Non-cascade permanent magnet synchronous motor model prediction speed current control system and method

Abstract

The invention provides a non-cascade permanent magnet synchronous motor model prediction speed current control system and method, and relates to the technical field of motor control, the system realizes the tracking of the rotating speed and the current in the same loop by introducing a model prediction speed current controller, only needs to set three influence factor parameters, and can realize the tracking of the rotating speed and the current. And the parameter setting workload of the traditional double-PID controller is obviously reduced. By adopting the saturation function type sliding mode load observer, the problem of high-frequency buffeting is effectively relieved, and the accuracy of load torque estimation is improved. The model prediction speed current controller is based on a discretized permanent magnet synchronous motor model, voltage vector output is optimized by constructing a cost function, rapid tracking of current and speed is achieved, and the dynamic performance of the system is improved. The objective of the invention is to solve the problems of limited bandwidth, complex parameter setting and insufficient dynamic performance in a conventional cascade control structure.

Description

Technical Field

[0001] The present invention relates to the technical field of motor control, and in particular to a non-cascaded permanent magnet synchronous motor model prediction speed current control system and method. Background Art

[0002] With the continuous advancement of modern industrial technology, permanent magnet synchronous motors (PMSM) have been widely used in many fields, such as electric vehicles, industrial automation, aerospace, etc., due to their high efficiency, high power density and excellent dynamic performance. However, in the field of motor control, traditional control strategies mostly adopt a dual-loop cascade structure of speed loop and current loop. Although this structure is relatively simple in design, it has many limitations.

[0003] First, the cascade control structure divides speed control and current control into two independent links. Although this separate control method is convenient for separate debugging, it will significantly reduce the overall bandwidth of the system. Lower bandwidth means that the system responds slower and cannot quickly adapt to load changes or dynamic instructions, thereby limiting the performance of the motor in high-performance application scenarios. Secondly, in order to ensure the stability of the system, the traditional method requires precise matching of the parameters of the speed loop and the current loop. This process is not only complicated, but also easily affected by changes in motor parameters and load disturbances, further increasing the difficulty of debugging the control system.

[0004] In recent years, with the rapid development of digital control technology, model predictive control (MPC) has gradually attracted attention as an advanced control strategy. MPC predicts the future system state by establishing a mathematical model of the motor and optimizes the control input to achieve the desired performance. However, despite the advantages of MPC such as fast dynamic response and flexible control strategy design, the traditional finite set model predictive control (FCS-MPC) is still limited by the cascade structure in practical applications. This structure not only limits the overall performance of the control system, but also requires the parameters of the current loop and the speed loop to be adjusted separately, which cannot give full play to the advantages of MPC in multivariable optimization and complex constraints.

[0005] In addition, in traditional control methods, the bandwidth of the current loop usually needs to be set to several times the bandwidth of the speed loop to reduce the mutual influence between the two. Although this design avoids the coupling between parameters to a certain extent, it inevitably sacrifices the dynamic performance of the system, making it difficult for the motor to achieve the ideal state in terms of fast response and high-precision control. Therefore, how to break the limitations of the traditional cascade structure and design a non-cascade control method that can give full play to the advantages of model predictive control, thereby improving the dynamic performance of the system, simplifying the parameter setting process, and realizing efficient coordinated control of current and speed has become a key issue that needs to be solved in the current field of permanent magnet synchronous motor control technology.

[0006] In view of this, this application is filed. Summary of the invention

[0007] The present invention provides a non-cascaded permanent magnet synchronous motor model prediction speed current control system and method, which can at least partially improve the above-mentioned problems.

[0008] To achieve the above object, the present invention adopts the following technical solutions: A non-cascaded permanent magnet synchronous motor model prediction speed current control system, comprising: a permanent magnet synchronous motor, a drive component, a sensor component, a model prediction speed current controller, and a preprocessing component, wherein the input end of the sensor component is electrically connected to the output end of the permanent magnet synchronous motor, the output end of the sensor component is electrically connected to the input end of the preprocessing component, the input end of the model prediction speed current controller is electrically connected to the output end of the preprocessing component and the output end of the sensor component, the output end of the model prediction speed current controller is electrically connected to the input end of the drive component, and the output end of the drive component is electrically connected to the input end of the permanent magnet synchronous motor; The sensor component is used to obtain the rotor position signal and three currents of the permanent magnet synchronous motor, and the preprocessing component is used to obtain the load torque estimation value and q-axis reference current of the permanent magnet synchronous motor; The model-predicted speed current controller is used to perform reference tracking of current and speed according to input feedback data, and output an optimal inverter control voltage; The driving component is used to perform PWM modulation and inversion processing on the optimal inverter control voltage, and transmit the obtained corresponding voltage to the permanent magnet synchronous motor to achieve control of the permanent magnet synchronous motor.

