A predictive current control method for a permanent magnet synchronous motor

Abstract

The present invention relates to the field of motor control technology and specifically provides a method for predictive current control of a permanent magnet synchronous motor (PMSC). The method comprises the following steps: establishing the basic mechanism equations of the inner and outer loops in the PMSC control of the permanent magnet synchronous motor; introducing a lumped disturbance term and a current ripple term into the cost function of the inner loop to improve the robustness of the MPCC to mismatches in inductance, permanent magnet flux linkage, and resistance parameters; and designing a strong tracking extended-dimensional Kalman filter torque observer in the outer loop to reduce the impact of load torque disturbances and sensor measurement noise on motor control performance. The present invention can simultaneously enhance the robustness of the MPCC to disturbances such as model internal parameter mismatch and model external uncertain load torque.

Description

Technical Field

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

[0002] Permanent magnet synchronous motors (PMSMs) are widely used in industry. To improve the performance and efficiency of PMSM drive systems, model predictive current control (MPCC) has become a research hotspot in the field of PMSM control, thanks to its suitability for handling multi-objective constraints and excellent dynamic performance. Traditional MPCC algorithms rely on accurate model parameters. However, during actual PMSM operation, copper losses, iron losses, and eddy current losses in the permanent magnets cause motor temperature rise, resulting in nonlinear variations in the permanent magnet flux and stator resistance with temperature. Under heavy loads, the load current is high, and as the current increases, the iron core saturates, causing a gradual decrease in stator inductance. In addition to mismatches in the PMSM model's internal parameters (inductance, permanent magnet flux, and resistance), external disturbances (such as load torque disturbances and speed sensor measurement noise) can significantly affect model accuracy. These adverse factors, both internal and external to the model, can severely impact MPCC control performance. Summary of the Invention

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

[0004] To achieve the above object, the technical solution created by the present invention is implemented as follows:

[0005] The present invention provides a method for predictive current control of a permanent magnet synchronous motor, comprising:

[0006] S1: Establish the cost function of the inner loop and the torque equation of the outer loop based on MPCC control;

[0007] S2: The lumped disturbance term and current ripple term are introduced 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 unstable switching frequency. The cost function after introducing the lumped disturbance term and current ripple term is for:

[0008] ;

[0009] in, express The d-axis reference current value at the moment, express The q-axis reference current value at time t, Indicates after one-step delay compensation The predicted value of the d-axis current at time t, Indicates after one-step delay compensation The predicted value of the q-axis current at time t, express The estimated value of the lumped disturbance on the d-axis at time instant, express The estimated value of the lumped disturbance on the q-axis at time q, 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 t, Represents the current limiting term;

[0010] 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:

[0011] ;

[0012] 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, Indicates 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 estimated value of the exogenous disturbance is increased by a constant coefficient.

[0013] Preferably, in S1, the cost function after one-step delay compensation is established based on MPCC control for:

[0014] .

[0015] Preferably, in S1, the torque equation of the outer loop established based on MPCC control is:

[0016] ;

[0017] in, Indicates the uncertain load torque of the motor rotor.

[0018] Preferably, the parameter mismatch includes inductance mismatch, flux linkage mismatch and resistance mismatch.

[0019] Preferably, the current error caused by parameter mismatch is:

[0020] ;

[0021] 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 the flux linkage, Indicates the electrical angular velocity of the motor rotor.

[0022] Preferably, based on the current error caused by parameter mismatch, the adaptive rate of the lumped disturbance term is designed to be:

[0023] ;

[0024] in, express The estimated value of the lumped disturbance on the time d axis, express The estimated value of the lumped disturbance on the q-axis at time q, 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 t, express The predicted value of the q-axis current at time t, represents the gain coefficient of the lumped disturbance term.

[0025] Preferably, the expression of the current ripple term is:

[0026] ;

[0027] in, Represents the gain factor of the current ripple term.

[0028] 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 follows:

[0029] ;

[0030] in, Represents the estimated value of the motor rotor mechanical angular velocity The derivative of

[0031] Estimated value of exogenous disturbance The adaptive law is:

[0032] ;

[0033] The estimated value of the exogenous disturbance Expanding to a new dimension in the state space, we obtain the extended-dimensional Kalman filter torque observer.

[0034] Preferably, the method further includes: the expanded dimension Kalman filter torque observer adopts a strong tracking design.

