A sensorless control method and system for a permanent magnet synchronous motor

Abstract

This invention provides a sensorless control method for a permanent magnet synchronous motor, comprising the following steps: S1, simulating to obtain the id iq instruction table; S2, setting the motor speed ω to be less than the field weakening speed point, and collecting the three-phase current, voltage, and T of the motor. e S3, after performing Clark transformation on the three-phase current and voltage, i is obtained. α i β u α u β After obtaining the rotor angle, the position estimation module feeds it back to the park transformation unit and the park inverse transformation unit; S4, i α i β After performing the park transformation, we obtain i d i q The comparator in the current loop is fed back; S5, the id iq instruction table sends a set of instructions i to the comparator. d* i q* The system generates three-phase current through a PI current regulator, Park inverse converter, SVPWM module, and inverter. It then collects current, voltage, and electromagnetic torque, estimates the rotor angle, and repeats the current loop adjustment until the motor stabilizes. Finally, the id iq instruction table sends the next set of instructions. d* i q* S6, repeat S5 until all instructions in the id iq instruction table have been issued, and collect data; S7, calculate the optimal torque-speed-current relationship table through a mathematical model.

Description

[Technical Field]

[0001] This invention relates to the field of motor control technology, and in particular to a sensorless control method and system for a permanent magnet synchronous motor. [Background Technology]

[0002] A permanent magnet synchronous motor mainly consists of permanent magnets and three-phase stator windings. Under the action of three-phase current, a rotating magnetic field is generated in the stator windings of the motor. The rotor rotates in the rotating magnetic field generated by the stator, eventually reaching a speed equal to the rotational speed of the rotating magnetic poles generated in the stator. Thus, electrical energy is converted into kinetic energy and used to drive the motor.

[0003] In the vector control process of a permanent magnet synchronous motor based on rotor flux orientation, the output torque and power of the motor can be controlled by adjusting the values ​​of the excitation component and torque component after decoupling the stator current. The given value of the stator current has a significant impact on the motor's torque output and operating efficiency.

[0004] In related technologies, the stator current value of a motor is typically calibrated manually through motor control performance experiments. However, manually calibrated stator current values ​​only meet the motor control performance requirements under the experimental conditions and are affected by the individual skill of the commissioning personnel and the accuracy of the testing bench. Therefore, providing the motor control module with manually calibrated stator current values ​​cannot meet the needs of accurate motor control and may cause the motor to deviate from its optimal operating point, reducing motor operating efficiency.

[0005] In addition, in high-precision motor control systems, position sensors are usually installed on the motor shaft to detect the angle of the motor rotor. Since position sensors often use precision photoelectric encoders, they are easily affected by the surrounding environment, such as humidity, dust, and vibration, making them a vulnerable link in the control system.

[0006] CN112039387A discloses a fault diagnosis method for a position sensor of a permanent magnet synchronous motor. However, it cannot fundamentally solve the problem of position sensors being prone to failure.

[0007] Therefore, it is necessary to provide a low-cost, high-efficiency, and applicable sensorless control method and system for permanent magnet synchronous motors that can be used with different types of motors to solve the above-mentioned technical problems. [Summary of the Invention]

[0008] The purpose of this invention is to provide a low-cost, high-efficiency, and applicable sensorless control method and system for permanent magnet synchronous motors that can be used with different types of motors, so as to solve the problems in related technologies.

[0009] To achieve the above objectives, the present invention provides a sensorless control method for a permanent magnet synchronous motor, characterized by comprising the following steps:

[0010] S1. Establish a mathematical model on the simulation software and preset the parameters ψ of the motor under test. f L d L q R s Preliminary simulation yielded the idiq instruction table; (ψ f L represents the rotor flux linkage of the motor. d L represents the d-axis inductance of the motor. q R represents the q-axis inductance of the motor. s (Indicates stator resistance)

[0011] S2, activating the motor under test, setting the speed ω to be less than the field weakening speed point, and collecting the current three-phase current I of the motor under test. a I b I c Three-phase voltage V a V b V c Magnetic torque T e ;