[0009] The present invention also provides a non-cascaded permanent magnet synchronous motor model prediction speed current control method. The method is applied to the non-cascaded permanent magnet synchronous motor model prediction speed current control system as described in any one of the above items, and comprises: Obtain the rotor position signal and three currents of the permanent magnet synchronous motor collected by the sensor component, and pre-process the rotor position signal and the three currents respectively to obtain the motor speed feedback value and the dq axis current feedback value; The motor speed feedback value is observed and processed by using a sliding mode load observer to obtain a load torque estimation value, and the load torque estimation value is calculated and processed by using a reference q-axis current calculation module to obtain a q-axis current reference value; Get the d-axis current reference value and motor speed reference , and input the d-axis current reference value, motor speed reference value, q-axis current reference value, load torque estimation value, motor speed feedback value and dq-axis current feedback value into the model prediction speed current controller for prediction processing to obtain the optimal inverter control voltage at the next moment, where: ; The optimal inverter control voltage is modulated and pre-processed by using a drive component to obtain a corresponding output voltage, and the permanent magnet synchronous motor is controlled according to the corresponding output voltage.

[0010] In summary, the non-cascaded permanent magnet synchronous motor model predictive speed current control system and method are intended to overcome the problems of limited bandwidth, complex parameter setting, and insufficient dynamic performance of the traditional cascade control structure in permanent magnet synchronous motor control. By introducing the model predictive speed current controller (MPSCC), the motor speed and current are tracked in the same loop, which greatly reduces the number of parameters that need to be adjusted. Only the parameters of three influencing factors need to be adjusted to give full play to the advantages of model predictive control in solving complex constrained multivariable control problems.

[0011] Specifically, the core components of the system include permanent magnet synchronous motor, current sensor, resolver sensor, saturation function type sliding mode load observer, reference q-axis current calculation module, model prediction speed current controller, PWM modulation and drive module and Clark-Park coordinate transformation module. Among them, the sliding mode load observer effectively alleviates the high-frequency jitter problem by replacing the traditional sign function with a saturation function, improves the accuracy of load torque estimation and the smoothness of the output. The reference q-axis current calculation module calculates the q-axis reference current based on the output of the load observer, combined with the electromagnetic torque equation and torque balance equation of the motor.

[0012] The model-predictive speed current controller is the core of the key technology. It is based on the discretized mathematical model of the permanent magnet synchronous motor, predicts the current and speed at the next moment through the forward Euler discrete equation, and constructs a cost function to optimize the reference voltage vector output of the inverter. The cost function comprehensively considers the weight factors of the d-axis current, q-axis current and speed to ensure fast and accurate tracking control in different operating stages (such as acceleration, steady state, etc.). By bringing all possible voltage vectors of the inverter into the prediction equation and calculating the cost function, the controller can select the optimal voltage vector, thereby realizing non-cascade control and significantly improving the dynamic performance of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic diagram of the structural framework of a non-cascaded permanent magnet synchronous motor model prediction speed and current control system provided by an embodiment of the present invention; Figure 2 It is a control block diagram of a saturation function type sliding mode load observer provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0015] refer to Figure 1 , Figure 2 As shown, the first embodiment of the present invention discloses a non-cascaded permanent magnet synchronous motor model prediction speed current control system, which includes: a permanent magnet synchronous motor, a drive component, a sensor component, a model prediction speed current controller, and a preprocessing component, wherein the input end of the sensor component is electrically connected to the output end of the permanent magnet synchronous motor, the output end of the sensor component is electrically connected to the input end of the preprocessing component, the input end of the model prediction speed current controller is electrically connected to the output end of the preprocessing component and the output end of the sensor component, the output end of the model prediction speed current controller is electrically connected to the input end of the drive component, and the output end of the drive component is electrically connected to the input end of the permanent magnet synchronous motor; The sensor component is used to obtain the rotor position signal and three currents of the permanent magnet synchronous motor, and the preprocessing component is used to obtain the load torque estimation value and q-axis reference current of the permanent magnet synchronous motor; The model-predicted speed current controller is used to perform reference tracking of current and speed according to input feedback data, and output an optimal inverter control voltage; The driving component is used to perform PWM modulation and inversion processing on the optimal inverter control voltage, and transmit the obtained corresponding voltage to the permanent magnet synchronous motor to achieve control of the permanent magnet synchronous motor.

[0016] Preferably, the sensor assembly includes a current sensor, a Clark-Park coordinate transformation module and a resolver sensor, the input end of the current sensor and the input end of the resolver sensor are electrically connected to the output end of the permanent magnet synchronous motor, the output end of the current sensor is electrically connected to the input end of the Clark-Park coordinate transformation module, the output end of the Clark-Park coordinate transformation module is electrically connected to the input end of the model prediction speed current controller, and the output end of the resolver sensor is electrically connected to the input end of the preprocessing component, wherein the current sensor is used to obtain three currents of the permanent magnet synchronous motor, the resolver sensor is used to obtain the rotor position signal of the permanent magnet synchronous motor, the Clark-Park coordinate transformation module is used to convert the three currents into two rotating coordinate systems, and the permanent magnet synchronous motor is a surface-mounted permanent magnet synchronous motor or a built-in permanent magnet synchronous motor.

[0017] Preferably, the preprocessing component includes a sliding mode load observer and a reference q-axis current calculation module, the input end of the sliding mode load observer is electrically connected to the output end of the resolver sensor, the output end of the sliding mode load observer is electrically connected to the input end of the reference q-axis current calculation module and the input end of the model predicted speed current controller, the output end of the reference q-axis current calculation module is electrically connected to the input end of the model predicted speed current controller, wherein the sliding mode load observer is used to estimate the load torque estimate in real time, and the reference q-axis current calculation module is used to calculate the q-axis reference current.