[0035] Preferably, the process of performing strong tracking by the extended dimension Kalman filter torque observer includes:

[0036] Calculate the prediction residual of the extended dimension Kalman filter torque observer for torque estimation :

[0037] ;

[0038] in, express The control input at the moment, express System output at the moment, express The posterior estimated state at time t;

[0039] Forecast residuals The covariance matrix of To update:

[0040] ;

[0041] in, is a constant between 0 and 1;

[0042] Define the fading factor for:

[0043] ;

[0044] 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 , Indicates trace operation;

[0045] Based on the fading factor The prior error covariance matrix is calculated as:

[0046] ;

[0047] in, express The prior error covariance matrix at time t;

[0048] Using the prior error covariance matrix Perform strong tracking Kalman filter iteration:

[0049] ;

[0050] 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.

[0051] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0052] By introducing a lumped disturbance term and a current ripple term into the inner-loop cost function and designing corresponding adaptive laws, this method eliminates steady-state current errors caused by mismatches in inductance, permanent magnet flux, and resistance parameters, while also improving transient current errors caused by unstable switching frequency. In the presence of parameter mismatch, the present invention achieves current tracking without steady-state errors, reduces the jitter of the axis reference current, and effectively minimizes the total harmonic distortion of the three-phase current, enabling the system to maintain precise current control despite the uncertainties of internal parameter variations.

[0053] The strong tracking extended-dimensional Kalman filter torque observer designed in the outer loop of this invention treats errors caused by improper noise covariance matrix settings and encoder measurement noise as total disturbances. An adaptive law is designed to introduce these errors into the state variables as new dimensions, enhancing the robustness of the outer loop in steady state and mitigating the impact of load torque disturbances and sensor measurement noise on motor control performance. Furthermore, a fading factor is introduced through strong tracking processing to balance the weight between robustness and tracking performance, achieving strong tracking of torque estimation when the load torque changes suddenly.

[0054] Compared with the traditional Kalman filter torque observer which assumes that the process noise covariance matrix and the measurement noise covariance matrix are both known, the strong tracking expanded dimension Kalman filter torque observer of the present invention can be used in practical applications with complex working conditions, and can enhance the robustness and stability in the torque tracking process. At the same time, the strong tracking design ensures that the rapidity of torque tracking is maintained while the state space dimension is improved. The present invention introduces a fading factor to effectively balance the weight between the system robustness and tracking performance. When the system is in a steady state, it focuses on robustness. When the system is in a dynamic process after a sudden change in load torque, it focuses on the strong tracking of torque estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The accompanying drawings, which constitute part of the present invention, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0056] Figure 1 1 is a structural block diagram of a permanent magnet synchronous motor system using a permanent magnet synchronous motor predictive current control method provided by an embodiment of the present invention;

[0057] Figure 2 is a design flow chart of a method for predictive current control of a permanent magnet synchronous motor provided by an embodiment of the present invention;

[0058] Figure 3 3. It is a comparison diagram of simulation results of q-axis reference current and actual current of the traditional cost function and the improved cost function of the present invention under the condition of parameter mismatch provided by an embodiment of the present invention;

[0059] Figure 43. A comparison diagram of three-phase current waveform simulation results of a cost function provided by an embodiment of the present invention and an improved cost function of the present invention;

[0060] Figure 5 3. A comparison diagram of torque estimation simulation results of various algorithms after a sudden load torque is applied, provided in accordance with an embodiment of the present invention;

[0061] Figure 6 3 is a comparison chart of torque estimation simulation results of various algorithms under parameter mismatch conditions provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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 use associated similar element numbers. In the following embodiments, many detailed descriptions are intended to enable the present invention to be better understood. 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. This is to avoid the core part of the present invention being overwhelmed by too much description. For those skilled in the art, it is not necessary to describe these related operations in detail. They can fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0063] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other to form various implementation methods. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various orders in the description and the drawings are only for the purpose of clearly describing a certain embodiment and are not intended to be a required order, unless otherwise specified that a certain order must be followed.

[0064] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are 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 therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, features defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0065] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art can understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0066] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments.