[0012] S3, the current three-phase current value I of the motor under test. a I b I c and three-phase voltage V a V b V c After performing the Clark transform, the α-axis current component i is obtained. α β-axis current component i β α-axis voltage component u α β-axis voltage component u β i α i β u α u β The feedback is sent to the position estimation module, which estimates the rotor angle. And feed it back to the park transform unit and the park inverse transform unit;

[0013] S4, current component i α β-axis current component i β After performing the Park transformation, the d-axis current component i is obtained. d q-axis current component i q The feedback is sent to the comparator in the current loop;

[0014] S5, the id iq instruction table sends a set of instructions i to the comparator. d* i q*The d-axis voltage u is output through a PI current regulator. d* q-axis voltage u q* u is obtained after Park inverse transformation α* u β* The pulse voltage generated by the SVPWM module is then fed back to the inverter to generate a three-phase current to control the rotation of the motor under test. The current and electromagnetic torque data of the motor under test are collected, the position estimation module estimates the rotor angle, and the current loop adjustment is repeated until the motor under test stabilizes. The id iq instruction table then sends the next set of instructions i to the comparator. d* i q* ;

[0015] S6. Repeat step S5 until the id iq instruction table has sent all the instructions. The collected current, voltage, electromagnetic torque data and the rotor angle estimated by the position estimation module are used as the basic training data for constructing the mathematical model.

[0016] S7, the optimal torque-speed-current relationship table is obtained through mathematical modeling in simulation software.

[0017] More preferably, in step S3, the position estimation module includes a sliding mode observer and a PLL phase-locked loop.

[0018] More preferably, in step S3, the i α i β u α u β Feedback is given to the sliding mode observer, which in turn receives feedback from the i-th sliding mode observer. α i β u α u β To reconstruct the back electromotive force component E of the permanent magnet synchronous motor α E β The algorithm formula for the sliding mode observer is as follows:

[0019]

[0020] More preferably, in step S3, the back electromotive force component E α E β It is introduced into the PLL phase-locked loop.

[0021] More preferably, in step S3, the PLL outputs the estimated rotor angle and feeds it back to the Park transformation unit and the Park inverse transformation unit. The algorithm formula of the PLL is as follows:

[0022]

[0023]

[0024] θ is the actual rotor angle of the permanent magnet synchronous motor. It is the estimated rotor angle.

[0025] More preferably, the closed-loop transfer function of the PLL is:

[0026]

[0027]

[0028]

[0029] (K p For proportional gain, K i Let ξ be the integral gain, ω be the damping coefficient, and ξ be the integral gain. n It is the natural angular frequency.

[0030] More preferably, the mathematical model includes a spatial state equation based on the dq voltage equation, the stator flux linkage equation, and the electromagnetic torque equation, wherein the spatial state equation is:

[0031]

[0032] Based on the dq voltage equation, stator flux linkage equation, electromagnetic torque equation, and the aforementioned spatial state equation, a correlation model Te(i) is established. d i q )∝Te(ψ d ψ q )∝ψ d (id,iq), ψ q (id, iq);

[0033] Add constraints to the association model

[0034]

[0035]

[0036] U smax =U dc *K, the coefficient of K takes values ​​within the range of U dc This represents the DC bus voltage. More preferably, the step of obtaining the preset id iq instruction table includes:

[0037] S201, in the simulation software, according to the formula And i d i q u d u q With electromagnetic torque Te To find the extreme values, we use Lagrange's theorem and introduce auxiliary functions H1 and H2.

[0038]

[0039]

[0040]

[0041]

[0042]

[0043] Preliminary simulations yielded a set of information about i d i q Matrix data;

[0044] S202, regarding i d i q The matrix data is based on i s Expand the scope from different angles to obtain a data set;

[0045] S203, the data group is assembled into the preset id iq instruction table.

[0046] More preferably, in step S202, by... d i q The matrix data is based on i s An angle of ±15°-30° is used to obtain a sector-shaped data cluster.

[0047] This invention also provides a system employing the aforementioned sensorless control method for a permanent magnet synchronous motor. The system includes a control module, a data acquisition module, and a data processing module. The control module comprises a power supply, an inverter, a motor under test, a command generator, a comparator, a PI current regulator, an SVPWM module, an abc-αβ conversion unit, an αβ-dq conversion unit, a dq-αβ conversion unit, and a position estimation module, all forming a current loop. The position estimation module includes a sliding mode observer and a PLL (phase-locked loop). The data acquisition module includes a current acquisition device, a voltage acquisition device, and a torque sensor connected to the motor under test. The data processing module includes simulation software.

