System and method for estimating rotor position and rotating speed of permanent magnet synchronous motor

Abstract

The invention belongs to the field of permanent magnet synchronous motors, and relates to a system and method for estimating the rotor position and rotating speed of a permanent magnet synchronous motor. A second-order generalized integrator is used for replacing a low-pass filter in a traditional sliding mode observer algorithm, high-frequency switching noise and higher harmonics in a counter electromotive force signal are filtered out through the second-order generalized integrator, efficient filtering can be achieved, and phase delay cannot be caused; and meanwhile, the amplitude frequency self-adaptive frequency-locked loop is utilized to realize the self-adaption of the tracking frequency, so that the precision and the dynamic performance of the estimation system can be effectively improved, and the control performance of the permanent magnet synchronous motor is improved. The problem that the control performance of the system is poor due to the sliding mode buffeting effect and higher harmonic noise interference in the high-speed stage of the permanent magnet synchronous motor is solved.

Description

Technical Field

[0001] The present invention belongs to the field of permanent magnet synchronous motors, and in particular relates to a permanent magnet synchronous motor rotor position and speed estimation system and method. Background Art

[0002] High-speed permanent magnet synchronous motors are widely used in new energy vehicles, industrial automation, wind power generation and other fields due to their high power density, good dynamic performance and low maintenance cost. However, the sensorless control technology of high-speed permanent magnet synchronous motors relies on accurate rotor position and speed estimation. The sliding mode observer algorithm (SMO) is used to estimate the rotor position and speed, and is combined with a low-pass filter (LPF) for filtering. Although this sliding mode observer and low-pass filter algorithm can effectively estimate the rotor speed and position, and improve the robustness of the system, its estimation performance also depends on accurate motor models and appropriate parameter tuning estimation. In addition, the filtering effect is usually not good at high speeds, which will cause filtering delays. There are still high-frequency sliding mode jitter and high-frequency noise interference, which seriously affect the control accuracy and overall control performance of the system. Summary of the invention

[0003] The present invention provides a permanent magnet synchronous motor rotor position and speed estimation system and method, which solve the problem of poor system control performance caused by sliding mode jitter effect and high-frequency noise interference in the high-speed stage of the permanent magnet synchronous motor.

[0004] The basic scheme provided by the present invention is: a permanent magnet synchronous motor rotor position and speed estimation system, comprising a sliding mode observer, a subtractor, a switching function, a second-order generalized integrator, and a frequency locked loop, wherein the output end of the sliding mode observer is connected to the input end of the switching function through the subtractor, the output end of the switching function is connected to the input end of the second-order generalized integrator and the input end of the sliding mode observer, the output end of the second-order generalized integrator is connected to the input end of the frequency locked loop, and a motor rotor position signal is output through an inverse tangent function, and the output end of the frequency locked loop is used to output a motor rotor speed signal and is connected to the input end of the second-order generalized integrator.

[0005] Preferably, the number of the second-order generalized integrators is two, and the second-order generalized integrators output the back-electromotive force signals of the α and β axes, the orthogonal back-electromotive force signal, and the error signal respectively.

[0006] Further preferably, the two second-order generalized integrators have the same structure, both including two subtractors, two multipliers, a first gain link, and two integration links; the input end of the first subtractor inputs a switching function and outputs a switching value, the output end is connected to the input end of the second subtractor through the first gain link, the input end of the second subtractor is connected to the input end of the first multiplier, the output end of the first multiplier is connected to the input end of the first integration link, the output end of the first integration link outputs a back-electromotive force signal and is connected to the input end of the first subtractor, the output end of the first subtractor outputs an error signal, the output end of the first integration link is connected to the input end of the second multiplier through the second integration link, the output end of the second multiplier outputs an orthogonal back-electromotive force signal, the input ends of the first multiplier and the second multiplier are connected to a resonant frequency, and the resonant frequency is the output signal of the frequency locked loop.

[0007] Further preferably, the frequency locked loop includes three gain links, four adders, a divider, a third integral link, and a multiplier; the input end of the first adder inputs the back EMF signal and the orthogonal back EMF signal of the α axis, and the output end is connected to the input end of the second adder through the second gain link; the input end of the third adder inputs the back EMF signal and the orthogonal back EMF signal of the β axis, and the output end is connected to the input end of the second adder through the third gain link, and the output end of the second adder is connected to the input end of the third multiplier through the divider; the input end of the fourth adder inputs the error signal of the α and β axes, and the output end is connected to the input end of the third multiplier through the fourth gain link, the output end of the third multiplier is connected to the input end of the third integral link, and the output end of the third integral link outputs the motor rotor speed signal and is connected to the input end of the divider.