[0018] Preferably, the drive component includes a PWM modulation module and an inverter drive module, the input end of the PWM modulation module is electrically connected to the output end of the model predicted speed current controller, the output end of the PWM modulation module is electrically connected to the input end of the inverter drive module, and the output end of the inverter drive module is electrically connected to the input end of the permanent magnet synchronous motor.

[0019] Specifically, in this embodiment, the non-cascaded permanent magnet synchronous motor model prediction speed current control system realizes efficient and accurate control of the permanent magnet synchronous motor through innovative structural design and control strategy, and significantly improves the dynamic performance and stability of the system. The system comprises a permanent magnet synchronous motor, a drive component, a sensor component, a model prediction speed current controller and a preprocessing component. Among them, the input end of the sensor component is electrically connected to the output end of the permanent magnet synchronous motor, which is used to collect the running status information of the motor in real time; the output end of the sensor component is electrically connected to the input end of the preprocessing component, and the collected raw data is transmitted to the preprocessing component for processing. The output end of the preprocessing component is electrically connected to the input end of the model prediction speed current controller to provide the controller with processed feedback data. The output end of the model prediction speed current controller is electrically connected to the input end of the drive component, and the optimized control signal is transmitted to the drive component. The output end of the drive component is finally electrically connected to the input end of the permanent magnet synchronous motor, and the voltage signal after PWM modulation and inversion processing is applied to the motor to achieve accurate control of the motor.

[0020] The sensor assembly is one of the key parts of the system, which is used to obtain the rotor position signal and three-phase current of the permanent magnet synchronous motor. Specifically, the sensor assembly includes a current sensor, a Clark-Park coordinate transformation module, and a resolver sensor. The input end of the current sensor is electrically connected to the output end of the permanent magnet synchronous motor to collect the three-phase current signal of the motor in real time. The resolver sensor is also electrically connected to the output end of the permanent magnet synchronous motor to obtain the position signal of the motor rotor. The output end of the current sensor is electrically connected to the input end of the Clark-Park coordinate transformation module, and the Clark-Park coordinate transformation module converts the collected three-phase current signal to a two-phase rotating coordinate system (dq axis) for subsequent processing. The output end of the Clark-Park coordinate transformation module is electrically connected to the input end of the model prediction speed current controller to provide the controller with a converted current signal. The output end of the resolver sensor is electrically connected to the input end of the preprocessing component to transmit the rotor position signal to the preprocessing component. Through this structural design, the sensor assembly can efficiently collect the key operating parameters of the motor and provide accurate input data for subsequent control algorithms.

[0021] The preprocessing component plays an important role in the intermediate processing of the system, which includes a sliding mode load observer and a reference q-axis current calculation module. The input end of the sliding mode load observer is electrically connected to the output end of the resolver sensor, receives the rotor position signal, and estimates the load torque estimate in real time based on this. The output end of the sliding mode load observer is electrically connected to the input end of the reference q-axis current calculation module and the input end of the model prediction speed current controller, and transmits the estimated load torque estimate to the subsequent module. The reference q-axis current calculation module calculates the q-axis reference current according to the load torque estimate, and electrically connects its output end to the input end of the model prediction speed current controller to provide a reference current signal to the controller. Through the processing of the preprocessing component, the system can accurately obtain the load torque estimate and the q-axis reference current, providing key feedback information for the optimization control of the model prediction speed current controller.

[0022] The model predictive speed current controller is the core control unit of the present invention, and its input end is electrically connected to the output end of the preprocessing component and the output end of the sensor component to receive processed feedback data. The controller performs reference tracking of current and speed based on the input feedback data, including the actual dq axis current, motor speed, load torque estimation value, and reference current. Through the advanced model predictive control algorithm, the controller can quickly calculate the optimal inverter control voltage and output it to the drive component. This process not only realizes fast and accurate tracking of current and speed, but also significantly improves the dynamic response speed and stability of the system, and reduces the overshoot phenomenon and adjustment time existing in traditional control methods.

[0023] The drive component is responsible for further processing the optimal inverter control voltage output by the model predicted speed current controller and transmitting it to the permanent magnet synchronous motor. The drive component includes a PWM modulation module and an inverter drive module. The input end of the PWM modulation module is electrically connected to the output end of the model predicted speed current controller, receives the control voltage signal output by the controller, and performs PWM modulation on it. The PWM modulated signal is transmitted to the input end of the inverter drive module, and the inverter drive module converts the PWM signal into a voltage signal suitable for the permanent magnet synchronous motor, and applies the voltage signal to the input end of the permanent magnet synchronous motor through its output end, thereby realizing precise drive and control of the motor. Through the efficient processing of the drive component, the system can quickly and accurately apply the optimized control signal to the motor, further improving the control performance of the system.