[0048] The technical advantages of this invention are as follows: the rotor angle is estimated by using a position estimation module, which reduces hardware requirements and makes the data acquisition method simpler and more accurate. Furthermore, after data acquisition, direct calculation and iterative processing can be performed to achieve real-time parameter calculation and updates, ensuring parameter reliability. Moreover, by building a mathematical model on the simulation software, the mathematical model can be updated and replaced in the form of a plug-in, ensuring that the calculated data better meets the control requirements. It is also beneficial for adapting to different types of motors, resulting in low cost and high efficiency. [Attached Image Description]

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein:

[0050] Figure 1 This is a flowchart of a sensorless control method for a permanent magnet synchronous motor according to the present invention;

[0051] Figure 2 This is a framework diagram of a sensorless control method for a permanent magnet synchronous motor according to the present invention;

[0052] Figure 3 This is a block diagram illustrating the principle of the PLL phase-locked loop of the present invention;

[0053] Figure 4 yes Figure 3 The equivalent block diagram is described above.

[0054] Figure 5 This is a schematic diagram illustrating the principle of obtaining a preset idiq instruction table according to the present invention;

[0055] Figure 6 Yes, this invention provides a system framework diagram.

Detailed Implementation Methods

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Parameter description: I a I b I c V represents three-phase current. a V b V c U represents the three-phase voltage.dc Indicates the DC bus voltage, i s i represents the stator current of the motor. d i represents the d-axis current of the motor stator. q i represents the q-axis current of the motor stator. α Represents the a-axis current component, i β Represents the β-axis current component, u α Represents the voltage component along the a-axis, u β E represents the β-axis voltage component. α E represents the back electromotive force component along the a-axis. β Represents the β-axis back electromotive force component, R s ω represents the stator resistance, ω represents the rotor speed, and θ represents the rotor angle. It is the estimated rotor angle, P n ψ represents the number of pole pairs of the motor. d ψ represents the magnetic flux linkage along the d-axis of the motor rotor. q ψ represents the magnetic flux linkage along the d-axis of the motor rotor. f L represents the rotor flux linkage of the motor. d L represents the d-axis inductance of the motor. q λ represents the q-axis inductance of the motor. i , λ u T represents the Lagrange operator. e K represents the electromagnetic torque of the motor. p It is the proportional gain, K i ξ is the integral gain, ξ is the damping coefficient, and ω is the damping coefficient. n It is the natural angular frequency.

[0058] Please refer to Figure 1 , Figure 2 As shown, the present invention provides a sensorless control method for a permanent magnet synchronous motor, which includes the following steps:

[0059] S1. Establish a mathematical model on the simulation software and preset the parameters ψ of the motor under test. f L d L q R s Preliminary simulation yielded the idiq instruction table; (ψ f L represents the rotor flux linkage of the motor. d L represents the d-axis inductance of the motor. q R represents the q-axis inductance of the motor. s (Indicates stator resistance)

[0060] S2, activating the motor under test, setting the speed ω to be less than the field weakening speed point, and collecting the current three-phase current I of the motor under test. a I b I c Three-phase voltage V a Vb V c Magnetic torque T e ;

[0061] S3, the current three-phase current value I of the motor under test. a I b I c and three-phase voltage V a V b V c After performing the Clark transform, the α-axis current component i is obtained. α β-axis current component i β α-axis voltage component u α β-axis voltage component u β i α i β u α u β The feedback is sent to the position estimation module, which estimates the rotor angle. And feed it back to the park transform unit and the park inverse transform unit;

[0062] S4, β-axis current component i α β-axis current component i β After performing the Park transformation, the d-axis current component i is obtained. d q-axis current component i q The feedback is sent to the comparator in the current loop;

