Predictive current control method for permanent magnet synchronous motor

Abstract

The invention relates to the technical field of motor control, and particularly provides a permanent magnet synchronous motor predictive current control method, which comprises the following steps of: establishing a basic mechanism equation of an inner ring and an outer ring in permanent magnet synchronous motor MPCC control, and introducing a lumped disturbance term and a current ripple term into a cost function of the inner ring, the robustness of the MPCC to mismatch of inductance, permanent magnet flux linkage and resistance parameters is improved; and a strong tracking dimension expansion Kalman filtering torque observer is designed on an outer ring, so that the influence of load torque disturbance and sensor measurement noise on the control performance of the motor is reduced. According to the method, the robustness of the MPCC on disturbance such as model internal parameter mismatch and model external uncertain load torque can be enhanced at the same time.

Description

Technical Field

[0001] The present invention belongs to the technical field of motor control, and particularly relates to a predictive current control method for a permanent magnet synchronous motor. Background Art

[0002] Permanent magnet synchronous motors have been widely used in industry. To improve the performance and efficiency of permanent magnet synchronous motor drive systems, Model Predictive Current Control (MPCC) has become a research hotspot in the field of permanent magnet synchronous motor control due to its advantages of being suitable for handling multi-objective constraints and having good dynamic performance. Traditional MPCC algorithms rely on accurate model parameters. However, during the actual operation of permanent magnet synchronous motors, copper loss, iron loss, and eddy current loss in permanent magnets will cause the motor temperature to rise, and the permanent magnet flux linkage and stator resistance will change nonlinearly with temperature. Under heavy load conditions, the load current is large, and the iron core will saturate as the current increases, resulting in a gradual decrease in the stator inductance. In addition to the mismatch of internal parameters (inductance, permanent magnet flux linkage, and resistance) of the permanent magnet synchronous motor model, external model disturbances (such as load torque disturbances and speed sensor measurement noise) will also significantly affect the accuracy of the model. These internal and external adverse factors of the model will seriously affect the control performance of MPCC. Summary of the Invention

[0003] In view of this, the present invention aims to provide a predictive current control method for a permanent magnet synchronous motor, which can simultaneously enhance the robustness of MPCC to internal parameter mismatches of the model and external uncertain load torques and other disturbances, and helps to achieve effective MPCC control of the permanent magnet synchronous motor under complex external working conditions.

[0004] To achieve the above object, the technical solution of the present invention is realized as follows: The present invention provides a predictive current control method for a permanent magnet synchronous motor, including: S1: Establish a cost function for the inner loop and a torque equation for the outer loop based on MPCC control; S2: Introduce a lumped disturbance term and a current ripple term into the cost function of the inner loop. The lumped disturbance term is used to compensate for the current error caused by parameter mismatch, and the current ripple term is used to compensate for the transient error caused by the non-fixed switching frequency; the cost function after introducing the lumped disturbance term and the current ripple term is: ; wherein, represents the reference current value of the d-axis at time represents the reference current value of the q-axis at time represents after one-step delay compensation The predicted value of the d-axis current at the moment, Indicates after one-step delay compensation The predicted value of the q-axis current at the moment, Indicates The estimated value of the lumped disturbance of the d-axis at the moment, Indicates The estimated value of the lumped disturbance of the q-axis at the moment, Indicates The compensation value of the d-axis current ripple at the moment, Indicates The compensation value of the q-axis current ripple at the moment, Indicates the current limiting term; Introduce exogenous disturbances into the torque equation of the outer loop, and expand the estimated value of the exogenous disturbance into a state variable to construct an extended Kalman filter torque observer. The state space equation of the extended Kalman filter torque observer is: ; Among them, Indicates the derivative of the system state , , Indicates the estimated value of the mechanical angular velocity of the motor rotor, Indicates the estimated value of the uncertain load torque, Indicates the estimated value of the exogenous disturbance, Indicates the control input, , Indicates the mechanical angular velocity of the motor rotor, Indicates the electromagnetic torque of the motor rotor, Indicates the system output, Indicates the system matrix, , Indicates the input control matrix, , Indicates the output control matrix, , Indicates the damping coefficient of the motor rotor, Indicates the moment of inertia of the motor rotor, Indicates the error term gain constant coefficient of the estimated value of the exogenous disturbance.

