Permanent magnet synchronous motor off-line parameter estimation method and system based on algebraic differential method

Abstract

The application relates to the technical field of motor control, and specifically discloses a permanent magnet synchronous motor offline parameter estimation method and system based on an algebraic differential method, which comprises the following steps: obtaining a speed control hyperlocal model and a second-order kinematic equation of a permanent magnet synchronous motor according to an initial electromechanical kinematic equation of the permanent magnet synchronous motor; performing Laplace transformation on the second-order kinematic equation, introducing an angle low-pass filter, and obtaining a complex frequency domain equation of the permanent magnet synchronous motor; obtaining a two-dimensional equation group composed of unknown coefficients of the permanent magnet synchronous motor through derivation, time domain conversion and integration of the complex frequency domain equation of the permanent magnet synchronous motor; and according to the positive and negative rotation of the permanent magnet synchronous motor under the speed instruction, substituting the obtained angle and q-axis current data into the two-dimensional equation group for solving, so that the value of a non-physical proportional factor can be obtained. The application can effectively estimate the value of the non-physical proportional factor in the model-free speed control of the permanent magnet synchronous motor based on the hyperlocal model, improve the dynamic performance of the model-free speed control of the permanent magnet synchronous motor, and enhance the robustness of the control system.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of motor control, and particularly relates to a permanent magnet synchronous motor offline parameter estimation method and system based on an algebraic differential method. BACKGROUND

[0002] The permanent magnet synchronous motor (PMSM) is favored more and more in small and medium power occasions and high-voltage and high-power applications such as industrial robots, aerospace, etc. due to its advantages of high efficiency, high power factor and easy control. The model-free deadbeat predictive speed control of the permanent magnet synchronous motor only uses the input and output data of the system, that is, it realizes the control of the motor through real-time observation and prediction of the system state. The model-free deadbeat predictive speed control has the advantages of high-precision control, fast response, no need for accurate motor parameters, strong robustness and simple structure and easy realization. However, if the non-physical proportional factor in the model-free deadbeat predictive speed controller is selected to be greatly different from the actual motor system parameters, the control performance will be affected, such as poor system dynamic response, large overshoot or unstable system, etc. Many times, the parameters provided by the motor manufacturer are not accurate or are not provided, and it is sometimes difficult to accurately calculate the moment of inertia of the load. In order to ensure the control accuracy and improve the motor performance, it is necessary to identify the non-physical proportional factor in the model-free deadbeat predictive speed control in engineering practice. The parameter identification methods are mainly divided into two types: offline identification and online identification. The offline identification mainly includes DC current delay, AC static method and vector control method, etc. However, this kind of identification method needs to be carried out when the motor is kept in a stable state. The online identification mainly includes least square method and its extension algorithm, model reference adaptive method, genetic algorithm and swarm intelligence optimization algorithm, parameter identification method based on artificial neural network and extended Kalman filter method, etc. However, this kind of identification has high requirements for hardware (such as processor performance) and software, and the algorithm is complex and needs real-time calculation. The above parameter identification methods mainly identify the conventional parameters of the motor one by one, and are not suitable for the estimation of the non-physical proportional factor. SUMMARY

[0003] Therefore, the application provides a permanent magnet synchronous motor offline parameter estimation method based on an algebraic differential method, which can accurately estimate the value of the non-physical proportional factor only by using the angle and current information of the motor, solve the problem of parameter value selection in the model-free deadbeat predictive speed control, and improve the control performance of the permanent magnet synchronous motor servo system.

[0004] To achieve the above-mentioned tasks, the application provides the following technical solutions:

[0005] The application provides a permanent magnet synchronous motor offline parameter estimation method based on algebraic differentiation method, and the estimation value of non-physical scale factor can be obtained by transforming electromechanical kinematic equation of the permanent magnet synchronous motor, substituting angle and current information, and solving linear equations about motor parameters, and the steps are as follows:

[0006] S1, obtaining a speed control hyper-local model and a second-order kinematic equation of the permanent magnet synchronous motor according to an initial electromechanical kinematic equation of the permanent magnet synchronous motor;

[0007] S2, performing Laplace transformation on the second-order kinematic equation, introducing an angle low-pass filter, and obtaining a complex frequency domain equation of the permanent magnet synchronous motor;

[0008] S3, obtaining a two-dimensional equation group composed of unknown coefficients of the permanent magnet synchronous motor by derivation, time domain conversion and integration on the complex frequency domain equation of the permanent magnet synchronous motor;

[0009] S4, substituting the obtained angle and q-axis current data into the two-dimensional equation group for solving according to the speed instruction positive and negative rotation of the permanent magnet synchronous motor, and the value of the non-physical scale factor can be obtained.

