A method and system for predictive control of MTPA of permanent magnet synchronous motor with constant parameters

Abstract

The invention discloses a permanent magnet synchronous motor constant parameter MTPA predictive control method and system. The invention uses a speed reference value and a motor feedback speed error as PI adjustment inputs, obtains reference variables through PI adjustment, and calculates d-axis and q-axis reference currents of the permanent magnet synchronous motor when it is working based on the reference variables and d-axis and q-axis current demand equations; establishes a value function based on the d-axis and q-axis reference currents, the value function consists of a total current error, an MTPA curve error and a voltage increment error within Np prediction cycles, and converts the value function into a quadratic programming value function; adds an error term between the real-time MTPA curve of the motor and a set MTPA curve value to the value function, simplifies the calculation method compared with the traditional segmented solution, and provides a system model for solving the value function of the permanent magnet synchronous motor model prediction.

Description

Technical Field

[0001] The present invention relates to the field of permanent magnet synchronous motor drive control, and in particular to a permanent magnet synchronous motor constant parameter MTPA predictive control method and system. Background Art

[0002] The maximum torque current ratio control of permanent magnet synchronous motor is to minimize the motor stator current under the condition of outputting the same electromagnetic torque. The MTPA formula method is one of the most widely used methods. By constructing the Lagrange multiplier method formula between the current and the electromagnetic torque, the square root function between the direct axis d-axis and the quadrature axis q-axis current, or the square root function between the quadrature axis q-axis current and the electromagnetic torque, or the trigonometric function between the current vector and the current vector angle can be obtained.

[0003] However, the formula methods listed above all involve the calculation of square roots and inverse trigonometric functions, which are complex and burdensome to the controller. In actual use, curve fitting or offline table building and online table lookup are usually adopted. When using the curve fitting method, the fitting accuracy depends on the order of the fitting polynomial. The higher the order, the higher the accuracy and the greater the amount of calculation. The table lookup method system needs to store a large amount of offline data, which takes up a lot of storage space, and the table has poor portability. Therefore, there is an urgent need for a simple calculation method that can also predict the control of the permanent magnet synchronous motor model. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a permanent magnet synchronous motor constant parameter MTPA predictive control method and system to solve the problems that the current common calculation method is complex and brings a calculation burden to the controller, other methods occupy a large amount of storage space, and the table has poor portability.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a permanent magnet synchronous motor constant parameter MTPA predictive control method, comprising: using a speed reference value and a motor feedback speed error as PI adjustment inputs, obtaining a reference variable through the PI adjustment, and calculating the d-axis and q-axis reference currents of the permanent magnet synchronous motor when it is working based on the reference variable combined with the d-axis and q-axis current demand equations;

[0008] According to the d-axis and q-axis reference currents, a cost function is established, wherein the cost function is composed of a total current error, an MTPA curve error, and a voltage increment error within Np prediction cycles, and the cost function is converted into a quadratic programming cost function;

[0009] Establish a discrete space current model of a permanent magnet synchronous motor and its first state space model;

[0010] The state space model is combined with the quadratic programming value function to solve the optimal control variables in the future prediction period that meet the system control requirements. The solution specifically includes modifying the first state space model into an extended state model, and modifying the second state space model of the extended state model to obtain a modified permanent magnet synchronous motor model, and bringing the modified permanent magnet synchronous motor model into the quadratic programming value function to obtain the optimal control variables.

[0011] As a preferred solution of the MTPA predictive control method for a permanent magnet synchronous motor with constant parameters described in the present invention, the d-axis and q-axis reference currents of the permanent magnet synchronous motor when working are calculated based on the reference variable combined with the d-axis and q-axis current demand equations, which are expressed as:

[0012]

[0013]

[0014] Among them, i d (k) represents the d-axis reference current, i q (k) represents the q-axis reference current, i N (k) represents the reference variable, represents the motor combination parameters consisting of d-axis inductance, q-axis inductance and flux linkage, i N is the current vector composed of the d-axis current and the q-axis current at time k.

[0015] As a preferred solution of the MTPA predictive control method for a permanent magnet synchronous motor with constant parameters described in the present invention, the cost function is composed of the total current error, the MTPA curve error and the voltage increment error within Np prediction cycles, and is expressed as:

[0016]

[0017] Where Np is the prediction period, Nc is the control period, k represents the current moment, m represents the mth moment starting from moment k, and n represents the nth moment starting from moment k. is the input voltage increment; They are current error weight, MTPA error weight and input voltage increment weight respectively.