[0005] Preferably, in S1, based on MPCC control, establish a cost function after one-step delay compensation For: .

[0006] Preferably, in S1, the torque equation of the outer loop established based on MPCC control is: ; Among them, Indicates the uncertain load torque of the motor rotor.

[0007] Preferably, the parameter mismatch includes inductance mismatch, flux linkage mismatch, and resistance mismatch.

[0008] Preferably, the current error caused by the parameter mismatch is: ; Wherein, Indicates the d-axis current error caused by the parameter mismatch, Indicates the q-axis current error caused by the parameter mismatch, Indicates the sampling period of the inner loop, Indicates the motor inductance, Indicates the mismatch error of the inductance, Indicates the motor stator resistance, Indicates the mismatch error of the resistance, Indicates the moment Of the d-axis current, Indicates the moment Of the q-axis current, Indicates the moment Of the d-axis voltage, Indicates the moment Of the q-axis voltage, Indicates the motor permanent magnet flux linkage, Indicates the mismatch error of the flux linkage, Indicates the electrical angular velocity of the motor rotor.

[0009] Preferably, based on the current error caused by the parameter mismatch, the adaptive rate of the lumped disturbance term is designed as: ; Wherein, Indicates The estimated value of the lumped disturbance on the d-axis at the moment, Indicates The estimated value of the lumped disturbance on the q-axis at the moment, Indicates The updated estimated value of the lumped disturbance on the d-axis at the moment, Indicates The updated estimated value of the lumped disturbance on the q-axis at the moment, Indicates The predicted value of the d-axis current at the moment, Indicates The predicted value of the q-axis current at the moment, Indicates the gain coefficient of the lumped disturbance term.

[0010] Preferably, the expression of the current ripple term is: ; Wherein, The gain coefficient representing the current ripple term.

[0011] Preferably, an exogenous disturbance is introduced into the torque equation of the outer loop established in S1, and the torque equation of the outer loop with the exogenous disturbance term introduced can be obtained as: ; Wherein, represents the estimated value of the mechanical angular velocity of the motor rotor derivative of; estimated value of the exogenous disturbance The adaptive law of is: ; The estimated value of the exogenous disturbance is expanded to a new dimension in the state space, and an augmented Kalman filter torque observer is obtained.

[0012] Preferably, it further includes: The augmented Kalman filter torque observer adopts a strong tracking design.

[0013] Preferably, the process of the augmented Kalman filter torque observer performing strong tracking includes: Calculating the prediction residual of the augmented Kalman filter torque observer for torque estimation : ; Wherein, represents the control input at time, represents the system output at time, represents the posterior estimation state at time; Updating the covariance matrix of the prediction residual : ; Wherein, is a constant between 0 and 1; Define the fading factor as: ; Wherein, is a constant greater than or equal to 1, represents the process noise covariance matrix, represents the measurement noise covariance matrix, represents the posterior error covariance matrix at time, represents the trace operation; Based on the fading factor The calculated prior error covariance matrix is as follows: ; Among them, represents the prior error covariance matrix at time Using the prior error covariance matrix to perform strong tracking Kalman filter iteration: ; Among them, represents the prior estimated state at time represents the posterior estimated state at time represents the Kalman gain at time represents the posterior error covariance matrix at time represents the identity matrix.

[0014] Compared with the prior art, the present invention can achieve the following beneficial effects: By introducing a lumped disturbance term and a current ripple term into the inner-loop cost function and designing a corresponding adaptive law, the present invention can eliminate the current steady-state error caused by the mismatch of inductance, permanent magnet flux linkage, and resistance parameters, and simultaneously improve the current transient error caused by the non-fixed switching frequency. In the case of parameter mismatch, the present invention can achieve current tracking without steady-state error, reduce the jitter of the shaft reference current, and effectively reduce the total harmonic distortion of the three-phase current, enabling the system to maintain accurate current control under uncertain factors of internal parameter changes.

[0015] The strong tracking extended Kalman filter torque observer designed in the outer loop of the present invention regards the errors caused by improper setting of the noise covariance matrix, encoder measurement noise, etc. as total disturbances, and designs an adaptive law to introduce them into the state variables as new dimensions, enhancing the robustness of the outer loop in the steady state and reducing the influence of load torque disturbance and sensor measurement noise on the motor control performance. In addition, by introducing a fading factor through strong tracking processing to balance the weights between robustness and tracking performance, strong tracking of torque estimation can be achieved when the load torque suddenly changes.

