step, the magnetic field detection sensor array is a group of sensors specifically designed to accurately measure the magnetic field intensity and direction, and they can provide high-resolution magnetic field information. The magnetic field distribution uniformity index reflects the degree of uniformity of the magnetic field in space and is an important parameter for evaluating the magnetic field quality. The magnetic field adjustment signal is an instruction generated according to the detection result to guide the adjustment of the magnetic field.

[0069] In the embodiments of the present application, a high-sensitivity magnetic field detection sensor array is used to real-time monitor the rotor magnetic field, obtain its radial position offset data and the magnetic field distribution uniformity index. Based on these data, the system generates a corresponding magnetic field adjustment signal. This signal not only indicates the direction and amplitude of the magnetic field that needs to be adjusted, but also takes into account the requirement of the magnetic field distribution uniformity, ensuring that the adjusted magnetic field meets the performance requirements and maintains good uniformity.

[0070] As a specific implementation manner, step 402 may include: 4021. Arrange a magnetic field detection sensor array on the stator side of the multi-motor, and the sensor array is distributed at a preset spatial interval for real-time collecting the radial distribution data of the rotor magnetic field; In this step, the magnetic field detection sensor array is an array composed of multiple high-sensitivity magnetic field sensors, which is installed on the stator side of the motor. These sensors are evenly distributed at a certain spatial interval to ensure that they can comprehensively cover and accurately measure the radial distribution of the rotor magnetic field. The preset spatial interval refers to the fixed distance between the sensors, and this parameter is designed according to the specific size and magnetic field characteristics of the motor to optimize the acquisition accuracy of the magnetic field data.

[0071] First, in the design or modification stage of the motor, a suitable position needs to be selected on the stator side to install the magnetic field detection sensor array. Each sensor is responsible for monitoring the magnetic field strength at its location and transmitting this data to the control system. Through a reasonable spatial layout, it can be ensured that the sensors can capture the entire picture of the rotor magnetic field, including its radial and circumferential variations. This step provides the basic data support for subsequent magnetic field analysis.

[0072] 4022. Calculate the radial position offset of the rotor magnetic field based on the detection data of the sensor array. The offset is determined by comparing the deviation between the actual magnetic field center and the theoretical magnetic field center. In this step, the radial position offset represents the position difference between the actual center and the theoretical center of the rotor magnetic field, which is a key indicator for evaluating the magnetic field symmetry and positioning accuracy. The theoretical magnetic field center refers to the ideal value calculated based on the motor design parameters; the actual magnetic field center is determined according to the real-time magnetic field data provided by the sensor array.

[0073] Using the magnetic field strength data collected by the sensor array, the system first identifies the actual center position of the current magnetic field. Then, this position is compared with the preset theoretical center, and the deviation between the two, that is, the radial position offset, is calculated. This process usually involves complex mathematical operations, such as the least squares fitting and other techniques, to improve the calculation accuracy. The finally obtained offset provides a direct basis for subsequent adjustments.

[0074] 4023. Synchronously calculate the magnetic field distribution uniformity index, which is generated by statistically calculating the distribution variances of the rotor magnetic field in the radial and circumferential directions. In this step, the magnetic field distribution uniformity index refers to a quantitative standard for measuring whether the magnetic field is evenly distributed in the entire internal space of the motor, usually determined by calculating the distribution variances of the magnetic field strength in different directions. The radial and circumferential distribution variances respectively reflect the fluctuations of the magnetic field in the direction perpendicular to the axis (radial) and the direction around the axis (circumferential).

[0075] After obtaining the magnetic field intensities at various sensor positions, the system further analyzes the spatial distribution characteristics of these data. Specifically, by performing statistical analysis on the radial and circumferential data, the corresponding distribution variances are calculated. A higher variance indicates uneven magnetic field distribution, while a lower variance indicates a more uniform magnetic field. This metric not only helps evaluate the quality of the current magnetic field but also provides important reference information for magnetic field adjustment.

[0076] 4024. Input the radial position offset and the magnetic field distribution uniformity index into the signal processing module to generate a magnetic field adjustment signal, which is used to compensate for the asymmetric distribution and position deviation of the rotor magnetic field.

[0077] In this step, the signal processing module refers to an integrated electronic unit that is responsible for receiving data from the sensor array and processing it to generate control instructions. The magnetic field adjustment signal refers to the control instructions generated based on the radial position offset and the magnetic field distribution uniformity index, which are used to guide the magnetic field adjustment device to perform specific adjustment operations.

[0078] After receiving the radial position offset and the magnetic field distribution uniformity index from the sensor array, the signal processing module comprehensively analyzes these data using a preset algorithm. Based on the analysis results, the module generates corresponding magnetic field adjustment signals. These signals may indicate how the magnetic field adjustment device should change the current, voltage, or other parameters to compensate for the asymmetric distribution and position deviation in the rotor magnetic field. For example, by adjusting the excitation current or using a specific compensation algorithm, the magnetic field can be realigned and its distribution uniformity optimized, thereby improving the overall performance and efficiency of the motor.

[0079] Through the above steps 4021 - 4024, this method realizes precise monitoring and dynamic adjustment of the motor magnetic field, ensuring that the motor can operate efficiently and stably under various working conditions. This method is particularly suitable for application scenarios that require high-precision magnetic field control, such as electric vehicle drive systems, etc., improving the reliability and adaptability of the system.

[0080] 403. Input the multi-dimensional relationship table and the magnetic field adjustment signal into the back electromotive force calculation model to correct the calculation deviation of the angle corresponding to the rotor magnetic field and update the independent adjustment weights of the excitation current component and the torque current component.

[0081] In this step, the back electromotive force calculation model is a mathematical model used to estimate the back electromotive force generated inside the motor during operation and its corresponding rotor magnetic field angle. The independent adjustment weight refers to the adjustment coefficient set for the excitation current component and the torque current component respectively in the vector control strategy, which is used to optimize their respective control effects.

[0082] In the embodiment of the present application, first, the multi-dimensional relationship table obtained from step 401 and the magnetic field adjustment signal obtained from step 402 are input into the back electromotive force calculation model together. The model uses these data to correct the previously calculated rotor magnetic field angle and eliminate possible deviations. Then, according to the corrected angle information, the system re-evaluates and updates the independent adjustment weights of the exciting current component and the torque current component, so that the motor can operate more efficiently under the new magnetic field conditions.

[0083] As a specific implementation manner, step 403 may include: 4031. Input the current fluctuation component of the dual three-phase winding and the magnetic field interaction parameter in the multi-dimensional dynamic relationship table into the back electromotive force calculation model, and dynamically correct the calculation deviation of the rotor magnetic field angle in combination with the magnetic field adjustment signal; Multi-dimensional dynamic relationship table: A data structure that records the current fluctuation component of the dual three-phase winding during the operation of the motor and the interaction parameters between it and the magnetic field.

[0084] Back electromotive force calculation model: A mathematical model used to estimate the back electromotive force generated inside the motor and the corresponding rotor magnetic field angle according to current and magnetic field data.