[0018] As a preferred solution of the MTPA predictive control method for a permanent magnet synchronous motor of the present invention, a discrete space current model of the permanent magnet synchronous motor and a first state space model thereof are established, wherein the discrete space current model of the permanent magnet synchronous motor is expressed as:

[0019]

[0020]

[0021] The first state space model is expressed as:

[0022]

[0023]

[0024] Where, k is the kth sampling period, i d (k),i q (k),ω m (k),ω m i d (k),ω m i q (k),u d (k),u q (k) are the d-axis current, q-axis current, speed, d-axis voltage and q-axis voltage at the kth cycle respectively.

[0025] As a preferred solution of the MTPA predictive control method for a permanent magnet synchronous motor according to the present invention, the first state space model is modified into an extended state model, which is expressed as:

[0026]

[0027]

[0028] Among them, Δi d (k),Δi q (k),Δω m (k),Δω m i d (k),Δω m i q (k),Δu d (k),Δu q (k) are the d-axis current increment, q-axis current increment, speed increment, speed d-axis current product increment, speed q-axis current product increment, d-axis voltage increment and q-axis voltage increment of the k-th sampling period respectively;

[0029] Modify the second state space model of the extended state model, expressed as:

[0030] x(k+1)=ax(k)+bΔu(k)

[0031] y(k)=cx(k)

[0032] in:

[0033]

[0034]

[0035] The modified permanent magnet synchronous motor model is expressed as:

[0036]

[0037]

[0038] As a preferred solution of the MTPA predictive control method for a permanent magnet synchronous motor with constant parameters described in the present invention, the value function is converted into a quadratic programming value function, including: performing a down-order processing on the value function and simplifying it to obtain a quadratic programming value function, which is expressed as:

[0039]

[0040] As a preferred solution of the MTPA predictive control method for a permanent magnet synchronous motor with constant parameters described in the present invention, the modified permanent magnet synchronous motor model is brought into the quadratic programming value function to obtain the optimal control variable, which is expressed as:

[0041]

[0042] in:

[0043] The output variables of Np prediction periods starting from the initial time k are:

[0044] Y=[y m (k+1) y m (k+2) … y m (k+Np-1) y m (k+Np)] T Np×1

[0045] The reference value of the output variable for Np forecast periods starting from the initial time k is:

[0046] Y*=[y* y* … y*] T Np×1

[0047] The control variable increment of Nc control cycles starting from the initial time k is:

[0048] ΔU=[Δu(k) Δu(k+1) … Δu(k+Nc-1)] T Nc×1

[0049] The error weight of the output variable for Np forecast periods starting from the initial time k is:

[0050]

[0051] The error weights of the input variables for Nc forecast periods starting from the initial time k are:

[0052]

[0053] Intermediate variable matrices F and Φ:

[0054]

[0055] Taking the derivative of ΔU(k), it is expressed as:

[0056]

[0057] Get ΔU(k) ​​within the prediction period, expressed as:

[0058]

[0059] Take the first periodic variable Δu d (k+1),Δu q (k+1) and obtain the d and q axis voltages when the motor is running according to the following formula:

[0060]

[0061] The d-axis and q-axis voltages are applied to the motor to control the motor.

[0062] In a second aspect, the present invention provides a permanent magnet synchronous motor constant parameter MTPA predictive control system, including an input conversion module, which is used to use a speed reference value and a motor feedback speed error as PI adjustment inputs, obtain a reference variable through the PI adjustment, and calculate the d-axis and q-axis reference currents of the permanent magnet synchronous motor when it is working based on the reference variable combined with the d-axis and q-axis current demand equations;

[0063] A function conversion module is used to establish a value function based on the d-axis and q-axis reference currents, wherein the value function is composed of a total current error, an MTPA curve error, and a voltage increment error within Np prediction cycles, and convert the value function into a quadratic programming value function;

[0064] A model building module, used to establish a discrete space current model of a permanent magnet synchronous motor and a first state space model thereof;

[0065] A solution module is used to solve the optimal control variables in a future prediction period that meet the system control requirements through the state space model combined with the quadratic programming value function. The solution specifically includes modifying the first state space model into an extended state model, and modifying the second state space model of the extended state model to obtain a modified permanent magnet synchronous motor model, and bringing the modified permanent magnet synchronous motor model into the quadratic programming value function to obtain the optimal control variables.