[0010] Further, the step of S1, obtaining a speed control hyper-local model and a second-order kinematic equation of the permanent magnet synchronous motor according to an initial electromechanical kinematic equation of the permanent magnet synchronous motor, specifically comprises the following steps:

[0011] The initial electromechanical kinematic equation of the permanent magnet synchronous motor is:

[0012]

[0013] Wherein, θ is a mechanical angle of the permanent magnet synchronous motor; ω m is a mechanical angular velocity of the permanent magnet synchronous motor; J n is a total rotational inertia of the permanent magnet synchronous motor; T e and T L are electromagnetic torque and load torque respectively; B n is a viscous friction coefficient; d n is a constant disturbance; f t represents total disturbance caused by parameter mismatch and other unknown disturbances; n p is the number of magnetic poles of the permanent magnet synchronous motor; is a permanent magnet flux linkage of the permanent magnet synchronous motor; i q is a q-axis stator current.

[0014] The initial electromechanical kinematic equation of the permanent magnet synchronous motor can be rewritten as a second-order kinematic equation about angle:

[0015]

[0016] Then it is arranged:

[0017]

[0018] wherein the coefficient coefficient Sum disturbance And consider A0 is constant.

[0019] Based on hyperlocal model: y is the system output, u is the system control variable, F is the known and unknown part of the system, and alpha is a non-physical scale factor. The initial electromechanical kinematics equation can be changed to a speed control hyperlocal model:

[0020]

[0021] wherein, is a non-physical scale factor of the permanent magnet synchronous motor speed control system, represents the known and unknown parts of the permanent magnet synchronous motor speed control system. Through the speed control hyperlocal model and the second-order kinematics equation of the permanent magnet synchronous motor, it can be seen that Therefore, the value of the non-physical scale factor alpha in the permanent magnet synchronous motor speed control hyperlocal model can be obtained by solving the b parameter.

[0022] Further, the S2, Laplace transform on the second-order kinematics equation, introduce angle low-pass filter, obtain the steps of the complex frequency domain equation of the permanent magnet synchronous motor, specifically including the following steps:

[0023] Laplace transform on the second-order kinematics equation of the permanent magnet synchronous motor, we can get:

[0024]

[0025] In order to accurately obtain the values of the coefficients alpha and b in the equation, a low-pass filter about the mechanical angle of the permanent magnet synchronous motor is introduced:

[0026]

[0027] wherein ω c is the cut-off angular frequency of the low-pass filter, and we can get:

[0028]

[0029] Multiply both sides by s, we can get the complex frequency domain equation of the permanent magnet synchronous motor:

[0030]

[0031] Further, the S3, by derivation of the complex frequency domain equation of the permanent magnet synchronous motor, time domain conversion and integration, the steps of obtaining two-dimensional equation group composed of unknown coefficients of permanent magnet synchronous motor, specifically includes the following steps:

[0032] Third derivative of the complex frequency domain equation of the permanent magnet synchronous motor with respect to s, eliminating the initial value θ0, and constant part A0:

[0033]

[0034] Multiply both sides of the equation by s -4 , we get:

[0035]

[0036] Since the complex frequency domain d v / ds v and the time domain (-t) v are equivalent, we can get:

[0037] aπ1(t)+bπ2(t)=q(t),

[0038] where

[0039] π1(t)=-∫t 3 y+∫ (2) (9t 2 y-ω c t 3 y)+∫ (3) (-18ty+6ω c t 2 y)+∫ (4) (6y-6ω c ty)

[0040] π2(t)=-∫ (4) 3ω c t 2 i q +∫ (3) ω c t 3 i q

[0041] q(t)=t 3 y+∫(-12t 2 y+ω c t 3 y)+∫ (2) (36ty-9ω c t 2 y)+∫ (3) (-24y+18ωcty)-6ω c ∫(4) y