[0024] In short, the non-cascaded permanent magnet synchronous motor model prediction speed current control system breaks the limitation of mutual restraint between the speed loop and the current loop in the traditional cascade control method through the non-cascade control structure design, and significantly improves the overall bandwidth and dynamic response speed of the system. The introduction of the model prediction speed current controller enables the reference tracking of current and speed to be completed in the same loop, greatly reducing the number of parameters that need to be adjusted and simplifying the debugging process of the control system. In addition, the combination of the sliding mode load observer and the reference q-axis current calculation module provides accurate feedback information for the controller, further improving the control accuracy and stability of the system. It solves the problem of decreased control bandwidth caused by the cascade structure of the traditional finite set prediction current control, and the difficulty of parameter adjustment caused by the mutual influence between the control parameters of the two loops under dual-loop control. Through this innovative control method and system structure. It can achieve efficient and precise control of permanent magnet synchronous motors, which is suitable for surface-mounted and built-in permanent magnet synchronous motors, and is widely used in robots, electric vehicles, aerospace and other fields, with important theoretical and practical application value.

[0025] A second embodiment of the present invention discloses a non-cascaded permanent magnet synchronous motor model prediction speed current control method, characterized in that the method is applied to the non-cascaded permanent magnet synchronous motor model prediction speed current control system as described in any one of the above, comprising: S1, obtaining the rotor position signal and three currents of the permanent magnet synchronous motor collected by the sensor component, and preprocessing the rotor position signal and the three currents respectively to obtain the motor speed feedback value and the dq axis current feedback value; Specifically, step S1 includes: obtaining the current moment collected by the current sensor k The three currents of the permanent magnet synchronous motor , and the Clark-Park coordinate transformation module is used to transform the three currents Perform coordinate transformation to obtain the dq axis current feedback value , dq axis current reference value Includes two d-axis current feedback values ​​in the rotating coordinate system and q-axis current feedback value ; Get the current time collected by the resolver sensor k The rotor position signal of the permanent magnet synchronous motor , and the rotor position signal Perform differential processing to obtain the motor speed feedback value .

[0026] In this embodiment, the operating state information of the permanent magnet synchronous motor, including the rotor position signal and the three-phase current, is first obtained through the sensor assembly. This information is the basis for achieving precise control, so the accuracy of obtaining and processing these signals is directly related to the performance of the entire control system. Specifically, the current sensor collects the three-phase current of the permanent magnet synchronous motor in real time. These current signals reflect the operating state of the motor, but it is not convenient to directly use the three-phase current for control. Therefore, the three-phase current is subjected to coordinate transformation processing through the Clark-Park coordinate transformation module, and is converted from a three-phase stationary coordinate system to a current feedback value under a two-phase rotating coordinate system (dq axis). This conversion process not only simplifies the complexity of the control algorithm, but also makes the current control more intuitive and efficient. The obtained dq axis current feedback value includes a d axis current feedback value and a q axis current feedback value, which correspond to the excitation current and torque current of the motor, respectively, and are key parameters for achieving precise current control.

[0027] At the same time, the resolver sensor collects the rotor position signal of the permanent magnet synchronous motor. The rotor position is an important parameter in motor control, which directly determines the motor's operating state and control strategy. By differentiating the rotor position signal, the actual speed feedback value of the motor can be obtained. This speed feedback value is not only used for speed control, but also provides an important basis for subsequent load torque estimation and current reference value calculation.

[0028] S2, using a sliding mode load observer to observe and process the motor speed feedback value to obtain a load torque estimation value, and using a reference q-axis current calculation module to calculate and process the load torque estimation value to obtain a q-axis current reference value; Specifically, step S2 includes: the expression derivation process of the sliding mode load observer is: establishing the torque equation and motion equation of the permanent magnet synchronous motor, and the mathematical expression is: ,in, is the electromagnetic torque, is the number of magnetic pole pairs, is the permanent magnet flux, is the d-axis inductance, is the q-axis inductance, is the load torque, is the viscous friction coefficient, is the motor rotor mechanical angular velocity, is the moment of inertia; Ignoring viscous friction, the equation of motion is simplified to: ; Assuming that the load is approximately constant within a current control cycle, and the system mechanical motion time constant is greater than the current loop time constant, the state equation with electrical angular velocity and load torque as state variables is obtained based on the torque equation and motion equation: ; Taking the electrical angular velocity and load torque as observation variables, the sliding mode load observer is constructed: , ,in, is the sliding mode gain, is the estimated value of load torque, K is the error gain, is the estimated value of the motor rotor electrical angular velocity, The error threshold is set The equation of the sliding mode load observer and the state equation are subtracted to obtain the observer error equation: , represents the load torque estimation error, For the current moment k The speed error; The speed error As the switching function, the sliding surface is defined as , and based on the convergence condition of generalized sliding mode motion Perform sliding mode reachability analysis, the formula is: ,get Gain in K The value range of is: , For the current moment k The rate of change of velocity error; Based on the sliding mode control law, when it is judged that the approaching sliding mode surface of the sliding mode load observer satisfies When the condition is , we substitute it into the equation of the sliding mode load observer and get: , to obtain the final load torque estimation error ,in, c is a preset constant.

[0029] The calculation formula derivation process of the reference q-axis current calculation module is specifically as follows: ignoring the influence of factors such as friction, and obtaining the motor electromagnetic torque equation and torque balance equation: ; In steady state equilibrium When the d-axis current reference value is used The control strategy is used to obtain the load torque estimate The current in steady state The relationship between , and the steady-state current As the q-axis current reference value .