[0067] In one embodiment of the present invention, a method for predictive current control of a permanent magnet synchronous motor is provided. Figure 1 As shown in , it can be applied to permanent magnet synchronous motor systems for MPCC control, achieving high-precision and high-robustness control of permanent magnet synchronous motors under complex working conditions. Figure 2 As shown in Figure 2, the specific process of predictive current control for the permanent magnet synchronous motor system is as follows:

[0068] S1: Based on the permanent magnet synchronous motor (PMSM) mechanism model, we constructed an inner-loop cost function for optimizing current control and an outer-loop torque equation for observing load torque. These functions facilitate subsequent precise control and disturbance compensation, thereby improving the performance and stability of the entire motor drive system.

[0069] First, the stator voltage equation of the inner ring of the permanent magnet synchronous motor is established as:

[0070] (1)

[0071] in, 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 The values are the same in surface-mount permanent magnet synchronous motors, so they are used uniformly in the following text. express, represents the electrical angular velocity of the motor rotor, represents the permanent magnet flux of the motor, Indicates the motor stator resistance.

[0072] The core idea of Model Predictive Current Control (MPCC) is to minimize the difference between the predicted current and the reference current by finding the minimum value of the cost function, thereby achieving precise control of the motor current. In practical applications, in order to compensate for the delay in the system, a cost function after one-step delay compensation is established. for:

[0073] (2)

[0074] in, express The d-axis reference current value at the moment, express The q-axis reference current value at time t, and is the ideal current value calculated by the motor control strategy, Indicates after one-step delay compensation The predicted value of the d-axis current at time t, Indicates after one-step delay compensation The predicted value of the q-axis current at time t, Indicates the current limit item. When the phase current amplitude is greater than the limit value, Take infinity; otherwise Take 0.

[0075] For a surface-mounted permanent magnet synchronous motor, the torque equation of the outer loop established based on MPCC control is:

[0076] (3)

[0077] in, Represents the electromagnetic torque of the motor rotor, Indicates the uncertain load torque of the motor rotor, Indicates the mechanical angular velocity of the motor rotor, represents the motor rotor damping coefficient, Indicates the motor rotor moment of inertia.

[0078] Due to the tight coupling between the outer and inner loops, uncertain load torque disturbances in the outer loop directly impact the inner loop's current control accuracy and dynamic performance. A sudden increase in load torque can cause a transient increase in motor current, triggering overcurrent protection or affecting stable motor operation. Therefore, to improve the robustness and control accuracy of motor drive systems, real-time load torque observation is necessary so that compensation can be incorporated into the control strategy, achieving precise motor control and stable operation. Accurate load torque estimation provides useful feedforward information for the inner loop current control, optimizing the performance of the entire control system.

[0079] S2: For the cost function of the inner loop, a lumped disturbance term and a current ripple term are introduced to improve the robustness of the MPCC to parameter mismatches of the inductance, permanent magnet flux, and resistance, so that the control system can maintain high-performance operation in the presence of parameter deviations. Specifically, in actual motor control systems, the motor parameters used by the controller (such as inductance, permanent magnet flux, and resistance) often have certain mismatch errors with the actual physical parameters of the motor. Parameter mismatch will cause model steady-state errors, affecting the accuracy and stability of motor control. The current error caused by parameter mismatch can be expressed as:

[0080] (4)

[0081] 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 magnetic flux.

[0082] To solve the problem of 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 the adaptive rate of the lumped disturbance for this disturbance as follows:

[0083] (5)

[0084] in, express The estimated value of the lumped disturbance on the time d axis, express The estimated value of the lumped disturbance on the q-axis at time q, 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 t, express The predicted value of the q-axis current at time t, Represents the gain coefficient of the lumped disturbance term. , and design its adaptive law as:

[0085] (6)

[0086] in, Indicates the gain coefficient to be adjusted The maximum value allowed, and is a constant coefficient between 0 and 1, Indicates the motor's given angular velocity, It indicates the angular velocity measured by the encoder in the motor system, reflecting the relationship between the actual operating speed of the motor and the expected speed. The relative error in angular velocity characterizes the degree of deviation in motor speed. By compensating the estimated values of the lumped disturbances on the d- and q-axes into the cost function, the model can avoid the steady-state current error caused by mismatches in the inductance, permanent magnet flux linkage, and resistance parameters.

[0087] Gain coefficient for lumped disturbance term , through the above adaptive law, the gain coefficient can be dynamically adjusted according to the size of the relative error of angular velocity. The closer it is to 0, that is, the closer the motor speed is to the given value, the closer the gain coefficient is to its maximum allowable value, thereby enhancing the disturbance compensation capability; on the contrary, when the angular velocity relative error is When it is large, the gain coefficient should be appropriately reduced to avoid overcompensation causing system oscillation.