[0066] In a third aspect, the present invention provides a computing device, comprising:

[0067] Memory and processor;

[0068] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the permanent magnet synchronous motor constant parameter MTPA predictive control method are implemented.

[0069] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the permanent magnet synchronous motor constant parameter MTPA predictive control method.

[0070] Compared with the prior art, the present invention has the following beneficial effects: the present invention converts the traditional MTPA operating point solution into a two-variable linear equation solution, specifically uses the MTPA operating point current as the current loop reference given current, and uses the error between the motor feedback current value and the MTPA operating point current as one item in the value function, so that the error between the motor current feedback value and the MTPA operating point current is as small as possible; in order to further ensure that the motor obtains maximum torque and minimum current during operation and continuously runs on the MTPA curve, the error term between the real-time MTPA curve of the motor and the set MTPA curve value is added to the value function, which simplifies the calculation method compared with the traditional piecewise solution, and at the same time, provides a system model for solving the permanent magnet synchronous motor model prediction value function. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0072] Figure 1 It is a schematic diagram of the overall process of the MTPA predictive control method of a permanent magnet synchronous motor according to an embodiment of the present invention;

[0073] Figure 2 A schematic diagram of a system control model applicable to the MTPA predictive control method for a permanent magnet synchronous motor according to an embodiment of the present invention;

[0074] Figure 3 A schematic diagram comparing the traditional MTPA formula method and the MPC-MTPA formula method in the MTPA predictive control method for a permanent magnet synchronous motor according to an embodiment of the present invention;

[0075] Figure 4 A schematic diagram showing a comparison of the value functions of a traditional MTPA prediction algorithm and an MPC-MTPA prediction algorithm in a permanent magnet synchronous motor constant parameter MTPA prediction control method according to an embodiment of the present invention;

[0076] Figure 5 It is a schematic diagram of simulation results of the traditional formula method MTPA and the improved MTPA algorithm in the permanent magnet synchronous motor constant parameter MTPA predictive control method according to an embodiment of the present invention;

[0077] Figure 6 A schematic diagram of the speed of a motor after running for 1 second in a permanent magnet synchronous motor constant parameter MTPA predictive control method according to an embodiment of the present invention;

[0078] Figure 7 A schematic diagram of the electromagnetic torque of a motor after running for 1 second in a permanent magnet synchronous motor constant parameter MTPA predictive control method according to an embodiment of the present invention;

[0079] Figure 8 This is an intention of the d-axis current of the motor after running for 1 second in the MTPA predictive control method for a permanent magnet synchronous motor according to an embodiment of the present invention;

[0080] Fig. 9 This is an intention of the q-axis current of a permanent magnet synchronous motor after the motor has run for 1 second in a constant parameter MTPA predictive control method of a permanent magnet synchronous motor described in an embodiment of the present invention. DETAILED DESCRIPTION

[0081] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0082] Example 1

[0083] Reference Figure 1 , is an embodiment of the present invention, and provides a permanent magnet synchronous motor constant parameter MTPA predictive control method, comprising:

[0084] S100: taking the speed reference value and the motor feedback speed error as PI adjustment inputs, obtaining a reference variable through PI adjustment, and calculating the d-axis and q-axis reference currents of the permanent magnet synchronous motor when working according to the reference variable combined with the d-axis and q-axis current demand equations;

[0085] It should be noted that when the permanent magnet synchronous motor MTPA is running, the d-axis and q-axis currents satisfy the equation:

[0086]

[0087] in

[0088] Among them, i d represents the d-axis current, i q represents the q-axis current.

[0089] The d-axis and q-axis currents at any time k can be represented by a unique variable i N (k) is expressed as:

[0090] i N (k) = i q (k)-i d (k) (2)

[0091] Transform formula (1) into the following form:

[0092] (i d (k)-Λ+i q (k))(i d (k)-Λ-i q (k))=Λ 2 (3)

[0093] Substituting equation (2) into equation (3), we get equation (4):

[0094] -(i d (k)-Λ+i q (k))(i N (k)+Λ)=Λ 2 (4)

[0095] Furthermore, the d-axis and q-axis reference currents of the permanent magnet synchronous motor when working are calculated based on the reference variables and the d-axis and q-axis current demand equations, that is, the binary linear equation (5) is obtained by combining equation (4) and equation (2), and the equation (6) is obtained by solving it, which is expressed as:

[0096]

[0097]

[0098] Among them, i d (k) represents the d-axis reference current, i q (k) represents the q-axis reference current, i N (k) represents the reference variable, represents the motor combination parameters consisting of d-axis inductance, q-axis inductance and flux linkage, i N is the current vector composed of the d-axis current and the q-axis current at time k.