[0008] In another preferred step, the output end of each second-order generalized integrator is connected to the input end of the frequency locked loop through a multiplier group, each multiplier group has the same structure and includes three multipliers, the input end of the fourth multiplier inputs the back-EMF signal output by the second-order generalized integrator, and the output end is connected to the input end of the first adder; the input end of the fifth multiplier inputs the orthogonal back-EMF signal output by the second-order generalized integrator, and the output end is connected to the input end of the first adder; the input end of the fifth multiplier is connected to the back-EMF signal and the orthogonal back-EMF signal output by the second-order generalized integrator, and the output end is connected to the input end of the fourth adder.

[0009] Preferably, the current dynamic error equation of the sliding mode observer is:

[0010]

[0011] In the formula, i α 、i β 、e α 、e βThey represent the stator current and back-EMF signal of the α and β axes when the motor is stationary in two phases; L s is the inductance of the motor stator winding; R is the stator resistance of the motor; is the error between the observed stator current value and the actual current value; is the observed current value of the motor stator; k is the gain of the sliding mode observer.

[0012] Preferably, the switching function equation is:

[0013]

[0014] In the formula, z α 、z β They represent the current and back-EMF components of the motor in the α and β coordinate systems when the two phases are stationary; i α 、i β They represent the stator currents of the α and β axes respectively when the motor is stationary in two phases; is the observed current value of the motor stator; k is the gain of the sliding mode observer.

[0015] The principle and advantage of the system of the present invention are as follows: compared with the estimation system using a low-pass filter and a phase-locked loop in the prior art, the second-order generalized integrator (SOGI) of the present invention is combined with an amplitude-frequency adaptive frequency-locked loop (FLL), and the estimation system can adaptively adjust the filtering characteristics of the second-order generalized integrator according to the frequency of the input signal, thereby having better filtering effect and estimation accuracy.

[0016] Among them, the second-order generalized integrator (SOGI) has good bandpass filtering characteristics at the resonant frequency. It is a second-order bandpass filter with frequency adaptive function. The second-order generalized integrator will be introduced to replace the low-pass filter in the existing sliding mode observer algorithm, filter the high-frequency switching noise and high-order harmonics in the back-EMF signal estimated by the sliding mode observer (SMO), extract the estimated value of the back-EMF signal, avoid the interference of high-frequency harmonics and switching noise, and improve the estimation accuracy of the sliding mode observer algorithm; the second-order generalized integrator can efficiently filter high-order harmonics and high-frequency switching noise in the high-speed stage of the permanent magnet synchronous motor without causing phase delay, avoiding the delay and accuracy loss problems in the high-speed stage of the permanent magnet synchronous motor, so that the estimation system has a higher estimation accuracy, thereby effectively reducing the sliding mode jitter effect and high-frequency noise interference of the permanent magnet synchronous motor, and improving the system control accuracy of the high-speed stage of the permanent magnet synchronous motor;

[0017] At the same time, the frequency-adaptive frequency-locked loop (FLL) is used to achieve adaptive tracking frequency. When the signal frequency changes, the system parameters can be quickly adjusted to ensure that the filter is always in the best working state, effectively improving the accuracy and dynamic performance of the estimation system.

[0018] The second-order generalized integrator (SOGI) is combined with an amplitude-frequency adaptive frequency-locked loop (FLL). The amplitude-frequency adaptive frequency-locked loop (FLL) module can parse the signal frequency value, and after the parameters are selected, the signal processing effect will no longer be affected by the amplitude and frequency conversion of the input signal. The system structure can maintain high-precision estimation of the rotor position and speed signals under different working conditions, thereby ensuring the control performance of the system.

[0019] Compared with the existing sliding mode observer algorithm structure, this system exhibits excellent filtering characteristics under high-frequency noise and dynamic frequency changes, and can extract the frequency value of the signal, providing a new solution for the sensorless control of permanent magnet synchronous motors and has high engineering application value.