[0016] Compared with the traditional Kalman filter torque observer which assumes that both the process noise covariance matrix and the measurement noise covariance matrix are known, the strong tracking augmented Kalman filter torque observer of the present invention can be applied in practical applications with complex working conditions, enhancing the robustness and stability during torque tracking. At the same time, the strong tracking design ensures that while the state space dimension is increased, the rapidity of torque tracking is also maintained. The present invention introduces a fading factor to effectively balance the weights between system robustness and tracking performance, focusing on robustness when the system is in a steady state and on strong tracking of torque estimation during the dynamic process after a sudden change in load torque. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings forming a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments and descriptions thereof are used to explain the present invention and do not unduly limit the present invention. In the drawings: Figure 1 is a block diagram of a permanent magnet synchronous motor system applying the permanent magnet synchronous motor predictive current control method according to an embodiment of the present invention; Figure 2 is a design flow chart of the permanent magnet synchronous motor predictive current control method according to an embodiment of the present invention; Figure 3 is a comparison diagram of simulation results of the q-axis reference current and the actual current of the traditional cost function and the improved cost function of the present invention under parameter mismatch according to an embodiment of the present invention; Figure 4 is a comparison diagram of simulation results of the three-phase current waveforms of the cost function and the improved cost function of the present invention according to an embodiment of the present invention; Figure 5 is a comparison diagram of simulation results of torque estimation of each algorithm after a sudden increase in load torque according to an embodiment of the present invention; Figure 6 is a comparison diagram of simulation results of torque estimation of each algorithm under parameter mismatch according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not constitute a limitation to the present invention. Similar elements in different embodiments are labeled with related similar element numbers. In the following embodiments, many details are described to enable a better understanding of the present invention. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, or methods. In some cases, some operations related to the present invention are not shown or described in the specification in order to avoid the core part of the present invention being overwhelmed by excessive description. For those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0019] It should be noted that, without conflict, the embodiments and features in the embodiments of the present invention can be combined with each other to form various embodiments. At the same time, the steps or actions in the method description can also be adjusted in the order that is obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for clearly describing a certain embodiment and do not mean that they are the necessary orders, unless it is stated that a certain order must be followed.

[0020] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation to the present invention. In addition, terms such as "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, the meaning of "a plurality" is two or more.

[0021] In the description of the present invention, it should be noted that unless otherwise clearly specified and defined, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be a direct connection or an indirect connection through an intermediate medium, and it may be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0022] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0023] In an embodiment of the present invention, a method for predicting current control of a permanent magnet synchronous motor is provided. As Figure 1 shown, it can be applied to a permanent magnet synchronous motor system for MPCC control to achieve high-precision and high-robustness control of the permanent magnet synchronous motor under complex working conditions. As Figure 2 shown, the specific process of predicting current control for the permanent magnet synchronous motor system is as follows: S1: Based on the mechanism model of a permanent magnet synchronous motor (PMSM), an inner-loop cost function for optimizing current control and an outer-loop torque equation for observing load torque are respectively constructed, which is convenient for subsequent precise control and disturbance compensation, thereby improving the performance and stability of the entire motor drive system.

[0024] First, the stator voltage equation of the inner loop of the permanent magnet synchronous motor is established as: (1) Where represents the d-axis voltage, represents the q-axis voltage, represents the d-axis current, represents the q-axis current, represents the d-axis inductance, represents the q-axis inductance, and are equal in value in a surface-mounted permanent magnet synchronous motor, so they are uniformly represented by subsequently, represents the electrical angular velocity of the motor rotor, represents the magnetic flux of the motor permanent magnet, represents the stator resistance of the motor.

[0025] The core idea of Model Predictive Current Control (MPCC) is to minimize the difference between the predicted current and the reference current by minimizing the cost function, thereby achieving precise control of the motor current. In practical applications, in order to compensate for the delay phenomenon in the system, a cost function after one-step delay compensation is established as follows: (2) where represents the reference current value of the d-axis at time represents the reference current value of the q-axis at time and are the ideal current values calculated by the control strategy of the motor, represents the predicted value of the d-axis current at time after one-step delay compensation, represents the predicted value of the q-axis current at time after one-step delay compensation, represents the current limiting term. When the phase current amplitude is greater than the limit value, takes infinity; otherwise takes 0.