[0042] ∫ (n) φ(t) is expressed as

[0043] Integrating the above formula once, the two-dimensional equation group about unknown coefficient of permanent magnet synchronous motor can be obtained:

[0044]

[0045] Wherein:

[0046] P 11 (t)=π1(t),P 12 (t)=π2(t),Q1(t)=q(t)

[0047] P 21 (t)=∫π1(t),P 22 (t)=∫π2(t),Q2(t)=∫q(t)

[0048] Further, the S4, according to the speed command positive and negative permanent magnet synchronous motor, the angle and q-axis current data obtained are substituted into the two-dimensional equation group to solve, the value of the non-physical scale factor in the step of obtaining is specifically includes the following steps:

[0049] According to the expected speed command positive and negative permanent magnet synchronous motor, the actual permanent magnet synchronous motor speed and q-axis current are measured and calculated through the motor encoder and current sensor, the value of the matrix element in the two-dimensional equation group in the [0, t] interval can be calculated:

[0050]

[0051] Then the values of the unknown coefficients a e and b e of the permanent magnet synchronous motor can be obtained:

[0052]

[0053] Therefore, the non-physical scale factor α of the permanent magnet synchronous motor super-local model is b e .

[0054] The application provides a kind of permanent magnet synchronous motor offline parameter estimation system based on algebraic differentiation method, comprising:

[0055] Data acquisition module is used to obtain heart motion geometry data from existing data file and permanent magnet synchronous motor servo system;

[0056] The two-dimensional equation set establishing module is used for obtaining a speed control hyperlocal model and a second-order kinematics equation of the permanent magnet synchronous motor according to an initial electromechanical kinematics equation of the permanent magnet synchronous motor, performing Laplace transformation on the second-order kinematics equation, introducing an angle low-pass filter, obtaining a complex frequency domain equation of the permanent magnet synchronous motor, and establishing a two-dimensional equation set composed of unknown coefficients of the permanent magnet synchronous motor through derivation, time domain conversion and integration on the complex frequency domain equation of the permanent magnet synchronous motor.

[0057] The parameter estimation module is used for performing integral operation and the like on actual data in a period of time, estimating the value of the non-physical proportional factor by solving a quadratic linear equation set.

[0058] The application provides a device, which comprises a processor and a memory coupled with the processor, wherein the memory stores program instructions for realizing offline parameter estimation of a permanent magnet synchronous motor based on an algebraic differential method; and the processor is used for executing the program instructions stored in the memory to realize estimation of a non-physical proportional factor.

[0059] The application provides a storage medium storing program instructions executable by a processor, wherein the program instructions are used for executing an offline parameter estimation method of a permanent magnet synchronous motor based on an algebraic differential method.

[0060] Compared with the prior art, the application has the advantages that the application does not need other information of a motor model, only uses input and output data of the motor, has the advantages of simple implementation, wide application range and no occupation of hardware resources of a control system, and provides an efficient and fast way for the value of the non-physical proportional factor. BRIEF DESCRIPTION OF DRAWINGS

[0061] Figure 1 FIG. 1 is a flowchart of an offline parameter estimation method of a permanent magnet synchronous motor based on an algebraic differential method according to Embodiment 1 of the application;

[0062] Figure 2 FIG. 2 is an experimental result graph of angle and current data obtained when the permanent magnet synchronous motor is driven for the first time according to Embodiment 1 of the application;

[0063] Figure 3 FIG. 3 is an experimental result graph of angle and current data obtained when the permanent magnet synchronous motor is driven for the second time according to Embodiment 1 of the application;

[0064] Figure 4 FIG. 4 is an experimental result graph of angle and current data obtained when the permanent magnet synchronous motor is driven for the third time according to Embodiment 1 of the application;

[0065] Figure 5 FIG. 5 is a result graph of the offline parameter estimation of the permanent magnet synchronous motor based on the algebraic differential method according to Embodiment 1 of the application;

[0066] Figure 6 Structure diagram of an off-line parameter estimation system for a permanent magnet synchronous motor based on algebraic differential method according to Embodiment 2 of the present application;

[0067] Figure 7 Structure diagram of a device according to Embodiment 3 of the present application;

[0068] Figure 8 Structure diagram of a storage medium according to Embodiment 4 of the present application. DETAILED DESCRIPTION

[0069] It should be understood that the specific embodiments described herein merely exemplify the present application and are not intended to limit the present application.