[0020] A method for estimating the rotor position and speed of a permanent magnet synchronous motor comprises the following steps:

[0021] S1: After coordinate transformation, the three-phase current is converted into the two-phase current i of the α and β axes. α and i β , and according to the two-phase current i α and i β Calculate the two-phase voltage u α and u β ;

[0022] S2: The two-phase voltage u α and u β Input the sliding mode observer to obtain the motor stator observation current value

[0023] S3: Observe the motor stator current value The difference is input into the switching function to obtain the switching quantity z. α and z β ;

[0024] S4: Set the switch quantity z α and z β Input the second-order generalized integrator to get the back EMF signal Orthogonal back EMF signal and the error signal ε α , ε β ;

[0025] S5: The back EMF signal The estimated value of the motor rotor position is obtained through the inverse tangent function output; the error signal ε α , ε β And the orthogonal back EMF signal Input the amplitude-frequency adaptive frequency-locked loop to obtain the estimated value of the motor rotor speed.

[0026] Preferably, in step S1, the two-phase current i α and i β The two-phase voltage u is obtained by calculating the current loop α and u β .

[0027] Preferably, in step S5, the output of the amplitude-frequency adaptive frequency-locked loop is used as the passband frequency of the second-order generalized integrator, which is used for the second-order generalized integrator in step S2 to adjust the switching quantity z α and z β Perform filtering.

[0028] The principle and advantage of the method of the present invention are as follows: the method uses a second-order generalized integrator to filter the back-electromotive force signal and the orthogonal back-electromotive force signal output by the sliding mode observer (SMO), extracts the estimated value of the signal, improves the estimation accuracy of the sliding mode observer algorithm, can effectively filter out high-frequency harmonics in the high-speed stage of the permanent magnet synchronous motor, and suppresses the interference of high-frequency switching noise, does not cause phase delay, avoids the delay and accuracy loss problems in the high-speed stage of the permanent magnet synchronous motor, solves the problems of poor filtering effect caused by the use of low-pass filters in the prior art, and low estimation accuracy of the estimation system caused by filtering delay, and effectively improves the control performance of the permanent magnet synchronous motor high-speed stage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a system structure diagram of the present invention;

[0030] Figure 2 This is a structural diagram of the amplitude-frequency adaptive SOGI-FLL of the present invention;

[0031] Figure 3 is the resonant frequency ω of the second-order generalized integrator input of the present invention f =100, Bode plot of transfer function D(s) when damping coefficient ξ changes;

[0032] Figure 4 The damping coefficient ξ of the second-order generalized integrator of the present invention is 1, and the resonant frequency ω f Bode plot of the transfer function D(s) when it changes;

[0033] Figure 5 is a flow chart of the method of the present invention;

[0034] Figure 6 A waveform comparison diagram of back EMF processed by an existing estimation system and an estimation system with amplitude-frequency adaptive SOGI-FLL according to the present invention;

[0035] Figure 7A waveform comparison diagram of harmonic content between an existing estimation system and an estimation system with amplitude-frequency adaptive SOGI-FLL according to the present invention;

[0036] Figure 8 A comparison diagram of the rotor speed and actual speed waveform estimated by the existing estimation system and the estimation system with amplitude-frequency adaptive SOGI-FLL according to the present invention;

[0037] Fig. 9 A comparison diagram of the rotation speed errors processed by the existing estimation system and the estimation system with amplitude-frequency adaptive SOGI-FLL according to the present invention;

[0038] Fig.10 A comparison diagram of the rotor positions estimated by the existing estimation system and the estimation system with amplitude-frequency adaptive SOGI-FLL according to the present invention;

[0039] Fig.11 The present invention is a position error comparison diagram between an existing estimation system and an estimation system with amplitude-frequency adaptive SOGI-FLL. DETAILED DESCRIPTION

[0040] The following is further described in detail through specific implementation methods:

[0041] The specific implementation process is as follows: Figure 1 to Figure 2 A permanent magnet synchronous motor rotor position and speed estimation system, comprising a sliding mode observer, a subtractor, a switching function, a second-order generalized integrator, and a frequency-locked loop, wherein the output end of the sliding mode observer is connected to the input end of the switching function through the subtractor, the output end of the switching function is connected to the input end of the second-order generalized integrator and the input end of the sliding mode observer, the output end of the second-order generalized integrator is connected to the input end of the frequency-locked loop, and the motor rotor position signal is output through an inverse tangent function The frequency-locked loop output terminal is used to output the motor rotor speed signal And connect the input of the second-order generalized integrator.