[0088] In addition to the steady-state error caused by parameter mismatch, actual motor control systems also suffer from transient current errors caused by unstable switching frequency, namely current ripple. Current ripple can reduce the smoothness of motor operation, affect control accuracy, and may even cause additional losses and heating problems in the motor. To effectively suppress 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:

[0089] (7)

[0090] in, 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 t, Represents the gain factor of the current ripple term, designed The adaptive law is:

[0091] (8)

[0092] in, Indicates the gain coefficient to be adjusted The maximum value allowed. From the above formula, it can be seen that the current ripple gain and the lumped disturbance gain The adaptive law has the same expression form, but has different allowable maximum values. The designed adaptive law can limit the change rate of the gain coefficient and the relative error of the angular velocity in a nonlinear way. The closer it is to 0, the closer the gain coefficient is to the maximum allowed value.

[0093] After the lumped disturbance term and current ripple term are introduced into the cost function, the cost function can be rewritten as:

[0094] (9)

[0095] 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 traditional MPCC to model internal parameters. First, a lumped disturbance term is introduced to eliminate the current steady-state error caused by parameter mismatch; secondly, a current ripple term is introduced to improve the current transient error caused by the unstable switching frequency. Taking into account the calculation speed limit of the hardware in actual implementation, the present invention designs both the lumped disturbance term and the current ripple term in incremental form. Each calculation is iterated based on 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 take effect when the relative error of the angular velocity falls within a certain range, effectively avoiding the compensation amount overshoot phenomenon that may be caused by the motor starting and stopping or when the given angular velocity suddenly changes.

[0096] The above has dealt with the parameter mismatch of the inner loop, but the uncertain load torque disturbance of the outer loop and the encoder measurement noise, the process noise inside the system and other factors will affect the reference current output effect. The traditional Kalman filter torque observer assumes that the process noise covariance matrix and the measurement noise covariance matrix are both known, but in actual applications 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 unfavorable factors such as improper noise covariance matrix settings and encoder measurement noise as exogenous disturbances. Therefore, by introducing 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 can be obtained as follows:

[0097] (10)

[0098] in, Represents the estimated value of the motor rotor mechanical angular velocity The derivative of Represents the estimated value of the uncertain load torque and the estimated value of the design exogenous disturbance The adaptive law is:

[0099] (11)

[0100] in, The error term representing the estimated value of the exogenous disturbance has a constant gain.

[0101] The estimated value of the exogenous disturbance Expanding to a new dimension in the state space, the expanded dimension Kalman filter torque observer is obtained as:

[0102] (12)

[0103] 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, Indicates the system output, represents the system matrix, , represents the input control matrix, , represents the output control matrix, .

[0104] Since the estimated value of the total disturbance is introduced as a new dimension in the state variable, the robustness and stability of the torque tracking process will be enhanced. However, the increase in the state space dimension also weakens the rapidity of torque tracking. To resolve this contradiction, the embodiment of the present invention performs strong tracking processing on the expanded 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:

[0105] Calculate the prediction residual of the extended dimension Kalman filter torque observer for torque estimation :

[0106] (13)

[0107] in, express The control input at the moment, express System output at the moment, express The posterior estimated state at time t;

[0108] Forecast residuals The covariance matrix of To update:

[0109] (14)

[0110] in, is a constant between 0 and 1;

[0111] Define the fading factor for:

[0112] (15)

[0113] in, 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, express The posterior error covariance matrix at time , Indicates trace operation.

[0114] Based on the fading factor The prior error covariance matrix is calculated as:

[0115] (16)

[0116] in, express The prior error covariance matrix at time t.

[0117] Using the prior error covariance matrix Perform strong tracking Kalman filter iteration:

[0118] (17)

[0119] in, express The prior estimated state at time , express The posterior estimated state at time , express The Kalman gain at the moment measures the impact of the new information on the state estimation. express The posterior error covariance matrix at the moment reflects the uncertainty of the state estimation. Represents the identity matrix.