[0070] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts fall within the scope of the present application.

[0071] Embodiment 1

[0072] Figure 1 Flowchart of a permanent magnet synchronous motor off-line parameter estimation method based on algebraic differential method according to Embodiment 1 of the present application, the steps comprising:

[0073] S1, obtaining a speed control hyper-local model and a second-order kinematic equation of a permanent magnet synchronous motor according to an initial electromechanical kinematic equation of the permanent magnet synchronous motor.

[0074] In this embodiment, the initial kinematic equation of the permanent magnet synchronous motor is:

[0075]

[0076] wherein, θ is a mechanical angle of the permanent magnet synchronous motor; ω m is a mechanical angular velocity of the permanent magnet synchronous motor; J n is a total rotational inertia of the permanent magnet synchronous motor; T e and T L are an electromagnetic torque and a load torque respectively; B n is a viscous friction coefficient; d n is a constant disturbance; f t represents a total disturbance caused by parameter mismatch and other unknown disturbances;

[0077] For a surface-mounted permanent magnet synchronous motor, the electromagnetic torque equation of the permanent magnet synchronous motor is:

[0078] wherein, T

[0079] where n p is the number of pole pairs of the permanent magnet synchronous motor; is the flux of the permanent magnet synchronous motor; d and i q are the stator currents of d-axis and q-axis, respectively, L d = L q are the stator inductances of d-axis and q-axis, respectively.

[0080] Rewriting the initial kinematic equation and electromagnetic torque equation, the second-order kinematic equation of the permanent magnet synchronous motor is:

[0081]

[0082] Moving terms:

[0083]

[0084] Then, it is arranged as:

[0085]

[0086] where the coefficient a = B n / J n , the coefficient The total disturbance A0 = (-T L -d n -f t )J n , and A0 is considered to be a constant.

[0087] The expression of the superlocal model is:

[0088]

[0089] where y is the output of the system, u is the control variable of the system, F is the known and unknown part of the system, and a is a non-physical scaling factor.

[0090] Based on the superlocal model, the electromechanical kinematic equation of the permanent magnet synchronous motor can be rewritten as the superlocal model of the speed control of the permanent magnet synchronous motor:

[0091]

[0092] where, is the non-physical scaling factor of the system, F = (-T L -B n ω m -d n -f t ) / J n represents the known and unknown parts of the system. Through the speed control superlocal model and the second-order kinematic equation of the permanent magnet synchronous motor, it can be seen that Therefore, the value of the non-physical proportional factor a in the speed control hyperlocal model of the permanent magnet synchronous motor can be obtained by solving the b parameter.

[0093] S2, Laplace transform is performed on the second-order kinematic equation, and a low-pass filter of angle is introduced to obtain the complex frequency domain equation of the permanent magnet synchronous motor.

[0094] The second-order kinematic equation of the permanent magnet synchronous motor after arrangement with respect to angle and q-axis current as variables is subjected to Laplace transform, and the following equation is obtained:

[0095]

[0096] In order to accurately obtain the values of the coefficients a and b in the equation, a low-pass filter of the mechanical angle of the permanent magnet synchronous motor is introduced:

[0097]

[0098] Where ω c is the cut-off angular frequency of the low-pass filter, and the following equation is obtained:

[0099]

[0100] The complex frequency domain equation of the permanent magnet synchronous motor is obtained by multiplying s on both sides of the equation:

[0101]

[0102] S3, by taking the derivative of the complex frequency domain equation of the permanent magnet synchronous motor, time domain conversion and integration, a two-dimensional equation group composed of unknown coefficients of the permanent magnet synchronous motor is obtained.

[0103] The derivative of the complex frequency domain equation of the permanent magnet synchronous motor is taken with respect to s, and A0is eliminated:

[0104]

[0105] The second derivative of the complex frequency domain equation of the permanent magnet synchronous motor is taken with respect to s, and

[0106]

[0107] The third derivative of the complex frequency domain equation of the permanent magnet synchronous motor is taken with respect to s, and finally the initial value θ0, and the constant value A0are eliminated:

[0108]

[0109] s -4 is multiplied on both sides of the equation, and the following equation is obtained:

[0110]

[0111] Since the complex frequency domain d v / ds v and the time domain (-t) v are equivalent, we can get:

[0112] aπ1(t) + bπ2(t) = q(t),

[0113] where

[0114] π1(t) = -∫t 3 y+∫ (2) (9t 2 y-ω c t 3 y)+∫ (3) (-18ty+6ω c t 2 y)+∫ (4) (6y-6ω c ty)

[0115] π2(t) = -∫ (4) 3ω c t 2 i q +∫ (3) ω c t 3 i q

[0116] q(t) = t 3 y+∫(-12t 2 y+ω c t 3 y)+∫ (2) (36ty-9ω c t 2 y)+∫ (3) (-24y+18ω c ty)-6ω c ∫ (4) y

[0117] The ∫ (n) φ(t) in the above formula is expressed as In particular

[0118] Integrating the above formula once, we can get a two-dimensional equation system about the unknown coefficients a e and b e of the permanent magnet synchronous motor:

[0119]

[0120] where:

[0121] P 11 (t) = π1(t), P 12 (t) = π2(t), Q1(t) = q(t)

[0122] P 21 (t) = ∫π1(t), P 22 (t) = ∫π2(t), Q2(t) = ∫q(t)

[0123] S4, according to the speed command of the permanent magnet synchronous motor, the obtained angle and q-axis current data are substituted into the two-dimensional equation set for solving, and the value of the non-physical scale factor can be obtained.

[0124] Please refer to Figure 2 , Figure 3 and Figure 4 , which are the mechanical angle and q-axis current information about the motor obtained after the permanent magnet synchronous motor is reversed according to the speed command in Embodiment 1 of the application. In each graph, the first channel shows the expected speed and the actual speed of the permanent magnet synchronous motor, and the permanent magnet synchronous motor drives the load to rotate according to the expected speed requirement; the second channel shows the actual current of the q-axis of the permanent magnet synchronous motor; the third channel shows the angle data of the actual rotation of the permanent magnet synchronous motor. The difference between the three experiments is that the initial angle of the permanent magnet synchronous motor is different.

[0125] After obtaining the angle and current information, substitute the matrix element calculation formula,

[0126]

[0127] The value of each element of the matrix can be obtained.

[0128] By substituting the matrix elements into the following formula, the values of the unknown coefficients a e and b e of the permanent magnet synchronous motor can be obtained:

[0129]

[0130] Therefore:

[0131]

[0132] The flux linkage of the permanent magnet synchronous motor in Embodiment 1 of the application The number of magnetic pole pairs n of the permanent magnet synchronous motor p = 20, the load moment of inertia J n = 0.04174 Kg.m 2 , so

[0133] Please refer to Figure 5The value of the non-physical proportional factor estimated according to the mechanical angle and q-axis current data of the permanent magnet synchronous motor in Embodiment 1 of the present application. As can be seen from the figure, the estimated values of the non-physical proportional factor of three experiments with different initial angles are all between 39 and 40, which is very close to the theoretical actual value 39.52, which proves the effectiveness of the off-line parameter estimation method of the permanent magnet synchronous motor based on the algebraic differential method of the present application.

[0134] The present application can effectively estimate the value of the non-physical proportional factor in the permanent magnet synchronous motor model-free speed control based on the super-local model, improve the dynamic performance of the permanent magnet synchronous motor model-free speed control, and enhance the robustness of the control system

[0135] Embodiment 2

[0136] Please refer to Figure 6 The structure diagram of the off-line parameter estimation system 400 of the permanent magnet synchronous motor based on the algebraic differential method in Embodiment 2 of the present application; the specific content includes:

[0137] The data acquisition module 410 is used to acquire angle and current data from existing data files and permanent magnet synchronous motor servo systems;

[0138] The parameter estimation module 420 performs integral operation on the actual data in a period of time, estimates the value of the non-physical proportional factor by solving the quadratic linear equation set. The establishment process of the quadratic linear equation set is as follows: according to the initial electromechanical kinematics equation of the permanent magnet synchronous motor, the speed control super-local model and the second-order kinematics equation of the permanent magnet synchronous motor are obtained, the Laplace transform is performed on the second-order kinematics equation, the angle low-pass filter is introduced, the complex frequency domain equation of the permanent magnet synchronous motor is obtained, and the quadratic linear equation set composed of unknown system parameters of the permanent magnet synchronous motor is established by derivation, time domain conversion and integration on the complex frequency domain equation of the permanent magnet synchronous motor.