[0063] S5, the id iq instruction table sends a set of instructions i to the comparator. d* i q* The d-axis voltage u is output through a PI current regulator. d* q-axis voltage u q* u is obtained after Park inverse transformation α* u β* The pulse voltage generated by the SVPWM module is then fed back to the inverter to generate a three-phase current to control the rotation of the motor under test. The current, voltage, and electromagnetic torque data of the motor under test are collected, and the position estimation module estimates the rotor angle. The current loop adjustment is repeated until the motor under test stabilizes. The id iq instruction table sends the next set of instructions i to the comparator. d* i q* ;

[0064] S6. Repeat step S5 until the id iq instruction table has sent all the instructions. The collected current, voltage, electromagnetic torque data and the rotor angle estimated by the position estimation module are used as the basic training data for constructing the mathematical model.

[0065] S7. The optimal torque-speed-current relationship table is obtained in the simulation software using the mathematical model.

[0066] The beneficial effects of the sensorless control method for permanent magnet synchronous motors of the present invention are as follows: the rotor angle is estimated by a position estimation module, reducing the need for position sensors; the data acquisition method is simple and accurate; and the data is directly calculated and iteratively processed after acquisition, enabling real-time parameter calculation and updating, thus ensuring parameter reliability. Furthermore, by building a mathematical model on simulation software, the mathematical model can be updated and replaced in the form of a plug-in, ensuring that the calculated data better meets the control requirements. It is also beneficial for adapting to different types of motors, resulting in low cost and high efficiency.

[0067] Specifically, in step S1, the motor under test is kept constant at its rotational speed ω by aligning it with the load motor. The rotational speed ω can be 80% of the field weakening speed point, but is not limited to this. Controlling the rotational speed by aligning the motor under test is convenient and simple, and this invention only requires one rotational speed to obtain accurate stator current across the entire speed range.

[0068] Specifically, in step S3, the position estimation module includes a sliding mode observer and a PLL phase-locked loop.

[0069] Specifically, in step S5, the collected current, voltage, and electromagnetic torque data, as well as the rotor angle estimated by the position estimation module, can be transmitted to the mathematical model in real time via CAN communication or other means. Alternatively, after all the id and iq commands have been sent in step S6, the collected data can be packaged and transmitted to the mathematical model via CAN communication or other means.

[0070] Specifically, in step S3, the three-phase current value I a I b I c and three-phase voltage V a V b V c After performing the Clark transformation, the α-axis voltage component u is obtained according to formula (1). α β-axis voltage component u β According to formula (2), the α-axis current component i is obtained. α β-axis current component i β .

[0071]

[0072]

[0073] Specifically, in step S3, the sliding mode observer is designed based on the voltage equation of the permanent magnet synchronous motor. The sliding mode observer uses the voltage u of the permanent magnet synchronous motor in the stator α-β coordinate system. αu β and current i α i β To rebuild the back electromotive force E of the motor α E β .

[0074] Specifically, the voltage equation of the permanent magnet synchronous motor in the α-β coordinate system of the stator is formula (3):

[0075]

[0076]

[0077] Specifically, the observations of the sliding mode observer are based on the back electromotive force component E. α E β As shown in formula (4), E α E β It contains information about the rotor angle θ and rotor speed ω of the permanent magnet synchronous motor.

[0078]

[0079] Based on formulas (3) and (4), the algorithm formula for the sliding mode observer is obtained, i.e., u α u β With E α E β Relational formula (5):

[0080]

[0081] Assumption

[0082]

[0083] θ is the actual rotor angle of the permanent magnet synchronous motor. It is the estimated rotor angle. It is the estimation error of the rotor angle.

[0084] when At that time, it was believed If this holds true, the algorithm formula for a PLL (phase-locked loop) can be obtained:

[0085]

[0086] like Figure 3 As shown, E α and E β It was introduced into a PLL phase-locked loop.

[0087] like Figure 4 The diagram shown is the equivalent block diagram for angle estimation based on a PLL. The transfer function of the PLL is obtained, and the open-loop transfer function is as follows:

[0088]

[0089] H(s) = 1 (9) Closed-loop transfer function

[0090]

[0091] The parameters of the second-order system transfer function are tuned as follows:

[0092]

[0093] in: (ξ is the damping coefficient, ω) n (It is the natural angular frequency)

[0094] Based on the above formula, we can further obtain two key parameters of the PLL: the proportional gain K. p Integral gain K i ,as follows

[0095]

[0096]

[0097] In summary, using the PLL-based sliding mode observer algorithm can effectively reduce the high-frequency jitter phenomenon in estimating the back EMF, and will not be directly introduced into subsequent calculations, thus preventing error amplification.