[0099] S200: establishing a value function based on the d-axis and q-axis reference currents, the value function being composed of the total current error, the MTPA curve error and the voltage increment error within Np prediction cycles, and converting the value function into a quadratic programming value function;

[0100] Furthermore, the cost function J is composed of the total current error, MTPA curve error and voltage increment error within Np prediction periods, and is expressed as:

[0101]

[0102] Where Np is the prediction period, Nc is the control period, k represents the current moment, m represents the mth moment starting from moment k, and n represents the nth moment starting from moment k. is the input voltage increment; They are current error weight, MTPA error weight and input voltage increment weight respectively.

[0103] It should be noted that the value function in formula (7) is mainly composed of three parts: the total current error, the MTPA curve error and the voltage increment error in Np prediction cycles. The first term, the total current error, is the error between the d-axis and q-axis feedback currents of the permanent magnet synchronous motor during MTPA operation and the MTPA operating point current obtained in step 1. The function of this term is to make the MTPA operating current follow the reference current, i.e., the MTPA operating point current, as much as possible; the second term, the MTPA curve error, is that the relationship between the motor feedback d-axis and q-axis currents satisfies the MTPA formula as much as possible. The function of this term is to further ensure that the permanent magnet synchronous motor operates in the MTPA mode; the third term is the voltage increment error. When the permanent magnet synchronous motor is operating stably, the voltage increment should approach 0 as soon as possible to ensure the steady-state performance and dynamic response of the motor.

[0104] Furthermore, the value function is converted into a quadratic programming value function, including: reducing the value function and simplifying it to obtain the quadratic programming value function.

[0105] It should be noted that the downscaling process first obtains formula (8):

[0106]

[0107] Substituting formula (5) into formula (8), we get formula (9):

[0108]

[0109] When the permanent magnet synchronous motor is running, the motor current is kept on the MTPA curve as much as possible. Formula (9) is a variation of formula (1), so the following formula is valid:

[0110]

[0111] Formula (10) can be equivalently converted to formula (11), reducing the power of the value function from 4 to 2, that is:

[0112]

[0113] Formula (11) can be further simplified as:

[0114]

[0115] in They are the output d-axis current error, q-axis current error, and MTPA curve error weight respectively.

[0116] make

[0117] Formula (12) can finally be transformed into the final quadratic programming value function, expressed as:

[0118]

[0119] It should be noted that the value function is converted into a general quadratic programming value function in order to facilitate the solution of the optimal variables.

[0120] S300: establishing a discrete space current model of a permanent magnet synchronous motor and a first state space model thereof;

[0121] Furthermore, the discrete space current model of the permanent magnet synchronous motor is expressed as:

[0122]

[0123] The first state-space model, that is, the state-space model of equation (14), is based on the d-axis current i d , q-axis current i q , speed ω m , speed and d-axis current product ω m i d , speed and q-axis current product ω m i q As a state variable, the d-axis voltage u d and q-axis voltage uq As the input control variable, the d-axis current i d and q-axis current i q As system output, it is expressed as:

[0124]

[0125]

[0126] Where, k is the kth sampling period, i d (k),i q (k),ω m (k),ω m i d (k),ω m i q (k),u d (k),u q (k) are the d-axis current, q-axis current, speed, d-axis voltage and q-axis voltage at the kth cycle respectively.

[0127] S400: Solving the optimal control variables in the future prediction period that meet the system control requirements through the state space model combined with the quadratic programming value function. The solution specifically includes modifying the first state space model into an extended state model, and modifying the second state space model of the extended state model to obtain a modified permanent magnet synchronous motor model, and bringing the modified permanent magnet synchronous motor model into the quadratic programming value function to obtain the optimal control variables.