[0030] In this embodiment, step S2 is one of the key links to realize the non-cascaded permanent magnet synchronous motor model predictive speed current control, which mainly completes the load torque estimation and the calculation of the q-axis current reference value through the sliding mode load observer and the reference q-axis current calculation module. This process not only provides an accurate input signal for the subsequent current control, but also significantly improves the dynamic performance and control accuracy of the system.

[0031] First, the design of the sliding mode load observer is based on the torque equation and motion equation of the permanent magnet synchronous motor; by establishing a mathematical model of the motor, the dynamic behavior of the motor can be accurately described. In order to simplify the model, the influence of viscous friction is ignored, and the motion equation is further simplified. Secondly, in practical applications, it is assumed that the load torque is approximately constant within a current control cycle, and the system mechanical motion time constant is much larger than the current loop time constant. Based on the above torque equation and motion equation, the state equation with electrical angular velocity and load torque as state variables can be obtained. By taking the electrical angular velocity and load torque as observation variables, a sliding mode load observer is constructed; among them, in order to avoid the high-frequency jitter problem near the sliding surface caused by the characteristics of the sign function of the traditional sliding mode control, a continuous function is used instead of a discontinuous sign function near the sliding surface, which can effectively reduce the high-frequency jitter problem and obtain a smoother output, so for In this way, the sliding mode load observer can estimate the change of load torque in real time and provide accurate feedback information for subsequent control.

[0032] Furthermore, the equation of the sliding mode load observer and the state equation are subjected to difference processing to obtain the observer error equation; by selecting the speed error as the switching function and defining the sliding surface as, the sliding mode reachability analysis can be performed based on the generalized sliding mode motion convergence condition; through analysis, the gain can be obtained K This analysis process ensures the stability and convergence of the sliding mode load observer, thereby improving the accuracy of the load torque estimation. Finally, when the sliding mode surface of the sliding mode load observer meets the conditions, it is substituted into the equation of the sliding mode load observer, and the load torque estimation error is finally obtained; the torque observer error converges to 0 in an exponential form, and the convergence speed depends on the feedback coefficient The size of the observer is given by K and By jointly deciding and selecting appropriate control parameters, the observed value can track the actual value. Through the above process, the sliding mode load observer can estimate the change of load torque in real time and accurately, and can respond quickly and provide reliable estimated values ​​even under sudden load changes or complex working conditions. This feature is of great significance for improving the dynamic performance and anti-interference ability of the system.

[0033] In this embodiment, after obtaining the load torque estimate, it is further calculated and processed by the reference q-axis current calculation module to obtain the q-axis current reference value. The calculation formula derivation process of the reference q-axis current calculation module is as follows: Ignore the influence of factors such as friction, and obtain the motor electromagnetic torque equation and torque balance equation. In the steady-state equilibrium state, the control strategy of the d-axis current reference value is adopted to obtain the relationship between the load torque estimate and the current in the steady state, and the current in the steady state is used as the q-axis current reference value. In this way, the reference q-axis current calculation module can dynamically adjust the q-axis current reference value according to the change of the load torque, thereby realizing precise control of the motor current.

[0034] S3, obtain the d-axis current reference value and motor speed reference , and input the d-axis current reference value, motor speed reference value, q-axis current reference value, load torque estimation value, motor speed feedback value and dq-axis current feedback value into the model prediction speed current controller for prediction processing to obtain the optimal inverter control voltage at the next moment, where: ; Specifically, step S3 includes: the process of deriving the mathematical expression of the model prediction speed current controller, specifically: The voltage equation of the permanent magnet synchronous motor is expressed in the synchronous rotating coordinate system as follows: ,in, is the stator resistance, is the motor electrical angular velocity; According to the voltage equation of the permanent magnet synchronous motor, the incremental equation of current and speed is obtained: ; According to the voltage equation of the permanent magnet synchronous motor and the incremental equation of current and speed, the voltage of the permanent magnet synchronous motor component in the synchronous rotating coordinate system is predicted using the previous Euler discrete equation to obtain the current and motor speed feedback value at the next moment. The mathematical expression is: ,in, is the controller control period, R is the stator resistance; The motor speed feedback value at the next moment is compensated and predicted to obtain the compensated motor speed feedback value: , and construct the cost function: ,in, , , They are d-axis current weight factor, q-axis current weight factor and speed weight factor respectively; According to the cost function, the optimal inverter control voltage at the next moment is obtained .

[0035] In this embodiment, the d-axis current reference value and the motor speed reference value are first obtained. These reference values, together with the q-axis current reference value, load torque estimation value, motor speed feedback value, and dq-axis current feedback value obtained in step S2, are input into the model prediction speed current controller as input signals. These input signals provide the controller with comprehensive motor operation status information, so that the controller can predict the optimal control voltage at the next moment based on the current state.