[0085] First, the system extracts the current fluctuation component of the dual three-phase winding and the magnetic field interaction parameter from the multi-dimensional dynamic relationship table. These data reflect the actual operating state of the motor under different working conditions. Then, these data together with the magnetic field adjustment signal generated in step 402 are input into the back electromotive force calculation model. The model uses these input data for complex mathematical operations to dynamically correct the previously calculated rotor magnetic field angle to eliminate possible deviations. In this way, the actual position and direction of the rotor magnetic field can be determined more accurately, providing accurate basic data for subsequent control.

[0086] 4032. Based on the corrected rotor magnetic field angle, recalculate the back electromotive force components in the two-phase stationary coordinate system and solve the real-time angle of the rotor magnetic flux; Corrected rotor magnetic field angle: A more accurate rotor magnetic field angle obtained after dynamic correction in step 4031.

[0087] Back electromotive force components in the two-phase stationary coordinate system: Represent the estimated back electromotive force values in the αβ coordinate system and are an important basis for further calculating the rotor magnetic flux angle.

[0088] After obtaining the corrected rotor magnetic field angle, the system uses this angle as a new reference point to recalculate the back electromotive force components in the two-phase stationary coordinate system (αβ coordinate system). Specifically, using the corrected angle information, a specific algorithm (such as Park transformation or extended Kalman filter) is applied to solve the real-time angle of the rotor magnetic flux. This step ensures more accurate calculation of the rotor magnetic flux angle, providing a reliable basis for subsequent field and torque current regulation.

[0089] 4033. Update the independent adjustment weights of the field current component and the torque current component according to the real-time angle of the rotor magnetic flux, where the adjustment weight of the field current component is dynamically adjusted by the change in the amplitude of the rotor magnetic flux; the adjustment weight of the torque current component is dynamically adjusted by the change in the angle of the rotor magnetic flux. Adjustment weight of the field current component: A coefficient used to optimize the control effect of the field current, dynamically adjusted according to the change in the amplitude of the rotor magnetic flux.

[0090] Adjustment weight of the torque current component: A coefficient used to optimize the control effect of the torque current, dynamically adjusted according to the change in the angle of the rotor magnetic flux.

[0091] Based on the real-time angle of the rotor magnetic flux obtained in step 4032, the system further analyzes the changes in its amplitude and angle. For the field current component, the system dynamically adjusts its adjustment weight according to the change in the amplitude of the rotor magnetic flux to ensure that the magnetic field strength meets the expectations. For the torque current component, the adjustment weight is dynamically adjusted according to the change in the angle of the rotor magnetic flux to ensure stable and efficient torque output. This dynamic adjustment mechanism enables the control system to better adapt to the changes of the motor under different operating conditions and improves the overall performance.

[0092] 4034. Input the updated adjustment weights into the proportional-integral controller to regenerate the first control component and the second control component to adapt to the dynamic changes of the rotor magnetic field.

[0093] Proportional-integral controller (PI controller): A feedback controller used to adjust the output according to the error between the set target value and the actual measured value, thereby achieving precise control of the system.

[0094] First control component and second control component: Control signals generated for the field current component and the torque current component respectively.

[0095] Input the adjusted regulation weights of the excitation current component and torque current component into the proportional-integral controller. The PI controller recalculates the control components of the excitation current and torque current based on these new weight values, namely the first control component and the second control component. These control components are then used to adjust the output voltage of the inverter, thereby changing the excitation and torque characteristics of the motor. The entire process ensures that the motor can maintain the optimal operating state under dynamically changing magnetic field conditions, improving the response speed and control accuracy of the system.

[0096] The following is a specific example: In an application scenario of an electric vehicle drive system, when the vehicle starts and travels under different road conditions, the control system first collects the current fluctuation components of the dual three-phase windings and the magnetic field interaction parameters through current sensors and magnetic field sensors, and constructs a multi-dimensional relationship table. Subsequently, a magnetic field detection sensor array is used to monitor the radial position offset of the rotor magnetic field with high precision, and the magnetic field distribution uniformity index is measured synchronously to generate a magnetic field adjustment signal. These signals are input into the back electromotive force calculation model to correct the calculation deviation of the rotor magnetic field angle. Based on this, the system updates the independent regulation weights of the excitation current component and torque current component to ensure that the motor can operate efficiently and smoothly under various working conditions. This method not only improves the response speed and control accuracy of the motor, but also enhances the robustness and adaptability of the system, significantly improving the driving experience.

[0097] This application collects key parameters during motor operation, constructs a multi-dimensional relationship table, monitors the magnetic field state in real time and adjusts the control strategy accordingly. This method significantly improves the accuracy and flexibility of motor control. It not only solves the problem of magnetic field angle calculation deviation in traditional control methods, but also can effectively cope with complex working condition changes to ensure that the motor can maintain the optimal performance under various operating states. This method is particularly suitable for high-performance motor application fields such as electric vehicle drive systems, improving the overall efficiency and stability of the system.

[0098] To further improve the anti-interference ability and stability of the motor control system, in some embodiments, the method further includes: 501. Monitor the drift amount corresponding to the electrical parameters of the multi-motor through a sliding mode observer, and dynamically cancel the mutual interference between the dual three-phase windings in combination with an interference cancellation algorithm to obtain an interference suppression result; In this step, a Sliding Mode Observer (SMO), an advanced state estimation technique, is used to monitor the system state in real time and estimate its changes. In a motor control system, it is commonly used to detect changes in electrical parameters. Drift: refers to the phenomenon that electrical parameters gradually deviate from their initial values over time due to factors such as temperature changes and aging. Interference cancellation algorithm: a technique used to identify and eliminate various interferences in the system to ensure the stable operation of the system.

[0099] In the embodiment of the present application, first, a sliding mode observer is integrated into the motor control system. This observer can monitor the electrical parameters (such as current, voltage, etc.) of the motor and their drift in real time. Then, a specially designed interference cancellation algorithm is used to analyze these data and calculate the specific situation of mutual interference between each phase winding. By applying adaptive filtering or other advanced algorithms, the system can dynamically cancel these interferences and generate interference suppression results. This step ensures that the motor can maintain a stable operating state even in the presence of external interferences.

[0100] In a specific implementation manner, step 501 may include: 5011. Deploy a dynamic parameter monitoring module in the control system of the multi-phase motor. This module collects the electrical parameters of the motor in real time, including current fluctuations, voltage fluctuations, temperature changes, and magnetic field strength changes. In the embodiment of the present application, first, a dynamic parameter monitoring module is integrated into the motor control system. This module collects key parameters such as current, voltage, temperature, and magnetic field strength in real time through sensors installed on the motor and its power supply circuit. For example, a current sensor can measure the current value in each phase winding, a voltage sensor can monitor the input voltage, a temperature sensor can detect the internal temperature of the motor, and a magnetic field sensor can capture changes in the magnetic field strength. These data are transmitted to the control system for further analysis and processing, providing basic data support for subsequent interference identification and compensation.

[0101] 5012. Calculate the mutual interference intensity between the dual three-phase windings based on the drift of the electrical parameters. The interference intensity is determined by comparing the current and voltage differences of each phase winding. Mutual interference intensity: refers to the degree of current and voltage differences caused by the interaction of electromagnetic fields between each phase winding.