[0128] Furthermore, the first state space model is modified into an extended state model. When the system is running stably, the optimal control variables d-axis and q-axis voltage u d 、u q Also remains stable, that is, Δu d and Δu q tends to 0. In order to increase the system input variable Δu d and Δu q To control, we modify equation (15) to:

[0129]

[0130]

[0131] Among them, Δi d (k),Δi q (k),Δω m (k),Δω m i d (k),Δω m i q (k),Δu d (k),Δuq (k) are the d-axis current increment, q-axis current increment, speed increment, speed d-axis current product increment, speed q-axis current product increment, d-axis voltage increment and q-axis voltage increment of the k-th sampling period respectively;

[0132] The second state space model of the modified extended state model, that is, the state space model of formula (16) is expressed as:

[0133] x(k+1)=ax(k)+bΔu(k)

[0134] y(k)=cx(k) (17)

[0135] in:

[0136]

[0137] It should be noted that in order to ensure that the optimal control variables solved can control the permanent magnet synchronous motor to operate near the MTPA curve, formula (13) adds the MTPA curve error to the output variable. In order to solve the optimal variables, the permanent magnet synchronous motor model in formula (17) needs to be modified;

[0138] The modified permanent magnet synchronous motor model is expressed as:

[0139]

[0140] Furthermore, the modified permanent magnet synchronous motor model is brought into the quadratic programming value function to obtain the optimal control variable, that is, substituting formula (18) into formula (13) to express it as:

[0141]

[0142] Among them: the output variable of Np prediction cycles starting from the initial time k is:

[0143] Y=[y m (k+1) y m (k+2) … y m (k+Np-1) y m (k+Np)] T Np×1

[0144] The reference value of the output variable for Np forecast periods starting from the initial time k is:

[0145] Y*=[y* y* … y*] T Np×1

[0146] The control variable increment of Nc control cycles starting from the initial time k is:

[0147] ΔU=[Δu(k) Δu(k+1) … Δu(k+Nc-1)] T Nc×1

[0148] The error weight of the output variable for Np forecast periods starting from the initial time k is:

[0149]

[0150] The error weights of the input variables for Nc forecast periods starting from the initial time k are:

[0151]

[0152] Intermediate variable matrices F and Φ:

[0153]

[0154] Deriving ΔU(k), that is, using formula (19), it is expressed as:

[0155]

[0156] Get ΔU(k) ​​within the forecast period:

[0157]

[0158] Take the first periodic variable Δu d (k+1),Δu q (k+1) and obtain the d and q axis voltages when the motor is running according to the following formula:

[0159]

[0160] The d-axis and q-axis voltages are applied to the motor to control the motor.

[0161] The above is a schematic scheme of a method for predicting and controlling a permanent magnet synchronous motor with constant parameters MTPA in this embodiment. It should be noted that the technical scheme of the system for predicting and controlling a permanent magnet synchronous motor with constant parameters MTPA is the same as the technical scheme of the method for predicting and controlling a permanent magnet synchronous motor with constant parameters MTPA in this embodiment. For details not described in detail in the technical scheme of the predictive control system for the permanent magnet synchronous motor with constant parameters MTPA in this embodiment, please refer to the description of the technical scheme of the method for predicting and controlling a permanent magnet synchronous motor with constant parameters MTPA in this embodiment.

[0162] The permanent magnet synchronous motor constant parameter MTPA predictive control system in this embodiment includes:

[0163] An input conversion module is used to use the speed reference value and the motor feedback speed error as PI adjustment inputs, obtain reference variables through PI adjustment, and calculate the d-axis and q-axis reference currents of the permanent magnet synchronous motor when working based on the reference variables combined with the d-axis and q-axis current demand equations;

[0164] Function conversion module, used to establish a value function based on the d-axis and q-axis reference currents. The value function is composed of the total current error, MTPA curve error and voltage increment error in Np prediction cycles, and converts the value function into a quadratic programming value function;

[0165] A model building module, used to establish a discrete space current model of a permanent magnet synchronous motor and a first state space model thereof;

[0166] A solution module is used to solve the optimal control variables in the future prediction period that meet the system control requirements through a state space model combined with a quadratic programming value function. The solution specifically includes modifying the first state space model into an extended state model, and modifying the second state space model of the extended state model to obtain a modified permanent magnet synchronous motor model, and bringing the modified permanent magnet synchronous motor model into the quadratic programming value function to obtain the optimal control variables.

[0167] This embodiment further provides a computing device, which is applicable to the case of MTPA predictive control of a permanent magnet synchronous motor with constant parameters, and includes:

[0168] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the permanent magnet synchronous motor constant parameter MTPA predictive control method proposed in the above embodiment.