[0036] The derivation process of the model prediction speed current controller is as follows: first, establish the voltage equation of the permanent magnet synchronous motor in the synchronous rotating coordinate system; through the above incremental equation, combined with the voltage equation of the permanent magnet synchronous motor, the previous Euler discrete equation is used to predict the voltage of the motor in the synchronous rotating coordinate system. Specifically, through discretization processing, the prediction expression of the current and motor speed feedback value at the next moment can be obtained. Among them, in order to further improve the prediction accuracy, the motor speed feedback value at the next moment is compensated and predicted to obtain the compensated motor speed feedback value; through the compensation prediction processing, the controller can more accurately reflect the actual operating state of the motor, especially under fast dynamic conditions. This compensation mechanism significantly improves the response speed and stability of the control system. From this, based on the above prediction results, a cost function is constructed, in which the weight factor in this function is set according to specific actual needs. In principle, the weight factor should be c>b>a, because when it is not close to the reference speed, the weight factor c is the largest to ensure that the fastest approach to the reference speed is the main tracking target, and when it is close to the steady state, the steady-state current should be the tracking target. At this time, the current cost function should play a leading role. In i d = 0 control strategy, i q Current should be the main tracking parameter, so the weight factor c>b>a. This cost function can consider the tracking of current and speed at the same time, realize speed tracking and current tracking in the same loop, and complete non-cascade control.

[0037] Finally, according to the principle of minimizing the cost function, the model predictive speed current controller calculates the optimal inverter control voltage at the next moment. This control voltage not only optimizes the current and speed tracking performance of the motor, but also reduces the adjustment time and overshoot of the system through the predictive control algorithm, significantly improving the dynamic performance of the system. The control process of MPSCC is to bring all possible output voltage vectors of the inverter (usually 8) and the actual physical parameters of the motor at the current k moment into the prediction equation, calculate all possible prediction values ​​at k+1 moments, bring the prediction values ​​into the cost function, and select the voltage vector with the smallest cost function as the inverter reference voltage vector output.

[0038] S4, using a drive component to perform modulation preprocessing on the optimal inverter control voltage to obtain a corresponding output voltage, and controlling the permanent magnet synchronous motor according to the corresponding output voltage.

[0039] Specifically, step S4 includes: calling the PWM modulation module to perform space vector pulse width modulation processing on the optimal inverter control voltage to obtain a pulse width modulation signal at the next moment; The inverter drive module is called to invert the pulse width modulation signal at the next moment to obtain the corresponding output voltage, and the corresponding output voltage is transmitted to the permanent magnet synchronous motor to realize the control of the permanent magnet synchronous motor.

[0040] In this embodiment, the PWM modulation module is first called to perform space vector pulse width modulation (SVPWM) processing on the optimal inverter control voltage output by the model predicted speed current controller. Space vector pulse width modulation is an advanced modulation technology that can effectively improve the output voltage utilization of the inverter while reducing the torque pulsation and current harmonics of the motor. Through SVPWM processing, the optimal inverter control voltage is converted into a series of pulse width modulation signals that accurately control the switching state of the inverter. These pulse width modulation signals not only contain the voltage amplitude and frequency information required by the motor, but also reduce the switching loss of the inverter through optimized switching strategies, thereby improving the efficiency and stability of the system.

[0041] Next, the inverter drive module is called to invert the pulse width modulation signal. The inverter drive module is the key link between the control algorithm and the motor hardware. It converts the DC power supply into an AC voltage suitable for the operation of the permanent magnet synchronous motor according to the instructions of the pulse width modulation signal. This process involves precise switch control and voltage conversion to ensure that the motor can receive a voltage signal consistent with the control target. The design of the inverter drive module uses advanced power electronic devices and circuit topology, which can achieve fast dynamic response and precise voltage output while achieving high efficiency and high reliability.

[0042] Finally, the inverter drive module transmits the processed corresponding output voltage to the permanent magnet synchronous motor, and the motor adjusts its operating state according to the received voltage signal, thereby achieving precise speed and current control. This closed-loop control process not only ensures that the motor's operating state can quickly and accurately track the reference value, but also significantly improves the system's dynamic performance and control accuracy through predictive control and optimized modulation strategies.

[0043] In summary, in terms of system architecture, the core of the present invention is the introduction of a non-cascaded model predictive speed current controller (MPSCC), which abandons the limitations of the traditional dual-loop cascade control structure. The controller simultaneously completes the tracking of current and speed in the same loop, and only needs to adjust the parameters of three influencing factors, which greatly reduces the number of parameters that need to be adjusted compared to the traditional dual PID controller. This simplification not only reduces the difficulty of debugging, but also significantly improves the dynamic performance of the system, enabling it to quickly adapt to load changes and dynamic instructions.

[0044] In order to achieve accurate load torque estimation, a saturation function type sliding mode load observer is used. This observer can estimate the change of load torque in real time by establishing the torque equation and motion equation of the motor and combining it with the sliding mode control theory. Compared with the traditional sliding mode control, the system and method use a saturation function to replace the sign function near the sliding surface, which effectively reduces the high-frequency jitter problem, makes the output smoother, and further improves the stability and reliability of the system.

[0045] In addition, the calculation of the reference current is also one of the key links of the present invention. By referring to the q-axis current calculation module, combined with the load torque estimation value and the electromagnetic torque equation of the motor, the system can dynamically adjust the q-axis current reference value. This current reference value calculation method based on load estimation not only improves the accuracy of current control, but also enhances the adaptability of the system under different working conditions, especially under load mutation or complex operating conditions, and can quickly return to steady-state operation.