[0102] Current and voltage differences: reflect the degree to which each phase winding is affected by other phase windings during operation.

[0103] In the embodiments of the present application, using the data obtained from the dynamic parameter monitoring module, the system calculates the current and voltage differences between the phase windings. Specifically, by comparing the current and voltage values of different phase windings at the same moment, the differences between them can be quantified. Such differences not only reflect the actual operating states of the phase windings but also reveal the degree of mutual interference existing between them. For example, if the current of a certain phase winding is significantly higher than that of other phases, it may indicate the existence of strong electromagnetic interference. Based on these difference data, the system can calculate the mutual interference intensity between the multi-phase windings, providing a basis for further interference elimination.

[0104] 5013. Dynamically cancel the mutual interference intensity through an interference cancellation algorithm, and the interference cancellation algorithm includes the following steps: Extract the current and voltage characteristics of each phase winding to generate an interference feature vector; Based on the interference feature vector, calculate an interference compensation signal; Superimpose the interference compensation signal onto the control signals of each phase winding to generate an interference suppression result.

[0105] Among them, the interference feature vector: a mathematical vector that contains the main characteristics of the current and voltage of each phase winding and is used to describe the specific pattern of interference. The interference compensation signal: a correction signal generated according to the interference feature vector, aiming to cancel the influence of interference. The interference suppression result: the final output signal after interference compensation, ensuring that each phase winding can operate normally with minimized interference.

[0106] In the embodiments of the present application, first, extract the current and voltage characteristics of each phase winding to generate an interference feature vector. This step usually involves complex signal processing techniques, such as the fast Fourier transform (FFT) or wavelet transform, to extract the key characteristics of the current and voltage signals. Next, based on the generated interference feature vector, use a specific algorithm (such as an adaptive filter or a Kalman filter) to calculate the corresponding interference compensation signal. This compensation signal is designed to precisely cancel the identified interference. Finally, superimpose the calculated interference compensation signal onto the original control signals of each phase winding to form new control instructions. These instructions are sent to an inverter or other control devices, thereby generating an interference suppression result, ensuring that the motor can operate stably and efficiently under complex working conditions.

[0107] Through the above steps, the system can monitor and dynamically cancel the mutual interference between the multi-phase windings in real time, improving the stability and reliability of the motor control system. This method is particularly applicable to application scenarios that require high-precision control, such as electric vehicle drive systems, etc., improving the overall performance of the system.

[0108] 502. Input the drift amount and the interference suppression result into the proportional-integral controller to adjust the generation logic of the first control component and the second control component. In this step, the proportional-integral controller (PI controller): A commonly used feedback controller that adjusts the output according to the error between the set target value and the actual measured value to achieve precise control. The first control component and the second control component: Control signals corresponding to the field current component and the torque current component respectively.

[0109] In the embodiment of the present application, the drift amount and the interference suppression result obtained from the sliding-mode observer are input into the proportional-integral controller. The PI controller uses this information to re-evaluate the current control requirements and adjusts the logic for generating the first control component and the second control component accordingly. Specifically, the controller recalculates the error based on the new input data and generates the corrected control components through proportional and integral operations. This step ensures that the control system can respond to external interferences in a timely manner and maintain the optimal operating state of the motor.

[0110] In a specific implementation manner, step 502 may include: 5021. Input the change amount of the operating parameters collected by the dynamic parameter monitoring module and the interference suppression result into the proportional-integral controller. The proportional-integral controller includes a d-axis current controller and a q-axis current controller. Change amount of operating parameters: Data obtained from the dynamic parameter monitoring module, including current fluctuations, voltage fluctuations, temperature changes, and magnetic field strength changes, etc. Interference suppression result: A signal generated by the interference cancellation algorithm used to cancel the mutual interference between the phase windings. Proportional-integral controller (PI controller): A feedback control mechanism that adjusts the output according to the error between the set target value and the actual measured value. In a motor control system, it is usually divided into a d-axis current controller and a q-axis current controller, which are used to control the field current component and the torque current component respectively.

[0111] In the embodiment of the present application, first, the system inputs the change amount of the operating parameters collected by the dynamic parameter monitoring module and the interference suppression result into the proportional-integral controller. These data contain the current operating state of the motor and the interference it has suffered. Specifically, the d-axis current controller is responsible for processing the field current component ( ), while the q-axis current controller is responsible for processing the torque current component ( ). By inputting the above data into these two controllers, the system can perform precise control based on the latest operating information.

[0112] 5022. Dynamically adjust the proportional coefficient and the integral coefficient of the d-axis current controller, and the proportional coefficient and the integral coefficient of the q-axis current controller based on the change amount of the operating parameters. Proportional coefficient: Determines the response speed of the controller to the error. A larger proportional coefficient will result in a faster response, but may also increase the risk of system oscillation. Integral coefficient: Determines the degree of response of the controller to the error accumulation, helps to eliminate the steady-state error, but an overly high integral coefficient may cause the system to become unstable.

[0113] In the embodiments of the present application, the system dynamically adjusts the proportional coefficient and integral coefficient of the d-axis and q-axis current controllers by using the change amount of the operating parameters obtained from the dynamic parameter monitoring module. The specific steps are as follows: First, the system calculates the errors between the actual values and the reference values of the field current component and the torque current component.

[0114] Second, based on these errors and the change amount of the operating parameters, the system dynamically adjusts the proportional coefficient and integral coefficient by using a preset adaptive algorithm (such as model predictive control or fuzzy logic control). For example, if a large current fluctuation is detected, the system may increase the proportional coefficient to speed up the response; if a steady-state error is found, the integral coefficient will be appropriately increased to gradually eliminate the error.

[0115] Finally, these adjustments are made in real time to ensure that the controller can always be optimized according to the latest operating conditions.

[0116] 5023. According to the adjusted proportional coefficient and integral coefficient, the first control component and the second control component are regenerated, where: the first control component is generated by the d-axis current controller through proportional-integral operation on the difference between the actual value and the reference value of the field current component; the second control component is generated by the q-axis current controller through proportional-integral operation on the difference between the actual value and the reference value of the torque current component.

[0117] The first control component: Generated by the d-axis current controller, used to adjust the field current component. The second control component: Generated by the q-axis current controller, used to adjust the torque current component.

[0118] In the embodiments of the present application, based on the adjusted proportional coefficient and integral coefficient, the system regenerates the first control component and the second control component. The specific steps are as follows: First, for the field current component, the d-axis current controller performs proportional-integral operation on the difference between its actual value and the reference value. This step combines the fast response characteristic of proportional control and the steady-state error elimination ability of integral control to generate the first control component.

[0119] Second, for the torque current component, the q-axis current controller also performs proportional-integral operation on the difference between its actual value and the reference value to generate the second control component.

[0120] Finally, the system generates new control instructions based on these control components and sends them to the inverter or other actuators to achieve precise control of the motor.

[0121] Through the above steps, the system can adjust the control strategy in real time according to the dynamic changes during the operation of the motor, ensuring that the motor can maintain the best performance under various working conditions. This method not only improves the anti-interference ability and stability of the system, but also enhances its ability to adapt to complex working conditions, and is particularly suitable for high-performance motor application fields such as electric vehicle drive systems.