[0139] Embodiment 3

[0140] Please refer to Figure 7 The device structure diagram of Embodiment 3 of the present application. The device 500 includes a processor 510 and a memory 520 coupled with the processor 510.

[0141] The memory 520 stores program instructions for implementing the above-mentioned off-line parameter estimation method of the permanent magnet synchronous motor based on the algebraic differential method.

[0142] The processor 510 is configured to execute the program instructions stored in the memory 520 to implement the off-line parameter estimation of the permanent magnet synchronous motor based on the algebraic differential method.

[0143] The processor 510 can also be called a CPU (Central Processing Unit). The processor 510 can be an integrated circuit chip including a processing core. The processor 510 can also be a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application-Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0144] Embodiment 4

[0145] Referring to Figure 8 The storage medium of the embodiment 4 of the present application is shown in FIG. 6. The storage medium of the embodiment of the present application stores a program file 610 capable of implementing all the methods described above. The program file 610 can be stored in the storage medium in the form of a software product, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the method of each embodiment of the present application. The storage medium described above includes a U disk, a mobile hard disk, a ROM (Read-Only Memory), a RAM (Random Access Memory), a magnetic disk or an optical disk, and various media capable of storing program codes, or a computer, a server, a mobile phone, a tablet, etc.

[0146] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, so that a process, device, article or method including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such a process, device, article or method. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, device, article or method including the element.

[0147] The above description is only the preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation, or direct or indirect application in other related technical fields, is also included in the patent protection scope of the present application.

[0148] While embodiments of the application have been shown and described, it is to be understood that the application is not limited to the details of the embodiments described, since various modifications can be made by those skilled in the art, without departing from the spirit and scope of the application, which are defined by the appended claims and their equivalents.

[0149] Of course, the present application also has other various embodiments, and based on the embodiments, other embodiments obtained by those of ordinary skill in the art without any creative work are within the scope of the present application.

Claims

1. A method for off-line parameter estimation of permanent magnet synchronous motor based on algebraic differentiation method, characterized in that, The electromechanical kinematic equation of the permanent magnet synchronous motor is transformed, and by solving a linear equation set about motor parameters, an estimated value of a non-physical proportional factor in a super-local model of the permanent magnet synchronous motor is obtained; The method comprises the following steps: S1, obtaining a speed control super-local model and a second-order kinematic equation of the permanent magnet synchronous motor according to an initial electromechanical kinematic equation of the permanent magnet synchronous motor; S2, performing Laplace transformation on the second-order kinematic equation, introducing an angle low-pass filter, and obtaining a complex frequency domain equation of the permanent magnet synchronous motor; S3, obtaining a two-dimensional equation set composed of unknown coefficients of the permanent magnet synchronous motor by derivation, time domain conversion and integration of the complex frequency domain equation of the permanent magnet synchronous motor; S4, substituting the obtained angle and q-axis current data into the two-dimensional equation set for solving to obtain the value of the non-physical proportional factor by forward and reverse rotation of the permanent magnet synchronous motor according to a speed instruction; The superlocal model is: y is the system output quantity, u is the system control variable, F is the known and unknown part of the system, and a is a non-physical scale factor.

2. The off-line parameter estimation method of permanent magnet synchronous motor based on algebraic differential method according to claim 1, characterized in that, The step S1 specifically comprises: The initial electromechanical kinematic equation of the permanent magnet synchronous motor is established as follows: where θ is the mechanical angle of the permanent magnet synchronous motor; ω m is the mechanical angular velocity of the permanent magnet synchronous motor; J n is the total rotational inertia of the permanent magnet synchronous motor; T e and T L are the electromagnetic torque and the load torque, respectively; B n is the viscous friction coefficient; d n is the constant disturbance; f t represents the total disturbance caused by parameter mismatch and other unknown disturbances; n p is the number of pole pairs of the permanent magnet synchronous motor; is the permanent magnet flux linkage of the permanent magnet synchronous motor; i q is the q-axis stator current; The initial electromechanical kinematic equation of the permanent magnet synchronous motor is rewritten as a second-order kinematic equation about the angle as follows: After arrangement, the initial electromechanical kinematic equation is constructed into the speed control super-local model based on the super-local model as follows: wherein the coefficients coefficients sum disturbance A0 is a constant; In the step S2, the complex frequency domain equation of the permanent magnet synchronous motor is obtained by performing Laplace transformation on the second-order kinematic equation and introducing an angle low-pass filter, and specifically comprises the following steps: wherein, is a non-physical proportionality factor of the permanent magnet synchronous motor speed control system, represents the known part and the unknown part of the permanent magnet synchronous motor speed control system.