[0098] Example 1

[0099] Specifically, in step S1, the establishment of the mathematical model includes the following steps:

[0100] S101, collect the data I a I b I c Perform Clark and Park transformations to obtain the d-axis current component i. d q-axis current component i q The voltage component u along the d-axis d The voltage component u along the q-axis q ;

[0101] The formula is as follows:

[0102]

[0103]

[0104] The dq voltage equation for the motor in steady state.

[0105]

[0106]

[0107] Stator flux linkage equation

[0108] ψ d =ψ f +L d i d (18)

[0109] ψ q =L q i q (19)

[0110] Electromagnetic torque equation of an electric motor

[0111]

[0112] S102, formula (21) is obtained through formulas (16)(17)(18)(19)(20);

[0113]

[0114] S103, combine formulas (16)(17)(18)(19)(20)(21) to form spatial equation (22);

[0115]

[0116] Thus, ψ d ψ q ψ, the matrix relation of (id, iq) d (id,iq), ψ q (id,iq), and then Te can be obtained with respect to ψ through formulas (18)(19)(20). d ψ q The matrix relationships are used to establish a correlation model.

[0117] Te(i d i q )∝Te(ψ d ψ q )∝ψ d (id,iq), ψ q (id,iq)(23)

[0118] S104, add constraint condition (24) to the established correlation model (23), namely the MTPA principle;

[0119]

[0120] S105, for i d i q ud u q With electromagnetic torque T e To find the extreme values, we use Lagrange's theorem and introduce auxiliary functions H1 and H2.

[0121]

[0122]

[0123] And obtain i under the constraints. d i q u d ,u q The optimal solution.

[0124]

[0125]

[0126]

[0127]

[0128]

[0129]

[0130] S106, Based on the above constraints, parameter constraints are applied to the correlation model (23).

[0131] Through the correlation model and constraints of this embodiment, the accurate stator current can be obtained across the entire speed range.

[0132] Example 2 The difference between Example 2 and Example 1 is:

[0133] In step S104, constraints (33) are added to the established association model (23), namely the MTPV principle;

[0134]

[0135] Substituting equations (16) and (17) into equation (33) aims to increase the maximum voltage limit U. smax U smax =U dc *K, the coefficient K takes values ​​within... Formula (33) can be obtained, and formula (34) serves as one of the constraints.

[0136] (R s i d -ωL q i q ) 2+[R s i q +ω(ψ f +L d i d )] 2 ≤(|u s | max ) 2 (34)

[0137] In summary, this embodiment employs constraints that satisfy the minimum stator current and the minimum voltage to obtain the maximum torque, thus enabling accurate stator current acquisition across the entire speed range.

[0138] Specifically, step S1, the step of obtaining the preset id iq instruction table includes:

[0139] S201, in the simulation software, i is calculated according to formula (20). d i q u d u q With electromagnetic torque T e The extreme values ​​are found by using Lagrange's theorem, and the constraints of auxiliary functions (25)(26) and (27), (28), and (29) are introduced. The motor parameters ψ are preset. f L d L q R s Preliminary simulations yielded a set of information about i. d i q Matrix data; preset motor parameters ψ f L d L q R s It can be provided to motor manufacturers.

[0140] S202, regarding i d i q The matrix data is based on i s Expand the scope from different angles to obtain a data set;

[0141] S203, the data group is organized into a preset id iq instruction table.

[0142] This design allows for the early elimination of unstable control points through constraints, effectively simplifying testing time.

[0143] like Figure 5 As shown, in step S202, this can be achieved by... d i q The matrix data is based on i s Angle ±15° is used to obtain a relatively simple sector data group, i.s 'to i s The data group between "".

[0144] In other embodiments, it can also be based on i s The angle is ±30° or 20°, but not limited to this.