[0042] The current dynamic error equation of the sliding mode observer is:

[0043]

[0044] In the formula, i α 、i β 、e α 、e β They represent the stator current and back-EMF signal of the α and β axes when the motor is stationary in two phases; L s is the inductance of the motor stator winding; R is the stator resistance of the motor; is the error between the observed stator current value and the actual current value; is the observed current value of the motor stator; k is the gain of the sliding mode observer.

[0045] The switching function equation is:

[0046]

[0047] In the formula, z α 、z β They represent the current and back-EMF components of the motor in the α and β coordinate systems when the two phases are stationary; i α 、i β They represent the stator currents of the α and β axes respectively when the motor is stationary in two phases; is the observed current value of the motor stator; k is the gain of the sliding mode observer.

[0048] The number of the second-order generalized integrators is two, and the input end of each second-order generalized integrator inputs the switch quantity z of the α and β axes respectively. α 、z β The output terminals output the back EMF signals of the α and β axes respectively. And the orthogonal back EMF signal The error signal ε, the orthogonal back EMF signal Includes orthogonal back EMF signals for α and β axes The error signal ε includes the error signals ε of the α and β axes α , ε β ;

[0049] like Figure 2 As shown in Figure 1, the two second-order generalized integrators have the same structure, including two subtractors, two multipliers, the first gain link, and two integration links. α The second-order generalized integrator structure is as follows: the input end of the first subtractor of the α-axis inputs the switching function and outputs the switching value z of the α-axis α The output end is connected to the input end of the second subtractor through the first gain link, the input end of the second subtractor is connected to the input end of the first multiplier, the output end of the first multiplier is connected to the input end of the first integral link, and the output end of the first integral link outputs the back-electromotive force signal of the α axis and connected to the input end of the first subtractor, which converts the switch value z of the α axis into α , Back EMF signal The output end outputs the error signal ε of the α axis. α The output end of the first integral link is connected to the input end of the second multiplier through the second integral link, and the output end of the second multiplier outputs the orthogonal back-electromotive force signal of the α axis Processing of β-axis switching value z βThe second-order generalized integrator structure is as follows: the input end of the first subtractor of the β axis inputs the switching function and outputs the switching value z of the β axis β The output end is connected to the input end of the second subtractor through the first gain link, the input end of the second subtractor is connected to the input end of the first multiplier, the output end of the first multiplier is connected to the input end of the first integral link, and the output end of the first integral link outputs the back-electromotive force signal of the β axis and connected to the input end of the first subtractor, which converts the switch value z of the β axis into β , Back EMF signal The output end outputs the error signal ε of the β axis. β The output end of the first integral link is connected to the input end of the second multiplier through the second integral link, and the output end of the second multiplier outputs the orthogonal back-electromotive force signal of the α axis The input ends of the first multiplier and the second multiplier of the α-axis and the β-axis are connected to a resonant frequency, and the resonant frequency is the output signal of the frequency locked loop.

[0050] In this embodiment, the gain of the first gain link is It can take into account both filtering effect and response performance.

[0051] The transfer function of the second-order generalized integrator is expressed as:

[0052]

[0053] Where ξ is the damping coefficient; ω f is the resonant frequency of the second-order generalized integrator; s is the complex variable in the Laplace transform.

[0054] like Figure 3 As shown, it is the resonant frequency ω of the second-order generalized integrator input f The Bode diagram of the transfer function D(s) when ξ is 100 and the value of ξ changes shows that as the value of ξ decreases, the resonant frequency ω f The more obvious the attenuation of the surrounding noise signal is, the smaller the ξ value is, the better the filtering effect is. However, at the same time, the passband bandwidth of the filter will be reduced, resulting in a slower response speed of the system. Figure 4 The second-order generalized integrator ξ value is 1, and the resonant frequency ω f From the Bode plot of the transfer function D(s) when the frequency changes, it can be seen that the second-order generalized integrator is an adaptive bandpass filter, and its bandwidth center is the resonant frequency of the second-order generalized integrator. f As the frequency changes, its amplitude-frequency characteristic curve moves left and right adaptively.