[0026] For the surface-mounted permanent magnet synchronous motor, the torque equation of the outer loop established based on MPCC control is: (3) where represents the electromagnetic torque of the motor rotor, represents the uncertain load torque of the motor rotor, represents the mechanical angular velocity of the motor rotor, represents the damping coefficient of the motor rotor, represents the moment of inertia of the motor rotor.

[0027] Due to the close coupling relationship between the outer loop and the inner loop, the uncertain load torque disturbance of the outer loop will directly affect the current control accuracy and dynamic performance of the inner loop. When the load torque suddenly increases, it will cause the motor current to increase instantaneously, which may trigger overcurrent protection or affect the stable operation of the motor. Therefore, in order to improve the robustness and control accuracy of the motor drive system, it is necessary to observe the load torque in real time so as to compensate it in the control strategy, thereby achieving precise control and stable operation of the motor. By accurately estimating the load torque, useful feedforward information can be provided for the inner loop current control, optimizing the performance of the entire control system.

[0028] S2: For the cost function of the inner loop, a lumped disturbance term and a current ripple term are introduced into it to improve the robustness of MPCC against the mismatches of inductor, permanent magnet flux linkage, and resistance parameters, enabling the control system to maintain high-performance operation under parameter deviations. Specifically, in an actual motor control system, there are often certain mismatch errors between the motor parameters (such as inductor, permanent magnet flux linkage, and resistance) used by the controller and the actual physical parameters of the motor. Parameter mismatch will cause steady-state errors in the model, affecting the accuracy and stability of motor control. Then, the current error caused by parameter mismatch can be expressed as: (4) where, represents the d-axis current error caused by parameter mismatch, represents the q-axis current error caused by parameter mismatch, represents the sampling period of the inner loop, represents the motor inductor, represents the mismatch error of the inductor, represents the motor stator resistance, represents the mismatch error of the resistance, represents the time of the d-axis current, represents the time of the q-axis current, represents the time of the d-axis voltage, represents the time of the q-axis voltage, represents the motor permanent magnet flux linkage, represents the mismatch error of the flux linkage.

[0029] To solve the problem of the current steady-state error caused by the above parameter mismatch, the embodiment of the present invention regards the current error caused by the mismatch as a lumped disturbance and designs an adaptive rate for this disturbance as: (5) where, represents the estimated value of the lumped disturbance on the d-axis at time represents the estimated value of the lumped disturbance on the q-axis at time represents the updated estimated value of the lumped disturbance on the d-axis at time represents the updated estimated value of the lumped disturbance on the q-axis at time represents the predicted value of the d-axis current at time represents the predicted value of the q-axis current at time Denote the gain coefficient of the lumped disturbance term. For the gain coefficient of the lumped disturbance term , design its adaptive law as: (6) where denotes the gain coefficient to be tuned of the maximum allowable value, and are constant coefficients between 0 and 1, denotes the given angular velocity of the motor, denotes the angular velocity measured by the encoder in the motor system, reflecting the relationship between the actual operating speed and the desired speed of the motor, denotes the relative error of the angular velocity, characterizing the deviation degree of the motor speed. Compensating the estimated values of the lumped disturbances on the d-axis and q-axis into the cost function can avoid the current steady-state error caused by the mismatch of inductance, permanent magnet flux linkage, and resistance parameters from the model.

[0030] For the gain coefficient of the lumped disturbance term , through the above adaptive law, the gain coefficient can be dynamically adjusted according to the magnitude of the relative error of the angular velocity. When the relative error of the angular velocity is closer to 0, that is, when the motor speed is closer to the given value, the gain coefficient is closer to its maximum allowable value, thereby enhancing the disturbance compensation ability; conversely, when the relative error of the angular velocity is large, the gain coefficient is appropriately reduced to avoid system oscillation caused by overcompensation.