[0145] This method of obtaining the preset ID iq command can greatly simplify the testing time, effectively eliminate some unstable control points, and have no impact on the test results.

[0146] like Figure 2 , Figure 6 As shown, the present invention provides a system that employs the aforementioned sensorless control method for a permanent magnet synchronous motor, comprising a control module, a data acquisition module, and a data processing module.

[0147] The control module includes a power supply, inverter, motor under test, command generator, two comparators, two PI current regulators, SVPWM module, abc-αβ conversion unit, αβ-dq conversion unit, dq-αβ conversion unit, and position estimation module, which together form a current loop.

[0148] The power supply output is connected to the inverter input, and the inverter output is connected to the motor under test. Specifically, the power supply is a battery pack that outputs DC power.

[0149] An inverter is used to convert direct current into alternating current to power the motor under test.

[0150] The acquisition module includes a current acquisition device, a voltage acquisition device, and a torque sensor connected to the motor under test.

[0151] The current acquisition device acquires the three-phase current I output from the inverter. a I b I c The current acquisition device is a current sensor.

[0152] The voltage acquisition device acquires the three-phase voltage V output of the inverter. a V b V c The voltage acquisition device is a voltage sensor.

[0153] The torque sensor collects the electromagnetic torque T of the motor under test. e .

[0154] The output of the current acquisition device is connected to the input of the abc-αβ conversion unit, which performs Clark transformation.

[0155] The output of the voltage acquisition device is connected to the input of the abc-αβ conversion unit.

[0156] The output of the abc-αβ transformation unit is connected to the position estimation module, which estimates the rotor angle and feeds it back to the αβ-dq transformation unit and the dq-αβ transformation unit.

[0157] The position estimation module includes a sliding mode observer and a PLL phase-locked loop.

[0158] The output of the abc-αβ transform unit is connected to the input of the αβ-dq transform unit for Park transform. The output of the αβ-dq transform unit is fed back to the comparator.

[0159] The instruction generator is used to store the preset id iq instruction table, and the output of the instruction generator is connected to the input of the comparator.

[0160] The comparator's output is connected to the input of a PI current regulator. The PI current regulator converts the current control signal output from the command generator into a voltage control signal.

[0161] The output of the PI current regulator is connected to the input of the dq-αβ converter unit to perform the inverse Park transform.

[0162] The output of the dq-αβ converter unit is connected to the input of the SVPWM module, which is used to convert the voltage control signal into the inverter control signal.

[0163] The output of the SVPWM module is connected to the input of the inverter, which converts the control signal into three-phase current and transmits it to the motor under test.

[0164] The data processing module includes simulation software, which can be MATLAB, Simplorer, etc., but is not limited to these.

[0165] The mathematical model includes the spatial state equations and constraints.

[0166] In summary, the beneficial effects of the system of the present invention are as follows: the device for acquiring and processing data is simple, requires no position sensor, the acquired data is accurate, and the data can be directly calculated and iteratively processed after acquisition, enabling real-time calculation and updating of parameters, ensuring the reliability of the parameters. Furthermore, by building a mathematical model on simulation software, the mathematical model and constraints can be updated and replaced in the form of plug-ins, ensuring that the calculated data better meets the control requirements. The operation is simple and efficient, which is conducive to adapting to different types of motors, saving time, reducing costs, and thus improving efficiency.