[0055] From the above analysis, we can see that in the second-order generalized integrator at the resonant frequency ω fIt has good bandpass filtering characteristics and is a second-order bandpass filter with frequency adaptive function. It is applied to the rotor position and speed estimation based on the sliding mode observer algorithm, replacing the low-pass filter in the existing estimation system, and the switching signal z estimated by the sliding mode observer is α 、z β Perform filtering to remove interference from high-frequency harmonics and high-frequency switching noise, and extract the estimated value of the back-EMF signal The accuracy of the estimation system is effectively improved, thereby solving the problem of permanent magnet synchronous motors being affected by high-frequency sliding mode jitter and high-frequency noise interference at high speed, which affects the control accuracy and overall control performance of the system.

[0056] The frequency-locked loop includes three gain links, four adders, a divider, a third integral link, and a multiplier; the input end of the first adder inputs the back-electromotive force signal of the α-axis Orthogonal back EMF signal The output end is connected to the input end of the second adder through the second gain link; the input end of the third adder inputs the back electromotive force signal of the β axis Orthogonal back EMF signal The output end is connected to the input end of the second adder through the third gain link, and the output end of the second adder is connected to the input end of the third multiplier through the divider; the input end of the fourth adder inputs the error signal ε of the α and β axes α , ε β The output end is connected to the input end of the third multiplier through the fourth gain link, the output end of the third multiplier is connected to the input end of the third integral link, and the output end of the third integral link outputs the motor rotor speed signal The output end of the second adder is connected to the denominator of the divider, and the output end of the third integral link is connected to the numerator of the divider.

[0057] The gains of the second gain link and the third gain link are 0.5.

[0058] The output end of each second-order generalized integrator is connected to the input end of the frequency-locked loop through a multiplier group. Each multiplier group has the same structure and includes three multipliers, namely, a fourth multiplier, a fifth multiplier, and a sixth multiplier. The two input ends of the fourth multiplier of the α-axis are both input with the α-axis back-EMF signal output by the second-order generalized integrator. The output end is connected to the input end of the first adder; the two input ends of the fifth multiplier are both input with the α-axis orthogonal back-electromotive force signal output by the second-order generalized integrator The output end is connected to the input end of the first adder; the two input ends of the sixth multiplier are respectively connected to the α-axis back-electromotive force signal output by the second-order generalized integrator Orthogonal back EMF signal The output end is connected to the input end of the fourth adder of the frequency locked loop. Both input ends of the β-axis fourth multiplier are input with the α-axis back-EMF signal output by the second-order generalized integrator. The output end is connected to the input end of the first adder; the two input ends of the fifth multiplier are both input with the β-axis orthogonal back-electromotive force signal output by the second-order generalized integrator The output end is connected to the input end of the first adder; the two input ends of the sixth multiplier are respectively connected to the β-axis back-electromotive force signal output by the second-order generalized integrator Orthogonal back EMF signal The output terminal is also connected to the input terminal of the fourth adder of the frequency locked loop

[0059] See also Figure 5 , a method for estimating the rotor position and speed of a permanent magnet synchronous motor, specifically comprising the following steps:

[0060] S1: After coordinate transformation, the three-phase current is converted into the two-phase current i of the α and β axes. α and i β , and according to the two-phase current i α and i β The two-phase voltage u is obtained by calculating the current loop α and u β ;

[0061] S2: The two-phase voltage u α and u β Input the sliding mode observer to obtain the motor stator observation current value

[0062] S3: Observe the motor stator current value The difference is input into the switching function to obtain the switching quantity z. α and z β ;

[0063] S4: Set the switch quantity z α and z β Input the second-order generalized integrator to get the back EMF signal Orthogonal back EMF signal and the error signal ε α , ε β ;

[0064] S5: The back EMF signal The estimated value of the motor rotor position is obtained through the inverse tangent function output; the error signal ε α , ε β And the orthogonal back EMF signal Input the amplitude-frequency adaptive frequency-locked loop to obtain the estimated value of the motor rotor speed.

[0065] In step S5, the output of the amplitude-frequency adaptive frequency-locked loop is used as the passband frequency of the second-order generalized integrator, which is used for the second-order generalized integrator in step S2 to adjust the switching quantity z α and z β Perform filtering.