[0031] In addition to the steady-state error caused by parameter mismatch, there is also a current transient error, that is, current ripple, caused by the non-fixed switching frequency in the actual motor control system. The current ripple will reduce the smooth operation of the motor, affect the control accuracy, and may even cause additional losses and heating problems of the motor. To effectively suppress the current ripple, the embodiment of the present invention also introduces a current ripple term into the cost function of the inner loop. The expression of the current ripple term is: (7) where denotes the compensation value of the d-axis current ripple at time denotes the compensation value of the q-axis current ripple at time denotes the gain coefficient of the current ripple term. Design the adaptive law as: (8) where denotes the gain coefficient to be tuned of the maximum allowable value. It can be seen from the above formula that the gain of the current ripple term And the lumped disturbance term gain has the same expression form of the adaptive law, but has different allowable maximum values. The designed adaptive law can limit the change rate of the gain coefficient in a non-linear manner, and the relative error of the angular velocity is closer to 0, the gain coefficient is closer to the allowable maximum value.

[0032] After introducing the lumped disturbance term and the current ripple term into the cost function, the cost function can be rewritten as: (9) It should be noted that the cost function designed in the embodiment of the present invention can effectively improve the problem of poor robustness of the traditional MPCC to the internal parameters of the model. First, the lumped disturbance term is introduced to eliminate the current steady-state error caused by parameter mismatch; secondly, the current ripple term is introduced to improve the current transient error caused by the non-fixed switching frequency. Considering the calculation speed limitation of the hardware in actual execution, the present invention designs both the lumped disturbance term and the current ripple term in an incremental form, and each calculation is iterated on the basis of the previous calculation, avoiding recalculation and effectively ensuring the rapidity of the cost function calculation; finally, the present invention designs an adaptive law for the gain coefficients in the lumped disturbance term and the current ripple term, so that these two terms only play a role when the relative error of the angular velocity falls within a certain interval, effectively avoiding the overshoot phenomenon of the compensation amount that may be caused when the motor starts or stops or the given angular velocity suddenly changes.

[0033] The above has processed the parameter mismatch of the inner loop, but factors such as the uncertain load torque disturbance in the outer loop, the encoder measurement noise, and the process noise inside the system will all affect the reference current output effect. The traditional Kalman filter torque observer assumes that both the process noise covariance matrix and the measurement noise covariance matrix are known, but in the actual application with complex working conditions, inappropriate noise settings will make the Kalman filter unable to guarantee its performance. Therefore, the embodiment of the present invention also introduces exogenous disturbances into the torque equation of the outer loop, and regards the errors caused by improper setting of the noise covariance matrix, encoder measurement noise and other adverse factors as exogenous disturbances Therefore, by introducing exogenous disturbances into the torque equation of the outer loop established in S1, the torque equation of the outer loop with exogenous disturbance terms can be obtained as: (10) Wherein, represents the estimated value of the mechanical angular velocity of the motor rotor the derivative of, represents the estimated value of the uncertain load torque, and designs the estimated value of the exogenous disturbance The adaptive law of is: (11) Wherein, The error term gain constant system representing the estimated value of the exogenous disturbance.

[0034] The estimated value of the exogenous disturbance is expanded into a new dimension in the state space, and the extended Kalman filter torque observer is obtained as: (12) where represents the system state derivative of , represents the estimated value of the mechanical angular velocity of the motor rotor, represents the estimated value of the uncertain load torque, represents the estimated value of the exogenous disturbance, represents the control input, , represents the mechanical angular velocity of the motor rotor, represents the electromagnetic torque of the motor rotor, represents the system output, represents the system matrix, , represents the input control matrix, , represents the output control matrix, .

[0035] Since the estimated value of the total disturbance is introduced as a new dimension in the state variables, the robustness and stability in the torque tracking process are enhanced, but the rapidity of torque tracking is weakened by the increase in the state space dimension. To solve this contradiction, the embodiment of the present invention performs strong tracking processing on the extended Kalman filter model. The core idea is to dynamically balance the weights of historical data and new data according to the real-time state of the system during the torque estimation process. The specific implementation steps are as follows: Calculate the prediction residual of the extended Kalman filter torque observer for torque estimation : (13) where represents the control input at time represents the system output at time represents the posterior estimation state at time; Update the covariance matrix of the prediction residual : (14) where is a constant between 0 and 1; Define the fading factor as: (15) where is a constant greater than or equal to 1, used to adjust the lower limit of the fading factor, represents the process noise covariance matrix, represents the measurement noise covariance matrix, represents the posterior error covariance matrix at time represents the trace operation.