[0122] 503. Based on the adjusted first control component and second control component, correct the voltage output rule of the inverter to ensure that the output of the three-phase voltage waveform matches the cooperative drive requirements of the multi-motor.

[0123] In this step, the voltage output rule of the inverter refers to the specific method and strategy by which the inverter generates a three-phase voltage waveform according to the control signal. The cooperative drive requirements refer to the application scenario requirements that the motor needs to meet, such as specific performance indicators such as speed and torque.

[0124] In the embodiment of the present application, the adjusted first control component and second control component are used as new instructions and input into the inverter. The inverter corrects its voltage output rule according to these instructions and generates a three-phase voltage waveform that meets the current working condition requirements. This step ensures that the voltage waveform output by the inverter can accurately meet the cooperative drive requirements of the motor, thereby optimizing the performance of the overall system.

[0125] In a specific implementation manner, step 503 may include: 5031. Based on the adjusted first control component and second control component, recalculate the control voltage components in the two-phase rotating coordinate system; The first control component and the second control component are control signals corresponding to the field current component and the torque current component respectively, and are generated after being adjusted by a proportional-integral controller.

[0126] The two-phase rotating coordinate system (dq coordinate system) is a coordinate system used to simplify motor control, where the d-axis represents the magnetic field direction and the q-axis represents the torque direction.

[0127] In the embodiment of the present application, the specific calculation process can refer to the formula calculation processes corresponding to steps 701-702 and steps 801-802 in the following embodiments, and the embodiment of the present application will not expand on this.

[0128] 5032. Convert the control voltage components into the reference voltage in the three-phase stationary coordinate system through inverse coordinate transformation; Inverse coordinate transformation: The process of converting from a two-phase rotating coordinate system (dq coordinate system) to a three-phase stationary coordinate system (abc coordinate system), usually using the inverse Park transformation or the inverse Clarke transformation.

[0129] Reference voltage: The voltage command in the three-phase stationary coordinate system, used to drive the inverter to output the required three-phase voltage waveform.

[0130] In the embodiments of the present application, the system converts the control voltage components in the two-phase rotating coordinate system ( and ) into the reference voltage in the three-phase stationary coordinate system through inverse coordinate transformation. The specific steps are as follows: Use the inverse Park transformation formula to convert and into the voltage components in the αβ coordinate system. Then use the inverse Clarke transformation formula to convert the voltage components in the αβ coordinate system into the reference voltage in the three-phase stationary coordinate system. This step ensures that the control system can generate specific voltage commands suitable for three-phase motors.

[0131] 5033. Input the reference voltage into the pulse width modulation module of the inverter to generate a three-phase voltage waveform; Pulse width modulation module (PWM module): A technology used to generate pulse width modulation signals, controlling the voltage waveform output by the inverter by adjusting the pulse width.

[0132] Three-phase voltage waveform: The three-phase alternating voltage waveform generated by the inverter according to the reference voltage, used to drive the motor.

[0133] In the embodiments of the present application, the converted reference voltage in the three-phase stationary coordinate system is input into the pulse width modulation module of the inverter. The PWM module generates corresponding pulse width modulation signals according to these reference voltages and applies them to the switching elements (such as IGBTs or MOSFETs) of the inverter, thereby generating accurate three-phase voltage waveforms. These voltage waveforms can accurately match the requirements of the motor to ensure its normal operation.

[0134] 5034. Real-time monitor the output characteristics of the three-phase voltage waveform, including amplitude, frequency, and phase, and compare them with the multi-motor coordinated operation requirements of the multi-motor; Output characteristics: Refer to the actual output parameters of the three-phase voltage waveform, including amplitude, frequency, and phase.

[0135] Multi-motor coordinated operation requirements: The requirements for the voltage waveform when multiple motors work together to ensure synchronization and stability.

[0136] In the embodiments of this application, the system monitors the three-phase voltage waveforms output by the inverter in real time and extracts key characteristics such as their amplitudes, frequencies, and phases. Then, these characteristics are compared with the pre-set multi-motor coordinated operation requirements. For example, if the system requires multiple motors to operate synchronously, it is necessary to ensure that the voltage waveforms received by each motor have the same frequency and phase difference. This step ensures that the output voltage waveforms can meet the requirements of multi-motor collaborative work.

[0137] 5035. According to the comparison results, dynamically optimize the voltage output rules of the inverter to ensure that the output of the three-phase voltage waveforms meets the synchronization and stability requirements of multi-motor coordinated operation.

[0138] Dynamic optimization: Adjust the voltage output rules of the inverter according to the results of real-time monitoring to achieve optimal performance.

[0139] Synchronization and stability requirements: Refer to the need for multiple motors to maintain a consistent operating state when working together to avoid out-of-sync or unstable phenomena.

[0140] In the embodiments of this application, according to the comparison results, the system dynamically optimizes the voltage output rules of the inverter. The specific steps are as follows: First, the system analyzes the differences between the actual output characteristics and the target requirements and identifies the existing errors.

[0141] Second, based on the error analysis results, an adaptive algorithm (such as model predictive control or fuzzy logic control) is used to adjust the voltage output rules of the inverter. For example, if a frequency deviation is detected, the system will adjust the modulation frequency of the PWM module; if an abnormal phase difference is found, the phase compensation strategy will be adjusted.

[0142] Finally, these adjustments are made in real time to ensure that the inverter can always be optimized according to the latest working conditions, thereby ensuring that the output of the three-phase voltage waveforms meets the synchronization and stability requirements of multi-motor coordinated operation.

[0143] Through the above steps, the system can monitor and dynamically optimize the voltage output of the inverter in real time to ensure that the multi-motor system can maintain synchronization and stable operation under complex working conditions. This method not only improves the overall performance of the system but also enhances its ability to adapt to complex application scenarios, especially suitable for high-performance motor application fields such as electric vehicle drive systems, etc.

[0144] For example, in a drive system of an electric vehicle, when the vehicle is driving on complex road conditions, the system first monitors the electrical parameters of the motor and their drift amounts in real time through a sliding mode observer. At the same time, an interference cancellation algorithm is applied to identify and dynamically cancel the mutual interference between the dual three-phase windings, generating an interference suppression result. Then, these data are input into a proportional-integral controller to adjust the logic for generating the first control component and the second control component to cope with the changing external environment. Finally, based on the adjusted control components, the inverter corrects its voltage output rule to ensure that the output three-phase voltage waveform can precisely match the cooperative drive requirements of the motor. For example, during climbing or accelerating, the system can quickly respond and provide the required high torque output, while during flat road cruising, it can optimize the energy efficiency, significantly enhancing the driving experience and the overall performance of the vehicle.

[0145] In this application, the sliding mode observer is used to monitor the electrical parameter drift amount, the interference cancellation algorithm is combined to dynamically cancel the mutual interference between the windings, and this information is input into the proportional-integral controller to adjust the control component generation logic. Finally, the voltage output rule of the inverter is corrected. This method significantly improves the anti-interference ability and stability of the motor control system. It not only solves the problem of being sensitive to external interference in traditional control methods but also can effectively cope with complex working condition changes, ensuring that the motor can maintain optimal performance in various operating states. This method is particularly suitable for high-performance motor application fields such as electric vehicle drive systems, improving the overall efficiency and reliability of the system.