[0066] The estimation system of the present invention is applied to a permanent magnet synchronous motor, and the motor is operated at a constant torque of 0.25 N·m and a rotation speed of 12000 rpm.

[0067] like Figure 6 As shown in FIG. 1 , a waveform comparison diagram of back EMF processed by an existing estimation system and an estimation system with amplitude-frequency adaptive SOGI-FLL is shown. Figure 7 As shown in the figure, it is a waveform comparison diagram of the harmonic content of the existing estimation system and the estimation system with amplitude-frequency adaptive SOGI-FLL. In the simulation analysis, the analysis period of the FFT module is set to 20 back-EMF periods, the motor fundamental frequency is set to 400Hz when the speed is 12000rpm, and the maximum frequency range of the analysis is 4000Hz. It can be seen that in the high-speed stage, the back-EMF waveform of the estimation system with amplitude-frequency adaptive SOGI-FLL is smoother and more sinusoidal than that of the existing estimation system; and the harmonic content is reduced from 24.61% to 8.06%, and the filtering effect is better.

[0068] like Figure 8 As shown in FIG. 1 , it is a comparison diagram of the rotor speed and actual speed waveform estimated by the existing estimation system and the estimation system with amplitude-frequency adaptive SOGI-FLL; Fig. 9 As shown, it is a comparison diagram of the speed error processed by the existing estimation system and the estimation system with amplitude-frequency adaptive SOGI-FLL; it can be seen that the noise content in the speed waveform of the existing estimation system is relatively high, and the maximum speed error reaches 255rpm. After calculation by the estimation system with adaptive filtering SOGI-FLL, the noise content in the speed waveform is significantly reduced, and the maximum speed error is reduced to 163rpm.

[0069] like Fig.10 As shown in FIG. 1 , it is a comparison diagram of the rotor position estimated by the existing estimation system and the estimation system with amplitude-frequency adaptive SOGI-FLL; Fig.11 As shown, it is a comparison chart of the position error between the existing estimation system and the estimation system with amplitude-frequency adaptive SOGI-FLL; when maintaining the rotation speed of 12000rpm, the rotor position error of the existing estimation system is 5.6°, and the rotor position error of the estimation system using amplitude-frequency adaptive SOGI-FLL is reduced to 1.4°.

[0070] Combined with the above simulation results, the estimation system and method of the present invention can better suppress noise and have higher estimation accuracy for rotor position and speed, both of which are better than the traditional sliding mode observer estimation system.

[0071] The above are only embodiments of the present invention. Common knowledge such as the known specific structures and characteristics in the scheme is not described in detail here. Ordinary technicians in the relevant field know all the common technical knowledge in the technical field to which the invention belongs before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply conventional experimental means before that date. Ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A permanent magnet synchronous motor rotor position and speed estimation system, characterized in that: The invention comprises a sliding mode observer, a subtractor, a switching function, a second-order generalized integrator and a frequency-locked loop. The output end of the sliding mode observer is connected to the input end of the switching function through the subtractor. The output end of the switching function is connected to the input end of the second-order generalized integrator and the input end of the sliding mode observer. The output end of the second-order generalized integrator is connected to the input end of the frequency-locked loop and outputs a motor rotor position signal through an inverse tangent function. The output end of the frequency-locked loop is used to output a motor rotor speed signal and is connected to the input end of the second-order generalized integrator.

2. The permanent magnet synchronous motor rotor position and speed estimation system according to claim 1, characterized in that: The number of the second-order generalized integrators is two, and the second-order generalized integrators output the back-electromotive force signals of the α and β axes, the orthogonal back-electromotive force signal, and the error signal respectively.

3. The permanent magnet synchronous motor rotor position and speed estimation system according to claim 2, characterized in that: The two second-order generalized integrators have the same structure, and both include two subtractors, two multipliers, a first gain link, and two integral links; the input end of the first subtractor inputs a switching function to output a switching value, the output end is connected to the input end of the second subtractor through the first gain link, the input end of the second subtractor is connected to the input end of the first multiplier, the output end of the first multiplier is connected to the input end of the first integral link, the output end of the first integral link outputs a back-electromotive force signal and is connected to the input end of the first subtractor, the output end of the first subtractor outputs an error signal, the output end of the first integral link is connected to the input end of the second multiplier through the second integral link, the output end of the second multiplier outputs an orthogonal back-electromotive force signal, the input ends of the first multiplier and the second multiplier are connected to a resonant frequency, and the resonant frequency is the output signal of the frequency locked loop.