[0120] After each iterative update, the estimated value of the load torque disturbance at the current moment can be output. When the system is in steady state operation, the prediction residual Smaller, at this time Taking the lower limit of 1, without introducing a strong tracking effect, the focus is on the robustness of the system to ensure that it can effectively resist the influence of various disturbances and noises under stable working conditions. When the load torque changes suddenly, the predicted residual The value of will suddenly change. When it is greater than 1, the weight of the new information is increased, and more emphasis will be placed on strong tracking, which can quickly respond to changes in load torque, adjust the system control strategy in time, and ensure stable operation of the motor.

[0121] In order to verify the effectiveness of the cost function designed by the present invention, the present invention compares the improvement of the designed cost function in eliminating steady-state errors and improving ripples with the traditional cost function under the same simulation conditions. Figure 3 As shown, the q-axis reference current of the traditional cost function and the improved cost function proposed by the present invention under the condition of parameter mismatch is shown. and actual current From the simulation results, it can be seen that the improved cost function not only effectively reduces the jitter of the q-axis reference current, but also achieves tracking without steady-state error in the case of mismatch of inductance, flux linkage and stator resistance, so that the system can still maintain precise current control under the uncertainty of internal parameter changes.

[0122] like Figure 4 As shown, the three-phase current waveform simulation results of the traditional cost function and the improved cost function proposed in the present invention are shown. 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.

[0123] In order to verify the effectiveness of the strong tracking and extended dimensionality Kalman filter method designed in the present invention, the present invention compares the torque estimation performance of the traditional Romberg algorithm, the traditional Kalman filter algorithm and the strong tracking and extended dimensionality Kalman filter algorithm proposed in the embodiment of the present invention under the same simulation conditions.

[0124] like Figure 5 As shown in FIG, the torque estimation simulation results after a sudden addition of a load torque of 5 N·m at 1 s are shown. It can be seen that among the various algorithms, the strong tracking extended dimension Kalman filter algorithm proposed in the present invention has the best tracking effect, which is reflected in the shortest transient response time and does not cause overshoot.

[0125] like Figure 6 As shown in the figure, the torque estimation simulation results of each algorithm under parameter mismatch are shown. The setting of parameter mismatch and Figure 3 It can be seen that among all the algorithms, the proposed strong tracking extended dimension Kalman filter algorithm has good steady-state performance, which is reflected in the minimum fluctuation of the output estimated torque in steady state and the smoothest output estimated torque curve; in the case of parameter mismatch, the proposed strong tracking extended dimension Kalman filter algorithm also has the shortest recovery time and the lowest transient amplitude.

[0126] In short, the above description is only a preferred embodiment of this specification and is not intended to limit the scope of protection of this specification. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this specification shall be included in the scope of protection of this specification.

[0127] The systems, devices, modules, or units described in one or more of the above embodiments may be implemented by a computer chip or entity, or by a product having a certain function. 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 smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0128] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0129] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0130] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. 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 the lumped disturbance term and the 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 unstable switching frequency. The cost function after introducing the lumped disturbance term and the current ripple term is: for: ； in, express The d-axis reference current value at the moment, express The q-axis reference current value at time t, Indicates after one step of delay compensation The predicted value of the d-axis current at time t, Indicates after one step of delay compensation The predicted value of the q-axis current at time t, express The estimated value of the lumped disturbance on the d-axis at time instant, express The estimated value of the lumped disturbance on the q-axis at time q, 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 t, 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, Indicates 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 estimated value of the exogenous disturbance is increased by a constant coefficient.

2. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, wherein: 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, wherein: In S1, the torque equation of the outer loop established based on MPCC control is: ； in, Indicates the uncertain load torque of the motor rotor.

4. The method for predictive current control of a permanent magnet synchronous motor according to claim 1, wherein: 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 the 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 time d axis, express The estimated value of the lumped disturbance on the q-axis at time q, 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 t, express The predicted value of the q-axis current at time t, 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, wherein: 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, wherein: 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 follows: ； 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, wherein: 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, wherein: The process of strong tracking by the extended dimension Kalman filter torque observer includes: Calculate the prediction residual of the torque estimation by the extended dimension Kalman filter torque observer : ； in, express The control input at the moment, express System output at the moment, express The posterior estimated state at time t; Forecast residuals The covariance matrix of To update: ； in, is a constant between 0 and 1; Define the fading 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 , Indicates trace operation; Based on the fading factor The prior error covariance matrix is calculated as: ； in, express The prior error covariance matrix at time t; 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.

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