[0169] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for realizing the MTPA predictive control of a permanent magnet synchronous motor with constant parameters as proposed in the above embodiment is implemented.

[0170] The storage medium proposed in this embodiment and the method for realizing the constant parameter MTPA predictive control of a permanent magnet synchronous motor proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0171] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0172] Example 2

[0173] Reference Figure 2-9 Based on the previous embodiment, this embodiment provides an application feasibility demonstration case of a permanent magnet synchronous motor constant parameter MTPA predictive control method and a verification and comparison case of beneficial effects.

[0174] The optimal control variables solved are input into the permanent magnet synchronous motor predictive control simulation system, as shown in X. The simulation motor parameters are set as follows: the number of motor pole pairs is 4; the armature resistance is 0.9585Ω; the q-axis inductance is 12e-03H; the d-axis inductance is 5.25e-03H, and the flux linkage is 0.1827Wb.

[0175] (1) Feasibility verification of the working current calculation method of the MPC-MTPA algorithm of the present invention.

[0176] The traditional MTPA formula method constructs the Lagrangian function of maximum torque and minimum current to solve the reference values ​​of d-axis current and q-axis current when MTPA is working. Figure 2 The traditional formula method and the MPC-MTPA formula method are shown. Figure 2 It can be seen that the MTPA working current calculation method proposed in the MPC-MTPA algorithm does not involve the calculation of square roots and trigonometric functions, which is simple and intuitive. The traditional MTPA predictive control value function usually uses the absolute value of the MTPA curve error as one of the tracking items. When solving the value function, it is necessary to solve it piecewise according to the sign of the curve error, such as Figure 3 shown.

[0177] In order to verify the correctness of the MPC-MTPA formula method for calculating the working current, the proposed algorithm and the traditional formula method were simulated. The simulation results are shown in Figure 5 Shown

[0178] from Figure 5 It can be seen that the proposed algorithm can well track the MTPA curve calculated by the traditional formula method.

[0179] (2) Comparison between the MPC-MTPA algorithm of the present invention and the MTPA based on PI and the MPC control method based on id=0.

[0180] The motor speed is set to 100 rad / s. In order to verify the dynamic performance of the system, the motor is started with a load of 10 N.m. After 0.3s, the load is increased to 20 N.m, and after 0.6s, the load is reduced to 5 N.m. Figure 6-9 They are the simulation results of the motor speed, electromagnetic torque, d-axis current and q-axis current after the motor has run for 1s.

[0181] from Figure 7-Figure 9 It can be seen that under the condition of the same torque, when the system is in a steady state, under the MPC-MTPA algorithm, when the d-axis and q-axis currents change with the system load, the MPC-MTPA algorithm can quickly perform adaptive adjustments and quickly stabilize in the new working condition, indicating that the dynamic performance of MPC-MTPA is better than that of PI-MTPA and id=0 algorithms.

[0182] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for predictive control of a permanent magnet synchronous motor with constant parameters MTPA, characterized in that: The speed reference value and the motor feedback speed error are used as PI adjustment inputs, a reference variable is obtained through the PI adjustment, and the d-axis and q-axis reference currents of the permanent magnet synchronous motor when working are calculated based on the reference variable combined with the d-axis and q-axis current demand equations; Among them, the d-axis and q-axis reference currents of the permanent magnet synchronous motor when working are calculated based on the reference variable combined with the d-axis and q-axis current demand equations, which are expressed as: Among them, i d (k) represents the d-axis reference current, i q (k) represents the q-axis reference current, i N (k) represents the reference variable, represents the motor combination parameters consisting of d-axis inductance, q-axis inductance and flux linkage, i N is the current vector composed of the d-axis current and the q-axis current at time k; According to the d-axis and q-axis reference currents, a cost function is established, wherein the cost function is composed of a total current error, an MTPA curve error, and a voltage increment error within Np prediction cycles, and the cost function is converted into a quadratic programming cost function; The value function is converted into a quadratic programming value function, including: performing a down-order processing on the value function and simplifying it to obtain a quadratic programming value function, which is expressed as: Where Np is the prediction period, Nc is the control period, k represents the current moment, m represents the mth moment starting from moment k, and n represents the nth moment starting from moment k. is the input voltage increment; Establish a discrete space current model of a permanent magnet synchronous motor and its first state space model; The state space model is combined with the quadratic programming value function to solve the optimal control variables in the future prediction period that meet the system control requirements. The solution specifically includes modifying the first state space model into an extended state model, and modifying the second state space model of the extended state model to obtain a modified permanent magnet synchronous motor model, and bringing the modified permanent magnet synchronous motor model into the quadratic programming value function to obtain the optimal control variables.