[0146] In order to further improve the accuracy of motor control and simplify the control strategy, in some embodiments, through coordinate transformation, the three-phase current in the three-phase stationary coordinate system is converted into current components in the two-phase stationary coordinate system, and the current components are converted into the field current component and the torque current component in the two-phase rotating coordinate system synchronized with the rotor flux linkage, including: 601. Map the three-phase current in the three-phase stationary coordinate system to the two-phase stationary coordinate system through a linear projection transformation to obtain a first-axis current component and a second-axis current component, where the first-axis current component is composed of a weighted combination of the three-phase currents, and the second-axis current component is composed of the orthogonal projection of the three-phase currents; First-axis current component : Represents the current component on the axis, usually composed of a weighted combination of the three-phase currents.

[0147] Second-axis current component : Represents the current component on the axis, usually composed of the orthogonal projection of the three-phase currents.

[0148] In the embodiments of this application, first, the three-phase current in the three-phase stationary coordinate system is and transformed into current components in the two-phase stationary coordinate system and . The specific formula is as follows:

[0149] This formula transforms three-phase current into two-phase current through linear projection, enabling the control system to perform subsequent processing more conveniently. Through this transformation, the system can simplify the complex three-phase AC system into a more easily controllable two-phase DC system.

[0150] Specifically, this formula transforms three-phase current into two-phase current through a linear transformation matrix. Specifically, each row of the matrix represents the mapping relationship from three-phase to two-phase. The Clarke transformation is used to transform three-phase current and transformed into two-phase current and . This step is the process of simplifying from a complex three-phase system to a more easily controllable two-phase system. The specific calculation is as follows: The first-axis current component is composed of a weighted combination of the three-phase currents , with weights .

[0151] The second-axis current component is composed of the orthogonal projection of the three-phase currents , with weights .

[0152] Among them, represents a normalization factor, and its introduction is to ensure the conservation of power before and after the transformation and simplify the mathematical calculation.

[0153] Through this transformation, the control system can simplify the complex three-phase AC system into a more easily processed two-phase DC system, thus preparing for the subsequent Park transformation.

[0154] 602. Based on the angle of the rotor flux linkage, perform a rotation transformation on the first-axis current component and the second-axis current component in the two-phase stationary coordinate system to obtain an excitation current component and a torque current component, where the excitation current component is in the same direction as the rotor flux linkage, and the torque current component is orthogonal to the direction of the rotor flux linkage.

[0155] The angle of the rotor flux linkage : represents the position angle of the rotor flux linkage relative to the stator and is a key parameter for performing the Park Transformation.

[0156] The excitation current component : Represents the current component in the direction of the rotor flux linkage, used to generate the magnetic field.

[0157] Torque current component : Represents the current component orthogonal to the direction of the rotor flux linkage, used to generate torque.

[0158] In the embodiments of the present application, the Park transformation formula is used to transform the current components and in the two-phase stationary coordinate system into the exciting current component and the torque current component in the two-phase rotating coordinate system. The specific formula is as follows:

[0159] This formula transforms the current components in the two-phase stationary coordinate system into the current components in the two-phase rotating coordinate system that rotate synchronously with the rotor flux linkage through a rotation transformation. In this way, the system can independently control the exciting current and the torque current, thereby achieving more precise and efficient motor control.

[0160] Among them, the rotation transformation matrix is a rotation transformation matrix on a two-dimensional plane, used to rotate the current components in the coordinate system and into the dq coordinate system. is the angle of the rotor flux linkage relative to the stator (usually provided by a position sensor or an estimator).

[0161] The first row of the matrix represents how to calculate the axis component , where .

[0162] The second row of the matrix represents how to calculate the axis component , where .

[0163] This rotation operation makes: The d-axis is always in the same direction as the rotor flux linkage; The q-axis is always orthogonal to the direction of the rotor flux linkage.

[0164] In order to further improve the accuracy and stability of motor control, in some embodiments, in the two-phase rotating coordinate system, through a proportional-integral controller, according to the exciting current component and the corresponding first preset reference value, a first control component is generated, including: 701. In the two-phase rotating coordinate system, based on the difference between the actual measured value of the exciting current component and the first preset reference value, a proportional-integral controller calculates the superposition result of the first proportional adjustment term and the first integral adjustment term. Among them, the weight of the first proportional adjustment term is determined by the preset proportional coefficient of the d-axis current controller in the two-phase rotating coordinate system, and the weight of the first integral adjustment term is determined by the preset integral coefficient of the d-axis current controller. Among them, the two-phase rotating coordinate system is called the dq coordinate system, also known as the d-q or direct-quadrature coordinate system, which is a rotating coordinate system used in the field of motor control. This coordinate system is mainly used to simplify the mathematical models of AC motors (such as induction motors and permanent magnet synchronous motors) and facilitate the implementation of precise control. In the dq coordinate system: The d-axis (Direct Axis): refers to the axis aligned with the rotor magnetic field direction. The direction of this axis is called the direct axis because it is directly aligned with the rotor magnetic field. The q-axis (Quadrature Axis): is perpendicular to the d-axis and leads the rotor magnetic field direction by 90 electrical degrees. The direction of this axis is called the quadrature axis. By converting parameters such as current and voltage into the dq coordinate system, the originally complex three-phase AC system can be converted into a more easily processed two-phase DC system.

[0165] In this step, the exciting current component : represents the current component that is consistent with the rotor flux linkage direction in the dq coordinate system. The first preset reference value : is the target value of the desired exciting current component. The first proportional adjustment term: is the proportional part based on the error between the actual measured value and the reference value, and is used to quickly respond to the error change. The first integral adjustment term: is the part based on the accumulation of the error between the actual measured value and the reference value, and is used to eliminate the steady-state error. The preset proportional coefficient and the preset integral coefficient : are the proportional and integral gain parameters of the proportional-integral controller respectively, which determine the response speed of the controller to the error and the compensation ability for the accumulated error.

[0166] 702. Apply a limit constraint to the accumulation process of the first integral adjustment term to limit the growth range of the integral accumulation value, and map the superposition result of the proportional adjustment term and the integral adjustment term to the first control component in the two-phase rotating coordinate system, which is used to adjust the voltage output of the inverter to make the actual measured value of the exciting current component approach the first preset reference value.

[0167] Limit constraint: A technical means to prevent the integral adjustment term from accumulating too much and causing system instability, usually setting a maximum and minimum accumulation value.

[0168] The first control component: the control signal generated after proportional-integral operation, which is used to drive the inverter to adjust its output voltage, thereby regulating the field current component of the motor.

[0169] In the embodiments of the present application, for the above steps 701-702, first, the system obtains the actual measured value of the field current component and compares it with the first preset reference value to obtain an error Then, a proportional-integral controller is used to process this error: Secondly, the preset proportional coefficient is used to amplify the error to obtain the first proportional adjustment term .

[0170] Next, the preset integral coefficient is used to accumulate and sum the error to obtain the first integral adjustment term .

[0171] Finally, the above two terms are superimposed to obtain the first control component . This signal serves as the first control component and is used to adjust the voltage output of the inverter.