[0046] In terms of control execution, the next state of the motor is predicted by the model prediction speed current controller, and the cost function is constructed to optimize the control voltage of the inverter. This predictive control method can calculate the optimal control signal in advance, significantly improving the dynamic response speed and stability of the system. At the same time, by reasonably setting the weight factor, the system can flexibly adjust the control target at different operating stages, further optimizing the operating performance of the motor. Finally, the drive component performs PWM modulation and inversion processing on the optimal inverter control voltage, and the system transmits the optimized voltage signal to the permanent magnet synchronous motor to achieve precise control of the motor. This closed-loop control process not only ensures that the operating state of the motor can quickly and accurately track the reference value, but also significantly improves the dynamic performance and control accuracy of the system through predictive control and optimized modulation strategy.

[0047] In short, the beneficial effects of the non-cascaded permanent magnet synchronous motor model prediction speed current control system and method are mainly reflected in the following aspects: First, the non-cascade control structure breaks through the bandwidth limitation of traditional cascade control and significantly improves the dynamic response speed and overall performance of the system; Second, through the combination of sliding mode load observer and model prediction speed current controller, the system can maintain a stable operating state under complex working conditions, and enhances anti-interference ability and adaptability; Third, by simplifying the parameter setting process, the debugging difficulty and cost are reduced, and the practicality and operability of the system are improved.

[0048] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A non-cascaded permanent magnet synchronous motor model prediction speed current control system, characterized in that: include: A permanent magnet synchronous motor, a drive component, a sensor component, a model predicted speed current controller, and a preprocessing component, wherein the input end of the sensor component is electrically connected to the output end of the permanent magnet synchronous motor, the output end of the sensor component is electrically connected to the input end of the preprocessing component, the input end of the model predicted speed current controller is electrically connected to the output end of the preprocessing component and the output end of the sensor component, the output end of the model predicted speed current controller is electrically connected to the input end of the drive component, and the output end of the drive component is electrically connected to the input end of the permanent magnet synchronous motor; The sensor component is used to obtain the rotor position signal and three currents of the permanent magnet synchronous motor, and the preprocessing component is used to obtain the load torque estimation value and q-axis reference current of the permanent magnet synchronous motor; The model-predicted speed current controller is used to perform reference tracking of current and speed according to input feedback data, and output an optimal inverter control voltage; The driving component is used to perform PWM modulation and inversion processing on the optimal inverter control voltage, and transmit the obtained corresponding voltage to the permanent magnet synchronous motor to achieve control of the permanent magnet synchronous motor.

2. The non-cascaded permanent magnet synchronous motor model prediction speed and current control system according to claim 1, characterized in that: The sensor assembly includes a current sensor, a Clar k -Park coordinate transformation module and resolver sensor, the input end of the current sensor and the input end of the resolver sensor are electrically connected to the output end of the permanent magnet synchronous motor, the output end of the current sensor is electrically connected to the input end of the Clark-Park coordinate transformation module, the output end of the Clark-Park coordinate transformation module is electrically connected to the input end of the model prediction speed current controller, the output end of the resolver sensor is electrically connected to the input end of the preprocessing component, wherein the current sensor is used to obtain three currents of the permanent magnet synchronous motor, the resolver sensor is used to obtain the rotor position signal of the permanent magnet synchronous motor, the Clark-Park coordinate transformation module is used to convert the three currents into two rotating coordinate systems, and the permanent magnet synchronous motor is a surface-mounted permanent magnet synchronous motor or a built-in permanent magnet synchronous motor.

3. The non-cascaded permanent magnet synchronous motor model prediction speed and current control system according to claim 2, characterized in that: The preprocessing component includes a sliding mode load observer and a reference q-axis current calculation module, the input end of the sliding mode load observer is electrically connected to the output end of the resolver sensor, the output end of the sliding mode load observer is electrically connected to the input end of the reference q-axis current calculation module and the input end of the model prediction speed current controller, the output end of the reference q-axis current calculation module is electrically connected to the input end of the model prediction speed current controller, wherein the sliding mode load observer is used to estimate the load torque estimate in real time, and the reference q-axis current calculation module is used to calculate the q-axis reference current.

4. The non-cascaded permanent magnet synchronous motor model prediction speed and current control system according to claim 3, characterized in that: The drive component includes a PWM modulation module and an inverter drive module, the input end of the PWM modulation module is electrically connected to the output end of the model prediction speed current controller, the output end of the PWM modulation module is electrically connected to the input end of the inverter drive module, and the output end of the inverter drive module is electrically connected to the input end of the permanent magnet synchronous motor.

5. A non-cascaded permanent magnet synchronous motor model prediction speed current control method, characterized in that: The method is applied to the non-cascaded permanent magnet synchronous motor model prediction speed current control system as claimed in any one of claims 1 to 4, comprising: Obtain the rotor position signal and three currents of the permanent magnet synchronous motor collected by the sensor component, and pre-process the rotor position signal and the three currents respectively to obtain the motor speed feedback value and the dq axis current feedback value; The motor speed feedback value is observed and processed by using a sliding mode load observer to obtain a load torque estimation value, and the load torque estimation value is calculated and processed by using a reference q-axis current calculation module to obtain a q-axis current reference value; Get the d-axis current reference value and motor speed reference , and input the d-axis current reference value, motor speed reference value, q-axis current reference value, load torque estimation value, motor speed feedback value and dq-axis current feedback value into the model prediction speed current controller for prediction processing to obtain the optimal inverter control voltage at the next moment, where: ; The optimal inverter control voltage is modulated and pre-processed by using a drive component to obtain a corresponding output voltage, and the permanent magnet synchronous motor is controlled according to the corresponding output voltage.