[0036] Based on the fading factor calculate the prior error covariance matrix as: (16) where represents the prior error covariance matrix at time

[0037] Use the prior error covariance matrix to perform strong tracking Kalman filter iteration: (17) where represents the prior estimated state at time represents the posterior estimated state at time represents the Kalman gain at time, measuring the influence degree of the innovation on the state estimation, represents the posterior error covariance matrix at time, reflecting the uncertainty of the state estimation, represents the identity matrix.

[0038] After each iteration update, the estimated value of the load torque disturbance at the current time can be output. When the system is in steady-state operation, the prediction residual is small, and at this time take the lower limit 1, without introducing strong tracking effect, mainly focusing on the robustness of the system to ensure that it can effectively resist the influence of various disturbances and noises under stable working conditions. And when the load torque suddenly changes, the value of the prediction residual will mutate accordingly, and at this time is greater than 1, the weight of the innovation is increased, and more attention will be paid to strong tracking performance, which can quickly respond to the change of the load torque, timely adjust the control strategy of the system, and ensure the stable operation of the motor.

[0039] To verify the effectiveness of the cost function designed by the present invention, under the same simulation conditions, the present invention compares the improvement of the designed cost function over the traditional cost function in terms of steady-state error elimination and ripple improvement. As Figure 3 shown, the q-axis reference current of the traditional cost function and the improved cost function proposed by the present invention under parameter mismatch is and the actual current presented. It can be seen that the improved cost function not only effectively reduces the jitter of the q-axis reference current, but also achieves steady-state error-free tracking under the mismatch of inductance, flux linkage, and stator resistance, enabling the system to maintain precise current control under uncertain internal parameter changes.

[0040] As Figure 4 shown, the simulation results of the three-phase current waveforms of the traditional cost function and the improved cost function proposed by the present invention are presented. THD is the total harmonic distortion of the phase current. It can be seen that the improved cost function effectively reduces the total harmonic distortion of the three-phase current.

[0041] To verify the effectiveness of the strong tracking augmented Kalman filter method designed by the present invention, under the same simulation conditions, the present invention compares the torque estimation performance of the traditional Romberg algorithm, the traditional Kalman filter algorithm, and the strong tracking augmented Kalman filter algorithm proposed in the embodiments of the present invention.

[0042] As Figure 5 shown, the torque estimation simulation results after suddenly applying a 5 N·m load torque at 1 s are presented. It can be seen that among the algorithms, the strong tracking augmented Kalman filter algorithm proposed by the present invention has the best tracking effect, manifested as the shortest transient response time and no overshoot.

[0043] As Figure 6 shown, the torque estimation simulation results of each algorithm under parameter mismatch are presented. The parameter mismatch settings are the same as Figure 3 . It can be seen that among the algorithms, the proposed strong tracking augmented Kalman filter algorithm has good steady-state performance, reflected as the smallest output estimated torque fluctuation at steady state and the smoothest output estimated torque curve; when there is parameter mismatch, the proposed strong tracking augmented Kalman filter algorithm also has the shortest recovery time and the lowest transient amplitude.

[0044] In summary, the above is only a preferred embodiment of this specification and is not intended to limit the protection scope of this specification. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this specification shall be included within the protection scope of this specification.

[0045] The systems, devices, modules or units described in one or more of the above embodiments may be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0046] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0047] Each embodiment in this specification is described in a progressive manner, and the same or similar parts among the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment.