[0172] It should be noted that when calculating the integral adjustment term, in order to avoid system oscillation or instability caused by excessive integral accumulation, the system imposes a limit constraint on the accumulation process of the integral adjustment term. The specific steps are as follows: Set a reasonable upper and lower limit (for example Max_Integral), and when the integral accumulation value exceeds this range, it is limited within this range. The integral adjustment term after the limit processing is superimposed with the proportional adjustment term to obtain the final adjustment signal . This signal serves as the first control component and is sent to the inverter to adjust its output voltage. The inverter adjusts the output voltage according to the received control component, so that the actual measured value of the field current component gradually approaches the first preset reference value , achieving precise control.

[0173] The following is a specific example: In an application scenario of an electric vehicle drive system, assume that it is currently necessary to increase the magnetic field strength of the motor. The control system first sets the first preset reference value of the field current component . Then, the system collects the current field current component in real time and calculates the error .

[0174] In step 701, the system uses a proportional-integral controller for processing: Assume the proportional coefficient , then the proportional adjustment term is .

[0175] Assume the integral coefficient , then the integral regulation term is . Assume the previous cumulative error is 0.5, then the new integral regulation term is .

[0176] Superposition result: the final regulation signal .

[0177] In step 702, the system applies a clamping constraint to the integral regulation term (assuming the upper limit is 1). Since the new integral regulation term 0.75 is less than the upper limit, no adjustment is required. The final regulation signal is sent to the inverter, and the inverter adjusts the output voltage according to this signal, so that the actual measured value of the field current component gradually approaches , achieving precise field control.

[0178] In this application, by using a proportional-integral controller in the two-phase rotating coordinate system, according to the difference between the actual measured value of the field current component and the preset reference value, the superposition result of the first proportional regulation term and the first integral regulation term is calculated, and a clamping constraint is applied to the integral regulation term. This method not only improves the accuracy and response speed of motor control, but also effectively avoids the system instability problem caused by excessive integral accumulation. It solves the problems such as slow error response and large steady-state error existing in traditional control methods, and is particularly suitable for high-performance motor application fields such as electric vehicle drive systems, etc., improving the overall efficiency and stability of the system.

[0179] In order to further improve the accuracy and stability of motor control, in some embodiments, generating a second control component according to the obtained motor torque, the torque current component, and the corresponding second preset reference value includes: 801. Based on the difference between the actual measured value of the torque current component and the second preset reference value, generate the synthesis result of the second proportional regulation term and the second integral regulation term through a proportional-integral controller, wherein the weight of the second proportional regulation term is determined by the preset proportional coefficient of the q-axis current controller in the two-phase rotating coordinate system, and the weight of the integral regulation term is determined by the preset integral coefficient of the q-axis current controller; Torque current component : Represents the current component orthogonal to the rotor flux direction in the dq coordinate system, and is used to generate motor torque.

[0180] Second preset reference value : The target value of the desired torque current component, usually set according to the required motor torque.

[0181] Second proportional adjustment term: The proportional part based on the error between the actual measurement value and the reference value, used to quickly respond to changes in the error.

[0182] Second integral adjustment term: The part based on the accumulation of the error between the actual measurement value and the reference value, used to eliminate the steady-state error.

[0183] Preset proportional coefficient And preset integral coefficient : They are respectively the proportional and integral gain parameters of the proportional-integral controller, which determine the response speed of the controller to the error and the compensation ability for the accumulated error.

[0184] 802. Apply a dynamic amplitude limiting constraint to the accumulation process of the second integral adjustment term, limit the growth range of the integral accumulation value, and map the combined result of the second proportional adjustment term and the second integral adjustment term to the second control component in the two-phase rotating coordinate system, used to adjust the voltage output of the inverter, so that the actual value of the torque current component approaches the second preset reference value.

[0185] Dynamic amplitude limiting constraint: A technical means to prevent the integral adjustment term from accumulating too much and causing system instability, usually dynamically adjusting the upper and lower limits according to the operating state of the system.

[0186] Second control component: The control signal generated after proportional-integral operation, used to drive the inverter to adjust its output voltage, thereby adjusting the torque current component of the motor.

[0187] In the embodiment of the present application, first, the system obtains the actual measurement value of the torque current component and compares it with the second preset reference value to obtain the error . Then, use the proportional-integral controller to process this error: Utilize the preset proportional coefficient to amplify the error to obtain the second proportional adjustment term .

[0188] Utilize the preset integral coefficient to accumulate and sum the error to obtain the second integral adjustment term .

[0189] Superimpose the above two items to obtain the final adjustment signal . This signal is used as the second control component to adjust the voltage output of the inverter.

[0190] It should be noted that when calculating the integral adjustment term, in order to avoid the system oscillating or becoming unstable due to excessive integral accumulation, the system applies a dynamic amplitude limiting constraint to the accumulation process of the integral adjustment term. The specific steps are as follows: Set a reasonable upper and lower limit (for example Max_Integral), and dynamically adjusts these limit values according to the current operating state of the system. When the integral accumulation value exceeds this range, it is limited within this range. The integral adjustment term after amplitude limiting is superimposed with the proportional adjustment term to obtain the final adjustment signal This signal is used as the second control component and is sent to the inverter to adjust its output voltage. The inverter adjusts the output voltage according to the received control component, so that the actual measured value of the torque current component gradually approaches the second preset reference value to achieve precise control.

[0191] In an electric vehicle acceleration scenario, assume that it is currently necessary to increase the torque of the motor to increase the vehicle speed. The control system first sets the second preset reference value of the torque current component Then, the system collects the current torque current component in real time and calculates the error .

[0192] In step 801, the system uses a proportional-integral controller for processing: Assume the proportionality coefficient , then the proportional adjustment term is .

[0193] Assume the integral coefficient , then the integral adjustment term is . Assume the previous cumulative error is 1, then the new integral adjustment term is .

[0194] The final adjustment signal .

[0195] In step 802, the system applies a dynamic amplitude limiting constraint to the integral adjustment term (assuming the upper limit is 1.5). Since the new integral adjustment term 1.2 is less than the upper limit, no adjustment is required. The final adjustment signal is sent to the inverter, and the inverter adjusts the output voltage according to this signal, so that the actual measured value of the torque current component gradually approaches , achieving precise torque control.

[0196] In this application, by using a proportional-integral controller in a two-phase rotating coordinate system, the synthesis result of the second proportional regulation term and the second integral regulation term is calculated according to the difference between the actual measured value and the preset reference value of the torque current component, and a dynamic amplitude limiting constraint is imposed on the integral regulation term. This method not only improves the accuracy and response speed of motor control, but also effectively avoids the system instability problem caused by excessive integral accumulation. It solves the problems such as slow error response and large steady-state error existing in traditional control methods, and is particularly suitable for high-performance motor application fields such as electric vehicle drive systems, etc., improving the overall efficiency and stability of the system. In addition, the dynamic amplitude limiting constraint can be flexibly adjusted according to the system state, further enhancing the robustness and adaptability of the control system.