2. The MTPA predictive control method for a permanent magnet synchronous motor according to claim 1, characterized in that: The cost function is composed of the total current error, MTPA curve error and voltage increment error in Np prediction cycles, and is expressed as: Where Np is the prediction period, Nc is the control period, k represents the current moment, m represents the mth moment starting from moment k, and n represents the nth moment starting from moment k. is the input voltage increment; They are current error weight, MTPA error weight and input voltage increment weight respectively.

3. The MTPA predictive control method for a permanent magnet synchronous motor according to claim 2, characterized in that: A permanent magnet synchronous motor discrete space current model and its first state space model are established, wherein the permanent magnet synchronous motor discrete space current model is expressed as: The first state space model is expressed as: Where, k is the kth sampling period, i d (k),i q (k),ω m (k),ω m i d (k),ω m i q (k),u d (k),u q (k) are the d-axis current, q-axis current, speed, speed-d-axis current product, speed-q-axis current product, d-axis voltage and q-axis voltage at the kth cycle respectively.

4. The MTPA predictive control method for a permanent magnet synchronous motor according to claim 3, characterized in that: The first state space model is modified into an extended state model, which is expressed as: Among them, Δi d (k),Δi q (k),Δω m (k),Δω m i d (k),Δω m i q (k),Δu d (k),Δu q (k) are the d-axis current increment, q-axis current increment, speed increment, speed d-axis current product increment, speed q-axis current product increment, d-axis voltage increment and q-axis voltage increment of the k-th sampling period respectively; Modify the second state space model of the extended state model, expressed as: x(k+1)=ax(k)+bΔu(k) y(k)=cx(k) in: The modified permanent magnet synchronous motor model is expressed as:

5. The MTPA predictive control method for a permanent magnet synchronous motor according to claim 4, characterized in that: Substituting the modified permanent magnet synchronous motor model into the quadratic programming value function, the optimal control variables are obtained, which are expressed as: in: The output variables of Np prediction periods starting from the initial time k are: Y=[y m (k+1)y m (k+2) … y m (k+Np-1)y m (k+Np)] T Np×1 The reference value of the output variable for Np forecast periods starting from the initial time k is: Y*=[y* y* … y*] T Np×1 The control variable increment of Nc control cycles starting from the initial time k is: ΔU=[Δu(k) Δu(k+1) … Δu(k+Nc-1)] T Nc×1 The error weight of the output variable for Np forecast periods starting from the initial time k is: The error weights of the input variables for Nc forecast periods starting from the initial time k are: Intermediate variable matrices F and Φ: Taking the derivative of ΔU(k), it is expressed as: Get ΔU(k) ​​within the prediction period, expressed as: Take the first periodic variable Δu d (k+1),Δu q (k+1) and obtain the d and q axis voltages when the motor is running according to the following formula: The d-axis and q-axis voltages are applied to the motor to control the motor.

6. A system using the MTPA predictive control method for a permanent magnet synchronous motor according to claim 1, characterized in that: include: An input conversion module is used to use a speed reference value and a motor feedback speed error as PI adjustment inputs, obtain a reference variable through the PI adjustment, and calculate the d-axis and q-axis reference currents of the permanent magnet synchronous motor when working according to the reference variable combined with the d-axis and q-axis current demand equations; A function conversion module is used to establish a value function based on the d-axis and q-axis reference currents, wherein the value function is composed of a total current error, an MTPA curve error, and a voltage increment error within Np prediction cycles, and convert the value function into a quadratic programming value function; A model building module, used to establish a discrete space current model of a permanent magnet synchronous motor and a first state space model thereof; A solution module is used to solve the optimal control variables in a future prediction period that meet the system control requirements through the state space model combined with the quadratic programming value function. The solution specifically includes modifying the first state space model into an extended state model, and modifying the second state space model of the extended state model to obtain a modified permanent magnet synchronous motor model, and bringing the modified permanent magnet synchronous motor model into the quadratic programming value function to obtain the optimal control variables.

7. An electronic device comprising: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the permanent magnet synchronous motor constant parameter MTPA predictive control method described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the permanent magnet synchronous motor constant parameter MTPA predictive control method according to any one of claims 1 to 5.

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