3. The off-line parameter estimation method of PMSM based on algebraic differentiation method according to claim 2, characterized in that, The second-order kinematic equation of the permanent magnet synchronous motor is subjected to Laplace transformation to obtain: Wherein, θ0 is an initial value, and a low-pass filter about the mechanical angle of the permanent magnet synchronous motor is introduced: Both sides are multiplied by s to obtain the complex frequency domain equation of the permanent magnet synchronous motor: where ω c is the cut-off angular frequency of the low-pass filter, which gives The step S3 specifically comprises:

4. The off-line parameter estimation method of PMSM based on algebraic differentiation method according to claim 3, characterized in that, aπ1(t)+bπ2(t)=q(t), Third derivative of the complex frequency domain equation of the permanent magnet synchronous motor with respect to s, eliminating the initial value θ0, and constant part A0: Multiply both sides of the equation by s -4 , we get: Since the complex frequency domain d v / ds v and the time domain (-t) v are equivalent, we have: Wherein: The above formula is integrated once to obtain a two-dimensional equation set composed of unknown coefficients of the permanent magnet synchronous motor: pi(t) = -∫t 3 y + ∫ (2) (9t 2 y - ω c t 3 y) + ∫ (3) (-18t y + 6ω c t 2 y) + ∫ (4) (6y - 6ω c t y) π2(t) = -∫ (4) 3ω c t 2 i q +∫ (3) ωct 3 i q q(t) = t 3 y + ∫(-12t 2 y + ω c t 3 y) + ∫ (2) (36ty - 9ω c t 2 y) + ∫ (3) (-24y + 18ω c ty) - 6ω c ∫ (4) y ∫ in the above formula (n) φ(t) is expressed as The step S4 specifically comprises the following steps: where a e and b e are unknown coefficients of the permanent magnet synchronous motor, and other parameters are:

5. The off-line parameter estimation method of PMSM based on algebraic differentiation method according to claim 4, characterized in that, The permanent magnet synchronous motor is forward and reverse rotated according to the expected speed instruction, the actual permanent magnet synchronous motor speed and q-axis current are measured and calculated through the motor encoder and the current sensor, and the values of the matrix elements in the two-dimensional equation set in the [0, t] interval are calculated: It comprises: Obtain the values of the unknown coefficients a e and b e of the permanent magnet synchronous motor Obtaining a non-physical scale factor a = b in a super-local model of a permanent magnet synchronous motor e .

6. A system for off-line parameter estimation of permanent magnet synchronous motor based on algebraic differentiation method implementing the method of any one of claims 1-5, characterized in that, A data acquisition module is configured to acquire angle and current data from existing data files and a permanent magnet synchronous motor servo system; A two-dimensional equation set establishment module is configured to obtain a speed control super-local model and a second-order kinematic equation of the permanent magnet synchronous motor according to an initial electromechanical kinematic equation of the permanent magnet synchronous motor, perform Laplace transformation on the second-order kinematic equation, introduce an angle low-pass filter, obtain a complex frequency domain equation of the permanent magnet synchronous motor, and establish a two-dimensional equation set composed of unknown coefficients of the permanent magnet synchronous motor by derivation, time domain conversion and integration of the complex frequency domain equation of the permanent magnet synchronous motor; A parameter estimation module is configured to perform integral operation on actual data in a period of time, estimate the value of the non-physical proportional factor by solving the two-dimensional equation set. ​ 7. An apparatus, comprising: The device comprises a processor, a memory coupled with the processor, wherein the memory stores program instructions for implementing the off-line parameter estimation method of the permanent magnet synchronous motor based on the algebraic differential method according to any one of claims 1-5; and the processor is configured to execute the program instructions stored in the memory to estimate the non-physical scale factor.

8. A storage medium, characterized by The memory stores processor-executable program instructions for executing the steps of the off-line parameter estimation method of the permanent magnet synchronous motor based on the algebraic differential method according to any one of claims 1-5.

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