6. The non-cascaded permanent magnet synchronous motor model prediction speed and current control method according to claim 5, characterized in that: The rotor position signal and three currents of the permanent magnet synchronous motor collected by the sensor component are obtained, and the rotor position signal and the three currents are preprocessed respectively to obtain the motor speed feedback value and the dq axis current feedback value, specifically: Get the current time collected by the current sensor k The three currents of the permanent magnet synchronous motor , and the Clark-Park coordinate transformation module is used to transform the three currents Perform coordinate transformation to obtain the dq axis current feedback value , dq axis current reference value Includes two d-axis current feedback values ​​in the rotating coordinate system and q-axis current feedback value ; Get the current time collected by the resolver sensor k The rotor position signal of the permanent magnet synchronous motor , and the rotor position signal Perform differential processing to obtain the motor speed feedback value .

7. The non-cascaded permanent magnet synchronous motor model prediction speed and current control method according to claim 6, characterized in that: The derivation process of the sliding mode load observer expression is: The torque equation and motion equation of the permanent magnet synchronous motor are established, and the mathematical expression is: ,in, is the electromagnetic torque, is the number of magnetic pole pairs, is the permanent magnet flux, is the d-axis inductance, is the q-axis inductance, is the load torque, is the viscous friction coefficient, is the motor rotor mechanical angular velocity, is the moment of inertia; Ignoring viscous friction, the equation of motion is simplified to: ; Assuming that the load is approximately constant within a current control cycle, and the system mechanical motion time constant is greater than the current loop time constant, the state equation with electrical angular velocity and load torque as state variables is obtained based on the torque equation and motion equation: ; Taking the electrical angular velocity and load torque as observation variables, the sliding mode load observer is constructed: , ,in, is the sliding mode gain, is the estimated value of load torque, K is the error gain, is the estimated value of the motor rotor electrical angular velocity, is the set error threshold; The equation of the sliding mode load observer and the state equation are subtracted to obtain the observer error equation: , represents the load torque estimation error, For the current moment k The speed error; The speed error As the switching function, the sliding surface is defined as , and based on the convergence condition of generalized sliding mode motion Perform sliding mode reachability analysis, the formula is: ,get Gain in K The value range of is: , For the current moment k The rate of change of velocity error; Based on the sliding mode control law, when it is judged that the approaching sliding mode surface of the sliding mode load observer satisfies When the condition is , we substitute it into the equation of the sliding mode load observer and get: , to obtain the final load torque estimation error ,in, c is a preset constant.

8. The non-cascaded permanent magnet synchronous motor model prediction speed and current control method according to claim 7, characterized in that: The calculation formula derivation process of the reference q-axis current calculation module is specifically as follows: Ignoring the influence of factors such as friction, the motor electromagnetic torque equation and torque balance equation are obtained: ; In steady state equilibrium When the d-axis current reference value is used The control strategy is used to obtain the load torque estimate The current in steady state The relationship between , and the steady-state current As the q-axis current reference value .

9. The non-cascaded permanent magnet synchronous motor model prediction speed and current control method according to claim 8, characterized in that: The derivation process of the mathematical expression of the model prediction speed current controller is as follows: The voltage equation of the permanent magnet synchronous motor is expressed in the synchronous rotating coordinate system as follows: ,in, is the stator resistance, is the motor electrical angular velocity; According to the voltage equation of the permanent magnet synchronous motor, the incremental equation of current and speed is obtained: ; According to the voltage equation of the permanent magnet synchronous motor and the incremental equation of current and speed, the voltage of the permanent magnet synchronous motor component in the synchronous rotating coordinate system is predicted using the previous Euler discrete equation to obtain the current and motor speed feedback value at the next moment. The mathematical expression is: ,in, is the controller control period, R is the stator resistance; The motor speed feedback value at the next moment is compensated and predicted to obtain the compensated motor speed feedback value: , and construct the cost function: ,in, , , They are d-axis current weight factor, q-axis current weight factor and speed weight factor respectively; According to the cost function, the optimal inverter control voltage at the next moment is obtained .

10. The non-cascaded permanent magnet synchronous motor model prediction speed and current control method according to claim 5, characterized in that: The optimal inverter control voltage is modulated and pre-processed by using a drive component to obtain a corresponding output voltage, and the permanent magnet synchronous motor is controlled according to the corresponding output voltage, specifically: Call the PWM modulation module to perform space vector pulse width modulation processing on the optimal inverter control voltage to obtain the pulse width modulation signal at the next moment; The inverter drive module is called to invert the pulse width modulation signal at the next moment to obtain the corresponding output voltage, and the corresponding output voltage is transmitted to the permanent magnet synchronous motor to realize the control of the permanent magnet synchronous motor.

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