[0197] In order to further improve the accuracy and stability of motor control, in some embodiments, through an inverse coordinate transformation method, the first control component and the second control voltage in the two-phase rotating coordinate system are converted into a reference voltage in the three-phase stationary coordinate system, so as to drive the inverter to output a corresponding three-phase voltage waveform through the reference voltage, including: 901. Based on the angle of the rotor magnetic flux, perform a reverse rotation transformation on the first control component and the second control voltage in the two-phase rotating coordinate system to generate orthogonal voltage components in the two-phase stationary coordinate system; First control component and the second control voltage : respectively represent the control voltages related to the excitation current and the torque current in the dq coordinate system. The angle of the rotor magnetic flux : represents the position angle of the rotor magnetic flux relative to the stator. Orthogonal voltage components and : represent the voltage components in the coordinate system.

[0198] In the embodiments of this application, first, the system obtains the first control component and the second control voltage , and performs a reverse rotation transformation according to the current angle of the rotor magnetic flux . The specific formula is as follows:

[0199] This matrix is the inverse transformation matrix of the Park Transformation, which is used to convert the voltage components in the dq coordinate system back to the coordinate system. Through this transformation, the system can convert the voltage signal that rotates synchronously with the rotor into a voltage signal in the fixed coordinate system, thus preparing for the subsequent Clarke inverse transformation.

[0200] Among them, regarding the rotation matrix Consistent with the function of step 602 in the above embodiment, this is not elaborated in this embodiment of the present application.

[0201] 902. Map the orthogonal voltage components in the two-phase stationary coordinate system to the three-phase stationary coordinate system through phase expansion transformation to obtain three-phase voltage components, where the first-phase voltage component in the three-phase voltage components is consistent with the first-axis component of the orthogonal voltage component, and the second-phase voltage component and the third-phase voltage component in the three-phase voltage components are composed of linear combinations of the first-axis and second-axis components of the orthogonal voltage component; Three-phase voltage components : Represents the three-phase voltage components in the abc coordinate system. Clarke Inverse Transformation: A method for converting voltage components in a two-phase stationary coordinate system ( coordinate system) into voltage components in a three-phase stationary coordinate system (abc coordinate system).

[0202] In this embodiment of the present application, based on step 901, the system uses the Clarke inverse transformation to transform the orthogonal voltage components in the two-phase stationary coordinate system and into voltage components in the three-phase stationary coordinate system , and . The specific formula is as follows:

[0203] This matrix transforms the voltage components in the coordinate system into the voltage components in the coordinate system. Through this transformation, the system can expand the control voltage originally in the two-phase coordinate system to the three-phase coordinate system to facilitate driving the inverter to output the corresponding three-phase voltage waveform.

[0204] Among them, is a mapping matrix from the two-phase system to the three-phase system, and its specific meaning is as follows: The first row: , indicating that is directly mapped to , that is, . This is because in the coordinate system directly corresponds to the A-phase voltage.

[0205] The second row: indicates that the linear combination of and is mapped to , that is, This reflects the phase difference (120 degrees) of the B-phase voltage relative to the A-phase voltage.

[0206] The third line: Indicates mapping the and linear combination of to That is, This reflects the phase difference (240 degrees or -120 degrees) of the C-phase voltage relative to the A-phase voltage.

[0207] 903. Use the as the reference voltage among the three-phase voltage components in the three-phase stationary coordinate system to drive the inverter to output the corresponding three-phase voltage waveform.

[0208] Reference voltage: The three-phase voltage components after inverse coordinate transformation, serving as the input signal of the inverter.

[0209] Inverter: A power electronic device used to convert direct current into alternating current and adjust its output voltage waveform according to the reference voltage.

[0210] In the embodiment of the present application, based on step 902, the system uses the three-phase voltage components in the three-phase stationary coordinate system and as the reference voltage and inputs them into the inverter. The inverter generates corresponding PWM (pulse width modulation) signals according to these reference voltages, thereby outputting the required three-phase voltage waveform. The specific implementation steps are as follows: The PWM module inside the inverter generates corresponding pulse width modulation signals according to the reference voltage. Through switching elements (such as IGBTs or MOSFETs), the inverter converts the DC power supply into a three-phase AC power supply and outputs a three-phase voltage waveform that meets the requirements of the reference voltage.

[0211] In the present application, through the inverse coordinate transformation method, the control voltage components in the two-phase rotating coordinate system are converted into the reference voltage in the three-phase stationary coordinate system. This method not only improves the accuracy and response speed of motor control but also effectively solves the complexity and inaccuracy problems existing in traditional control methods. It enables the control system to independently adjust the excitation current and torque current according to actual needs and accurately convert these adjustment results into the output voltage waveform of the inverter, which is particularly suitable for high-performance motor application fields such as electric vehicle drive systems, etc., improving the overall efficiency and stability of the system. In addition, this method simplifies the complex three-phase AC motor control strategy and enhances the robustness and adaptability of the system.

[0212] Figure 2 The following is a schematic structural diagram of a radial vector control system for a multi-motor provided by an embodiment of the present application. As Figure 2 shown, this system includes: A determination module 21, configured to determine three-phase currents of a multi-source motor in a three-phase stationary coordinate system; A conversion module 22, configured to convert the three-phase currents in the three-phase stationary coordinate system into current components in a two-phase stationary coordinate system through a coordinate conversion method, and convert the current components into an exciting current component and a torque current component in a two-phase rotating coordinate system that synchronously rotates with the rotor flux linkage; A generation module 23, configured to generate a first control component through a proportional-integral controller according to the exciting current component and a corresponding first preset reference value in the two-phase rotating coordinate system; generate a second control component according to the obtained motor torque, the torque current component, and a corresponding second preset reference value; The conversion module 22 is further configured to convert the first control component and the second control voltage in the two-phase rotating coordinate system into a reference voltage in the three-phase stationary coordinate system through an inverse coordinate conversion method, so as to drive an inverter to output corresponding three-phase voltages through the reference voltage, and realize the radial vector of the multi-source motor.

[0213] Figure 2 The radial vector control system of the multi-source motor can execute Figure 1 The radial vector control method of the multi-source motor described in the embodiments shown. The implementation principle and technical effects will not be elaborated here. For the radial vector control system of the multi-source motor in the above embodiments, the specific manners in which each module and unit perform operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0214] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A radial vector control method for a multi-element motor, characterized in that: include: Determine the three-phase current of the multi-electromoter in the three-phase stationary coordinate system; By means of coordinate conversion, the three-phase current in the three-phase stationary coordinate system is converted into the current component in the two-phase stationary coordinate system, and the current component is converted into the excitation current component and the torque current component in the two-phase rotating coordinate system rotating synchronously with the rotor flux; In the two-phase rotating coordinate system, a first control component is generated according to the excitation current component and a corresponding first preset reference value through a proportional-integral controller; a second control component is generated according to the acquired motor torque, the torque current component and a corresponding second preset reference value; By means of inverse coordinate conversion, the first control component and the second control voltage in the two-phase rotating coordinate system are converted into a reference voltage in the three-phase stationary coordinate system, so that the reference voltage drives the inverter to output the corresponding three-phase voltage waveform to realize the radial vector of the multi-electromoter.