[0048] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for predictive current control of a permanent magnet synchronous motor, characterized in that: include: S1: Establish the cost function of the inner loop and the torque equation of the outer loop based on MPCC control; S2: Introduce lumped disturbance term and current ripple term into the cost function of the inner loop. The lumped disturbance term is used to compensate for the current error caused by parameter mismatch, and the current ripple term is used to compensate for the transient error caused by the non-fixed switching frequency. The cost function after introducing the lumped disturbance term and current ripple term is for: ； in, express The d-axis reference current value at time, express The q-axis reference current value at time, Indicates after one step of delay compensation The predicted value of the d-axis current at time, Indicates after one step of delay compensation The predicted value of the q-axis current at time, express The estimated value of the lumped disturbance on the d-axis at time, express The estimated value of the lumped disturbance on the q-axis at time, express The compensation value of the d-axis current ripple at the moment, express The compensation value of the q-axis current ripple at time, Represents the current limiting term; An exogenous disturbance is introduced into the torque equation of the outer loop, and the estimated value of the exogenous disturbance is expanded into a state variable to construct an extended-dimensional Kalman filter torque observer. The state space equation of the extended-dimensional Kalman filter torque observer is: ； in, Indicates system status The derivative of , represents the estimated value of the motor rotor mechanical angular velocity, represents the estimated value of the uncertain load torque, represents the estimated value of the exogenous disturbance, represents the control input, , Indicates the mechanical angular velocity of the motor rotor, Represents the electromagnetic torque of the motor rotor, Represents the system output, represents the system matrix, , represents the input control matrix, , represents the output control matrix, , represents the motor rotor damping coefficient, represents the motor rotor moment of inertia, The error term that represents the estimate of the exogenous disturbance is gained by a constant coefficient.

2. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, characterized in that: In S1, the cost function after one-step delay compensation is established based on MPCC control. for: 。 3. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, characterized in that: In S1, the torque equation of the outer loop established based on MPCC control is: ； in, Indicates the motor rotor has uncertain load torque.

4. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, characterized in that: Parameter mismatch includes inductance mismatch, flux linkage mismatch and resistance mismatch.

5. The method for predictive current control of a permanent magnet synchronous motor according to claim 4, characterized in that: The current error caused by parameter mismatch is: ； in, represents the d-axis current error caused by parameter mismatch, represents the q-axis current error caused by parameter mismatch, represents the sampling period of the inner loop, represents the motor inductance, represents the mismatch error of the inductor, represents the motor stator resistance, represents the resistor mismatch error, Indicates time The d-axis current, Indicates time The q-axis current, Indicates time The d-axis voltage, Indicates time The q-axis voltage, represents the permanent magnet flux of the motor, represents the mismatch error of flux linkage, Indicates the electrical angular velocity of the motor rotor.

6. The method for predictive current control of a permanent magnet synchronous motor according to claim 5, characterized in that: According to the current error caused by parameter mismatch, the adaptive rate of the lumped disturbance term is designed as: ； in, express The estimated value of the lumped disturbance on the d-axis at time, express The estimated value of the lumped disturbance on the q-axis at time, express The estimated value of the lumped disturbance on the d-axis updated at all times, express The estimated value of the q-axis lumped disturbance updated at all times, express The predicted value of the d-axis current at time, express The predicted value of the q-axis current at time, represents the gain coefficient of the lumped disturbance term.

7. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, characterized in that: The expression of the current ripple term is: ； in, Represents the gain factor of the current ripple term.

8. The method for predictive current control of a permanent magnet synchronous motor according to claim 3, characterized in that: By introducing the exogenous disturbance into the torque equation of the outer loop established in S1, the torque equation of the outer loop with the exogenous disturbance term introduced can be obtained as: ； in, Represents the estimated value of the motor rotor mechanical angular velocity The derivative of The estimated value of the exogenous disturbance The adaptive law is: ； The estimated value of the exogenous disturbance Expanding to a new dimension in the state space, the expanded-dimensional Kalman filter torque observer is obtained.

9. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, characterized in that: Also includes: The extended dimension Kalman filter torque observer adopts a strong tracking design.

10. The method for predictive current control of a permanent magnet synchronous motor according to claim 9, characterized in that: The process of strong tracking by the extended dimension Kalman filter torque observer includes: Calculate the prediction residual of the extended dimension Kalman filter torque observer for torque estimation : ； in, express The control input at the moment, express System output at time, express The posterior estimated state at time t; For the prediction residual The covariance matrix of To update: ； in, is a constant between 0 and 1; Define the fade factor for: ； in, is a constant greater than or equal to 1, represents the process noise covariance matrix, represents the measurement noise covariance matrix, express The posterior error covariance matrix at time , represents the trace operation; Based on the fading factor The prior error covariance matrix is ​​calculated as: ； in, express The prior error covariance matrix at time; Using the prior error covariance matrix Perform strong tracking Kalman filter iteration: ； in, express The prior estimated state at time , express The posterior estimated state at time , express The Kalman gain at time t, express The posterior error covariance matrix at time , Represents the identity matrix.

Images