[0167] Finally, 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 it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A sensorless control method for a permanent magnet synchronous motor, characterized in that, It includes the following steps: S1. Establish a mathematical model on the simulation software and preset the parameters of the motor under test. , The idiq instruction table was obtained through preliminary simulation. Indicates the rotor flux linkage of the motor. This represents the d-axis inductance of the motor. This represents the q-axis inductance of the motor. Indicates stator resistance; The preliminary simulation yields the id iq instruction table, including: S201, in the simulation software, according to the formula And to , , With electromagnetic torque To find the extreme values, we use Lagrange's theorem and introduce auxiliary functions H1 and H2. ， Preliminary simulations yielded a set of information about Matrix data; S202, regarding The matrix data is based on Expand the scope from different angles to obtain a data set; S203, the data group is assembled into the id iq instruction table; S2, activate the motor under test and set the speed. Below the field weakening speed point, the current three-phase current of the motor under test is collected. , , Three-phase voltage , , Magnetic torque ; S3, the current three-phase current value of the motor under test. , , and three-phase voltage , , After performing the Clark transform, the α-axis current component is obtained. β-axis current component α-axis voltage component β-axis voltage component , , , , The feedback is sent to the position estimation module, which estimates the rotor angle. The feedback is then sent to the park transformation unit and the park inverse transformation unit; the position estimation module includes a sliding mode observer and a PLL phase-locked loop; S4, Current Component β-axis current component After performing the Park transformation, the d-axis current component is obtained. i q The feedback is given to the comparator in the current loop; S5, the id iq instruction table sends a set of instructions to the comparator. The d-axis voltage is output through a PI current regulator. , After inverse Park transformation, we obtain , The pulse voltage generated by the SVPWM module is then fed back to the inverter to generate a three-phase current to control the rotation of the motor under test. The current and electromagnetic torque data of the motor under test are collected, the position estimation module estimates the rotor angle, and the current loop adjustment is repeated until the motor under test stabilizes. The id iq instruction table then sends the next set of instructions to the comparator. ; S6. Repeat step S5 until the id iq instruction table has sent all the instructions. The collected current, voltage, electromagnetic torque data and the rotor angle estimated by the position estimation module are used as the basic training data for constructing the mathematical model. S7 uses a mathematical model in simulation software to obtain the optimal torque-speed-current relationship table.

2. The sensorless control method for a permanent magnet synchronous motor according to claim 1, characterized in that, In step S3, the , , , Feedback is given to the sliding mode observer, which, through the... , , , To reconstruct the back electromotive force component of the permanent magnet synchronous motor , The algorithm formula for the sliding mode observer is as follows: 。 3. The sensorless control method for a permanent magnet synchronous motor according to claim 2, characterized in that, In step S3, the back electromotive force component , It is introduced into the PLL phase-locked loop.

4. The sensorless control method for a permanent magnet synchronous motor according to claim 3, characterized in that, In step S3, the PLL outputs the estimated rotor angle and feeds it back to the Park transformation unit and the Park inverse transformation unit. The algorithm formula of the PLL is as follows: This is the actual rotor angle of the permanent magnet synchronous motor. It is the estimated rotor angle, | |< 6.

5. The sensorless control method for a permanent magnet synchronous motor according to claim 4, characterized in that, The closed-loop transfer function of the PLL is: ； For proportional gain, For integral gain, It is the damping coefficient. It is the natural angular frequency.

6. The sensorless control method for a permanent magnet synchronous motor according to claim 1, characterized in that, The mathematical model includes a spatial state equation based on the dq voltage equation, the stator flux linkage equation, and the electromagnetic torque equation. The spatial state equation is as follows: Based on the dq voltage equation, stator flux linkage equation, electromagnetic torque equation, and the aforementioned spatial state equation, a correlation model Te( ) Te( ) , ; Add constraints to the association model ; , This indicates the DC bus voltage.

7. The sensorless control method for a permanent magnet synchronous motor according to claim 1, characterized in that, In step S202, by regarding The matrix data is based on An angle of ±15°-30° is used to obtain a sector-shaped data cluster.

8. The sensorless control method for a permanent magnet synchronous motor according to claim 7, characterized in that, The The matrix data is based on The angle is ±20°.

9. A sensorless control method for a permanent magnet synchronous motor according to claim 1, characterized in that, The rotational speed ω is 80% of the rotational speed point of the weakening magnetic field.

10. A system employing a sensorless control method for a permanent magnet synchronous motor as described in any one of claims 1-9, characterized in that, It includes a control module, an acquisition module, and a data processing module. The control module includes a power supply, an inverter, a motor under test, a command generator, a comparator, a PI current regulator, an SVPWM module, an abc-αβ conversion unit, an αβ-dq conversion unit, a dq-αβ conversion unit, and a position estimation module that together form a current loop. The position estimation module includes a sliding mode observer and a PLL phase-locked loop. The acquisition module includes a current acquisition device, a voltage acquisition device, and a torque sensor connected to the motor under test. The data processing module includes simulation software.

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