2. The method according to claim 1, characterized in that Also includes: Obtain the position information of the rotor flux; Determine the angle of the rotor flux by combining the acquired electrical parameters of the multi-electromotor and a pre-established back electromotive force observation model; The back-electromotive force observation model extracts the back-electromotive force components in a two-phase stationary coordinate system, and solves the angle of the rotor flux based on the orthogonal relationship of the back-electromotive force components; the excitation current component and the torque current component are determined according to the angle of the rotor flux.

3. The method according to claim 1, characterized in that Also includes: According to the operating condition and control target of the multi-electromotor, adjusting the first preset parameter value corresponding to the excitation current component and the second preset reference value corresponding to the torque current component; Inputting the adjusted first preset reference value and second preset reference value into the proportional integral controller to regenerate the first control component and the second control component to adjust the radial force application point of the rotor flux; The process of adjusting the first preset parameter value corresponding to the excitation current component and the second preset reference value corresponding to the torque current component includes: During the startup phase, when the multi-electromotor is in the inner ring operation mode, the first preset reference value is lowered and the second preset reference value is increased to reduce the torque output and increase the speed; or, when the multi-electromotor is in the outer ring operation mode, the first preset reference value is increased and the second preset reference value is lowered to increase the torque output and reduce the current consumption.

4. The method according to claim 2, characterized in that: Also includes: Collecting the current fluctuation components and magnetic field interaction parameters corresponding to the dual three-phase windings of the multi-element motor, and constructing a multi-dimensional relationship table, wherein the multi-dimensional relationship table is used to describe the interaction characteristics between the dual three-phase windings; Based on the magnetic field detection sensor array, the radial position deviation of the rotor magnetic field is detected with a preset accuracy, and the magnetic field distribution uniformity index is measured synchronously to generate a magnetic field adjustment signal; The multi-dimensional relationship table and the magnetic field adjustment signal are input into a back electromotive force calculation model to correct the calculation deviation of the rotor magnetic field corresponding angle, and to update the independent adjustment weights of the excitation current component and the torque current component.

5. The method according to claim 2, characterized in that: Also includes: The drift corresponding to the electrical parameters of the multi-electromotor is monitored by a sliding mode observer, and the mutual interference between the dual three-phase windings is dynamically offset in combination with an interference elimination algorithm to obtain an interference suppression result; Inputting the drift amount and the interference suppression result into the proportional-integral controller to adjust the generation logic of the first control component and the second control component; Based on the adjusted first control component and second control component, the voltage output rule of the inverter is modified to ensure that the output of the three-phase voltage waveform matches the coordinated driving requirements of the multi-electromotor.

6. The method according to claim 1, characterized in that The coordinate conversion method converts the three-phase current in the three-phase stationary coordinate system into the current component in the two-phase stationary coordinate system, and converts the current component into the excitation current component and the torque current component in the two-phase rotating coordinate system that rotates synchronously with the rotor flux, including: Mapping the three-phase current in the three-phase stationary coordinate system to the two-phase stationary coordinate system through linear projection transformation to obtain a first axis current component and a second axis current component, wherein the first axis current component is composed of a weighted combination of the three-phase currents, and the second axis current component is composed of an orthogonal projection of the three-phase currents; Based on the angle of the rotor flux, the first axis current component and the second axis current component in the two-phase stationary coordinate system are rotationally transformed to obtain an excitation current component and a torque current component, wherein the excitation current component is consistent with the direction of the rotor flux, and the torque current component is orthogonal to the direction of the rotor flux.

7. The method according to claim 1, characterized in that In the two-phase rotating coordinate system, generating a first control component according to the excitation current component and a corresponding first preset reference value through a proportional-integral controller includes: In the two-phase rotating coordinate system, a superposition result of a first proportional adjustment item and a first integral adjustment item is calculated based on a difference between an actual measured value of the excitation current component and a first preset reference value by a proportional-integral controller, wherein a weight of the first proportional adjustment item is determined by a preset proportional coefficient of a d-axis current controller in the two-phase rotating coordinate system, and a weight of the first integral adjustment item is determined by a preset integral coefficient of the d-axis current controller; A limiting constraint is imposed on the accumulation process of the first integral adjustment item to limit the growth range of the integral accumulation value, and the superposition result of the proportional adjustment item and the integral adjustment item is mapped to the first control component in a two-phase rotating coordinate system, which is used to adjust the voltage output of the inverter so that the actual test value of the excitation current component approaches the first preset reference value.

8. The method according to claim 1, characterized in that The generating of the second control component according to the acquired motor torque, the torque current component and the corresponding second preset reference value comprises: generating a synthesis result of a second proportional adjustment item and a second integral adjustment item based on a difference between an actual measurement value of the torque current component and a second preset reference value by a proportional-integral controller, wherein a weight of the second proportional adjustment item is determined by a preset proportional coefficient of a q-axis current controller in the two-phase rotating coordinate system, and a weight of the integral adjustment item is determined by a preset integral coefficient of the q-axis current controller; A dynamic limiting constraint is applied to the accumulation process of the second integral adjustment item to limit the growth range of the integral accumulation value, and the synthesis result of the second proportional adjustment item and the second integral adjustment item is mapped to a second control component in a two-phase rotating coordinate system, which is used to adjust the voltage output of the inverter so that the actual value of the torque current component approaches the second preset reference value.

9. The method according to claim 1, characterized in that: The method of converting the first control component and the second control voltage in the two-phase rotating coordinate system into a reference voltage in the three-phase stationary coordinate system by inverse coordinate conversion, so as to drive the inverter to output a corresponding three-phase voltage waveform by the reference voltage, comprises: Based on the angle of the rotor flux, the first control component and the second control voltage in the two-phase rotating coordinate system are reversely transformed to generate an orthogonal voltage component in the two-phase stationary coordinate system; Mapping the orthogonal voltage components in the two-phase stationary coordinate system to the three-phase stationary coordinate system through phase expansion transformation to obtain three-phase voltage components, wherein the first phase voltage component of the three-phase voltage components is consistent with the first axis component of the orthogonal voltage component, and the second phase voltage component and the third phase voltage component of the three-phase voltage component are formed by a linear combination of the first axis component and the second axis component of the orthogonal voltage component; The three-phase voltage components in the three-phase stationary coordinate system are used as reference voltages to drive the inverter to output corresponding three-phase voltage waveforms.

10. A radial vector control system for a multi-electromotor, characterized in that: include: A determination module, used for determining the three-phase current of the multi-electromotor in a three-phase stationary coordinate system; A conversion module, used to convert the three-phase current in the three-phase stationary coordinate system into the current component in the two-phase stationary coordinate system through coordinate conversion, and convert the current component into the excitation current component and the torque current component in the two-phase rotating coordinate system rotating synchronously with the rotor flux; A generating module, configured to generate a first control component according to the excitation current component and a corresponding first preset reference value through a proportional-integral controller in the two-phase rotating coordinate system; and generate a second control component according to the acquired motor torque, the torque current component and a corresponding second preset reference value; The conversion module is also used to convert the first control component and the second control voltage in the two-phase rotating coordinate system into a reference voltage in the three-phase stationary coordinate system through an inverse coordinate conversion method, so as to drive the inverter to output the corresponding three-phase voltage through the reference voltage to realize the radial vector of the multi-electromoter.

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