4. The permanent magnet synchronous motor rotor position and speed estimation system according to claim 2, characterized in that: The frequency locked loop includes three gain links, four adders, a divider, a third integral link, and a multiplier; the input end of the first adder inputs the back electromotive force signal and the orthogonal back electromotive force signal of the α axis, and the output end is connected to the input end of the second adder through the second gain link; the input end of the third adder inputs the back electromotive force signal and the orthogonal back electromotive force signal of the β axis, and the output end is connected to the input end of the second adder through the third gain link, and the output end of the second adder is connected to the input end of the third multiplier through the divider; the input end of the fourth adder inputs the error signal of the α and β axes, and the output end is connected to the input end of the third multiplier through the fourth gain link, the output end of the third multiplier is connected to the input end of the third integral link, and the output end of the third integral link outputs the motor rotor speed signal and is connected to the input end of the divider.

5. The permanent magnet synchronous motor rotor position and speed estimation system according to claim 4, characterized in that: The output end of each second-order generalized integrator is connected to the input end of the frequency locked loop through a multiplier group, each multiplier group has the same structure and includes three multipliers, the input end of the fourth multiplier inputs the back-electromotive force signal output by the second-order generalized integrator, and the output end is connected to the input end of the first adder; the input end of the fifth multiplier inputs the orthogonal back-electromotive force signal output by the second-order generalized integrator, and the output end is connected to the input end of the first adder; the input end of the fifth multiplier is connected to the back-electromotive force signal and the orthogonal back-electromotive force signal output by the second-order generalized integrator, and the output end is connected to the input end of the fourth adder.

6. The permanent magnet synchronous motor rotor position and speed estimation system according to claim 1, characterized in that: The current dynamic error equation of the sliding mode observer is: In the formula, e α 、e β They represent the back EMF signals of the α and β axes when the motor is stationary in two phases; i α 、i β They represent the stator current of the α and β axes when the motor is stationary in two phases; L s is the inductance of the motor stator winding; R is the stator resistance of the motor; are the errors between the observed stator current and the actual current for the α and β axes respectively; are the observed motor stator current values ​​of the α and β axes respectively; k is the gain of the sliding mode observer.

7. The permanent magnet synchronous motor rotor position and speed estimation system according to claim 1, characterized in that: The switching function equation is: In the formula, z α 、z β They represent the back EMF components in the α and β coordinate systems when the motor is stationary in two phases; i α 、i β They represent the stator currents of the α and β axes respectively when the motor is stationary in two phases; are the observed motor stator current values ​​of the α and β axes respectively; k is the gain of the sliding mode observer.

8. A method for estimating the rotor position and speed of a permanent magnet synchronous motor, characterized in that: The specific steps include: S1: After coordinate transformation, the three-phase current is converted into the two-phase current i of the α and β axes. α 、i β , and according to the two-phase current i of the α and β axes α 、i β The two-phase voltage u of α and β axes is calculated α 、u β ; S2: The two-phase voltage u α and u β Input the sliding mode observer to obtain the motor stator observation current value S3: Observe the motor stator current value The difference is input into the switching function to obtain the switching quantity z. α 、z β ; S4: Set the switch quantity z α 、z β Input the second-order generalized integrator to get the back EMF signal Orthogonal back EMF signal and the error signal ε α , ε β ; S5: The back EMF signal The estimated value of the motor rotor position is obtained through the inverse tangent function output; the error signal ε α , ε β And the orthogonal back EMF signal Input the amplitude-frequency adaptive frequency-locked loop to obtain the estimated value of the motor rotor speed.

9. The method for estimating the rotor position and speed of a permanent magnet synchronous motor according to claim 8, characterized in that: In step S1, the two-phase current i α 、i β The two-phase voltage u is obtained by calculating the current loop α 、u β .

10. The method for estimating the rotor position and speed of a permanent magnet synchronous motor according to claim 8, characterized in that: In step S5, the output of the amplitude-frequency adaptive frequency-locked loop is used as the passband frequency of the second-order generalized integrator, which is used for the second-order generalized integrator in step S2 to adjust the switching quantity z α and z β Perform filtering.

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